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Energy Performance Analysis of an Integrated Distributed Variable-Frequency Pump and Water Storage System for District Cooling Systems

Energy Performance Analysis of an Integrated Distributed Variable-Frequency Pump and Water... applied sciences Article Energy Performance Analysis of an Integrated Distributed Variable-Frequency Pump and Water Storage System for District Cooling Systems Yichi Zhang, Chuanxin Chen and Jianjun Xia * Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China; zhangyic16@mails.tsinghua.edu.cn (Y.Z.); cindychen528@126.com (C.C.) * Correspondence: xiajianjun@tsinghua.edu.cn; Tel.: +86-010-6277-5553 Received: 30 September 2017; Accepted: 3 November 2017; Published: 6 November 2017 Abstract: In a district cooling system (DCS), the distribution system (i.e., cooling water system or chilled water system) will continue to be a critical consideration because it substantially contributes to the total energy consumption. Thus, in this paper, a new distributed variable-frequency pump (DVFP) system with water storage (WS) for cooling water is adapted to a DCS with large end-use cooling load fluctuations. The basic principle and energy saving potential of the new system is analyzed. A case study of a DCS with a conventional central circulating pump (CCCP) system is presented to compare the energy consumption and the operating performance of CCCP and DVFP systems that are exposed to various weather conditions. The methods to perform this case study include, cooling load simulation and the modeling of two water distribution networks and systems via several commercial software packages. By replacing the throttling valves with a DVFP, the pump efficiency is increased and transportation energy consumption is reduced. Additionally, by introducing water tank storage, the cooling water is cooled at night and is released at a peak hour during the daytime, thereby further reducing the energy cost. As compared to the field test results of the CCCP system, the daily electrical energy saved by the DVFP and WS system is approximately 57% for a cooling water pump system on the hottest day in summer. This value also corresponds to approximately 10% of the energy saved for the entire system. Furthermore, additional energy could be saved under partial loading conditions. Keywords: district cooling; distributed variable-frequency pumps; water storage; cooling water; energy saving 1. Introduction District cooling systems (DCSs), which generate cold water in a central plant that is distributed to end uses to fulfill its cooling demands, have become a widely used solution for large-area buildings in many countries [1,2]. Generally, there are two types of DCSs that differ according to the type of water that is produced at the central plant; the two types are as follows: (1) a centralized chilled water system; and, (2) a centralized cooling water system. In the first type, the central chiller is designed to have large cooling capacity to promote a high coefficient of performance (COP); additionally, the removal of terminal chillers makes it possible to more efficiently utilize the building space [3]. It also provides an ideal platform for interrelated thermal technologies implementing tri-generation [2] or thermal storage [4]. The second system, also referred to as the water-loop heat pump system, produces cooling water via a cooling tower or natural sources, such as seawater and transports it to end-use chillers [5]. This system is designed to utilize the distributed chillers to achieve variable cooling loads in end uses. Another advantage of this system is that it can incorporate vast varieties of cooling sources and recover Appl. Sci. 2017, 7, 1139; doi:10.3390/app7111139 www.mdpi.com/journal/applsci Appl. Sci. 2017, 7, 1139 2 of 16 the rejected heat inside of a building [6–8]. Because systems with variable cooling loads are the focus of this study, the second system with centralized cooling water was selected for further research. However, it should be noted that DCSs do possess limitations. For instance, the water transportation system consumes a large amount of energy, as an America-based study showed that the pumping system in a typical DCS consumed 30% of the total energy of the system [9]. The reason for this can be explained by the design and control strategy of conventional central circulation pump (CCCP) systems. The central circulating pumps are designed for the most remote consumer; thus, the flow rate and pump head are quite excessive for the other consumers. Therefore, the remaining consumers must employ valves to control water flow, which responds slow and causes additional losses in local pressure. The use of throttling valves alters the resistance characteristics of the network, resulting in the low efficiency of pump operation. In addition, the precision of water flow control is reduced when the end-use cooling demand varies according to each consumer, which leads to an imbalance in cold supply. Under the assumption that a large flow of water would offset the cold supply imbalance, most of the pumps currently in use generate large flows, which again increases transport energy consumption [10]. However, these problems can be solved by employing distributed variable-frequency pumps (DVFPs). When the cooling load varies, the chiller adjusts the heat that is released to condensing water side and the DVFP adjusts the pump speed to control the cooling water flow, maintain the supply, and return water temperature difference (DT) at a preset value. Each DVFP is designed to provide the pressure drop in corresponding end-use building and main pipes. Thus, the main circulating pumps, which are also referred to as primary pumps (PPs), are removed and the transportation energy is reduced. By replacing the valves with pumps, the pump head is reduced and the resistance characteristics of the main pipes become relatively stable, thereby increasing pump efficiency. Additionally, variable-frequency pumps are able to rapidly and precisely adjust water flow, while maintaining a level of high-efficiency operation, preventing extra flow, and satisfying the specific cooling demand of each end-user. Variable frequency pumps (VFPs) have been studied for many years and are implemented in a wide variety of applications in fields related to air-conditioning, district heating, and municipal water distribution. Some studies have focused on control strategies for VFPs. Ma and Wang optimized pump speed and sequence control in a complex air-conditioning system to save energy [11]. Wang and Burnett developed a control strategy that implements an adaptive and derivative strategy to optimize the speed of pumps by resetting the pressure set point [12]. Marchi studied the components in pumping systems to provide insight into the assessment of VFPS efficiency and energy consumption [13]. Pan studied the performance of several check valves that were connected to DVFPs and the influence of these valves on energy consumption [14]. Some studies also focused on the performance of DVFPs in actual projects and calculated the energy-saving and cost-saving potential; this includes the hydraulic performance of a district heating project in Kuerle, China [15], the minimum of capital cost and energy consumption in a district heating projects in Dalian, China [16], and a project involving a municipal water distribution system [17]. Gamberi et al. simulated a multi-zone heating system and developed the Newton-Raphson method to solve various hydraulic problems [18]. Sheng analyzed the factors affecting energy saving rate in the DVFPs system [19]. Although these studies yielded significant contributions to the field, most current studies are focused on chilled water pumps and fail to adequately investigate cooling water pumps, the influence of cooling water temperature on the entire system, and, more significantly, the chiller performance. Furthermore, there is a lack of studies on timely effective system performance in response to cooling loads that fluctuate in real time. Alternatively, thermal storage systems including water storage, ice storage, and eutectic salt storage systems have also been widely used in DCSs. Under the conditions of time-of-use tariff of electricity, thermal storage systems produce and store hot/cold water overnight at relatively cheaper electricity costs and release the stored contents at the peak price time. As a result, the system has been proven as cost-saving and peak shaving, which is beneficial for electric power plants [20,21]. Furthermore, the Appl. Sci. 2017, 7, 1139 3 of 16 nominal cooling capacity can be reduced. As an example, many studies focusing on cold storage have aimed to optimize the control and performance. Kawashima et al. presented an optimal control strategy based on artificial neural networks to predict cooling loads [22]. Chan et al. conducted simulations to evaluate the performance of a combined DCS and ice storage system, and studied the influence of tariff structures on the combined system [23]. Hasnain reviewed the research on thermal storage and compared three cold storage media and rated ice storage [24]. In contrast to the numerous studies on other types of storage systems, there is a lack of studies and applications on cooling water storage. Water temperature from cooling towers is low, due to the low environmental wet bulb temperature at night, plus the valley electrical price it is cost-efficient to use cooling towers to generate cooling water and store it overnight. Furthermore, cooling water with lower temperature supplied during daytime hours would increase the COP of the chiller, thereby further decreasing the electricity consumption. Additionally, with the assistance of water tanks, there is no need to keep pumps and cooling towers in constant operation; this provides a greater flexibility for the controlling system. Therefore, by exploiting the advantages of each of the related components, a novel DVFP system with water storage (DVFP and WS) designed for implementation in a DCS with variable end-user-required cooling loads has been developed and is proposed in this paper. In this new system, chillers and variable-frequency pumps are installed at each end-use building and independently controlled while sharing a single cooling water loop. Cooling water is generated at a central cooling tower and is stored in a water tank that is located near the cooling tower. Then, the cold water in the water tank is transported to the end users. In this study, only the cooling water loop is discussed because the chilled water loop is distributed at each end use and operates independently. This paper first presents a schematic of the new system and introduces the principles of its design. Subsequently, a DCS with CCCPs in Beijing, China was selected for a case study. The system performance and energy consumption of CCCP and DVFP and WS systems are accordingly compared based on the results of the DCS case study. This procedure includes a field test of the current CCCP system to obtain operating data, a cooling load simulation by implementing DeST software (Designer ’s Simulation Toolkit) under various weather conditions, modeling of the water networks and equipment, and a calculation of the operating parameters. The simulated building load and energy consumptions of the current system are found to be in agreement with the field test results, and, as compared to the current system, the DVFP and water storage (WS) system has been proven to have energy-saving potential. 2. Design Schematic and Principles A descriptive schematic diagram of the current CCCP system is shown in Figure 1. S1–S12 illustrate the terminal end users with chillers; the primary pumps are responsible for circulating the whole cooling water loop, whereas cooling towers are designed to coordinate with them. The power of primary pumps Q in units W is given as: p p 2.72G H total p p Q = (1) p p where H is the pump head (unit: mH O), G is the total flow rate (unit: m /h), and h is the p p 2 1 total efficiency of the pump. The pump head, which is the total pressure drop of the entire water loop, is simply described as H = H + H + H (2) p p ct sn m where H is cooling tower pressure loss. H is the pressure loss in most unfavorable end use. H is ct sn m the loss in main pipes. All of the units are in mH O. The losses in auxiliary equipment, such as check valves are also considered in corresponding components. For a CCCP system, because quantity control is only implemented on the primary pumps and cooling tower, the power of cooling towers is the product of the number of operating towers and nominal power. For water pumps, the relationship between the pump head and water flow rate can be written as a polynomial below: Appl. Sci. 2017, 7, 1139 4 of 16 H = a + a G + a G (3) p p 0 1 p p 2 p p Appl. Sci. 2017, 7, 1139 4 of 16 where a , a , and a are obtained through pump operation curve-fitting data. Additionally, the 0 1 2 relationship where between , , and pr essur are obtai e lossn and ed through p flow rateuin mp opera water loops tion curve- can be fitting da written ta. asAdditionally, the relationship between pressure loss and flow rate in water loops can be written as H = H + bG (4) total (4) H= + where H is the static pressure loss and b is calculated from the resistance characteristics of the pipes where is the static pressure loss and is calculated from the resistance characteristics of the and auxiliary equipment. The pumps operate at the intersection of the pump curve (3) and loops pipes and auxiliary equipment. The pumps operate at the intersection of the pump curve (3) and curve (4). loops curve (4). End-use water flow is controlled by throttling valves fixed at each branch. During operation, the End-use water flow is controlled by throttling valves fixed at each branch. During operation, the pumps operate at a constant speed and valve operation is variable; this alters the parameter in pumps operate at a constant speed and valve operation is variable; this alters the parameter b in Equation Equation (4), as well as the loops resistance curve, thereby changing the operating point of the pumps (4), as well as the loops resistance curve, thereby changing the operating point of the pumps and decreasing and decreasing pump efficiency as a result. Furthermore, water flow cannot be controlled by valves pump efficiency as a result. Furthermore, water flow cannot be controlled by valves as precisely as is as precisely as is required by the end user; thus, imbalance of the cold supply between the nearest required by the end user; thus, imbalance of the cold supply between the nearest building and building building and building frequently occurs. The actual water flow distributed at each end use is not frequently occurs. The actual water flow distributed at each end use is not related to the cooling load; related to the cooling load; thus, the ∆T and the subsequent COP of the chiller is affected. A common thus, the DT and the subsequent COP of the chiller is affected. A common way to offset this DT imbalance way to offset this ∆T imbalance is to increase the circulating water flow, which would also increase is to increase the circulating water flow, which would also increase energy consumption. energy consumption. Figure 1. Schematic diagram of the current conventional central circulating pump (CCCP) system. Figure 1. Schematic diagram of the current conventional central circulating pump (CCCP) system. However, the DVFP and WS system shown in Figure 2 has made many improvements. The However, the DVFP and WS system shown in Figure 2 has made many improvements. The water water tank has partitioned the cooling water into two different sides: the source side and tank has partitioned the cooling water into two different sides: the source side and transportation side. transportation side. On the transportation side, DVFPs fixed at each terminal are designed to initiate On the transportation side, DVFPs fixed at each terminal are designed to initiate the pressure drop the pressure drop in the end-use water loop and corresponding main pipes. It is capable of varying in the end-use water loop and corresponding main pipes. It is capable of varying the pump speed to the pump speed to control water flow. The flow rate of the i-th pump in pump curve (3) is control water flow. The flow rate of the i-th pump G in pump curve (3) is si = (5) G = G (5) si nominal where n is the operating frequency, which can be a 50ltered and is the nominal flow rate of the pump, which is designed according to the maximum cooling load. is the sum of . where n is the operating frequency, which can be altered and G is the nominal flow rate of the nominal The resistance curve at the end use remains stable as the speed of the pumps changes, assuring pump, which is designed according to the maximum cooling load. G is the sum of G . si pump efficiency. Note that the PPs are removed for this observation, the tota total l power of DVFPs can The resistance curve at the end use remains stable as the speed of the pumps changes, assuring be calculated as pump efficiency. Note that the PPs are removed for this observation, the total power of DVFPs can be calculated as Q=2.72 (6) si Q = 2.72G (6) å si si where is the pump head of the i-th pump. Thus, the transportation energy-saving potential is i=1 feasible because the following occurs: Appl. Sci. 2017, 7, 1139 5 of 16 Appl. Sci. 2017, 7, 1139 5 of 16 where H is the pump head of the i-th pump. Thus, the transportation energy-saving potential is si feasible because the following occurs: • Water flow is controlled as required so there is no extra water flow. • The pump operating point remains stable to ensure pump efficiency. Water flow is controlled as required so there is no extra water flow. • The removal of valves prevents extra pressure loss. The pump operating point remains stable to ensure pump efficiency. • The PPs are removed, and not all of the water flow needs to overcome main pipe resistance. The removal of valves prevents extra pressure loss. The PPs are removed, and not all of the water flow needs to overcome main pipe resistance. On the source side, the cooling towers and cooling tower pumps are quantity controlled to change the flow rate as required. In this case, the cooling tower pumps only provide the pressure loss On the source side, the cooling towers and cooling tower pumps are quantity controlled to change on the source side; this drop is quite small. Additionally, the storage tank affords increased pump the flow rate as required. In this case, the cooling tower pumps only provide the pressure loss on the flexibility and cooling tower control flexibility. As based on the time-of-use electricity tariff, the source side; this drop is quite small. Additionally, the storage tank affords increased pump flexibility cooling source would generate an increased amount of cold water and store it in the water tank and cooling tower control flexibility. As based on the time-of-use electricity tariff, the cooling source during the time of minimum electricity cost, and subsequently reduce the usage during the peak cost would generate an increased amount of cold water and store it in the water tank during the time of time. In order to make full use of the water tank, it is stratified into several horizontal layers [25]. minimum electricity cost, and subsequently reduce the usage during the peak cost time. In order to Small holes exist throughout the partition to allow water to freely flow between layers. This study make full use of the water tank, it is stratified into several horizontal layers [25]. Small holes exist takes a five-layer water tank as an example. The relatively hot water returning from each chiller throughout the partition to allow water to freely flow between layers. This study takes a five-layer condenser flows into the top layer, where it is extracted and pumped into the cooling tower. The water tank as an example. The relatively hot water returning from each chiller condenser flows into the outlet water from the cooling tower flows into the bottom layer and is then pumped to the top layer, where it is extracted and pumped into the cooling tower. The outlet water from the cooling transportation side. Middle layers 2–4 are storage and transition layers between the relatively hot tower flows into the bottom layer and is then pumped to the transportation side. Middle layers 2–4 are upper layer and cold bottom layer. This design minimizes the intermixing of the water, which is storage and transition layers between the relatively hot upper layer and cold bottom layer. This design partitioned according to temperature level, to ensure that the water transported into the end use is minimizes the intermixing of the water, which is partitioned according to temperature level, to ensure always the coldest. It is considered as energy-saving because colder water decreases the condensing that the water transported into the end use is always the coldest. It is considered as energy-saving temperature and increases the COP of the chiller. because colder water decreases the condensing temperature and increases the COP of the chiller. Although the energy-saving potential of current related systems has been briefly discussed, the Although the energy-saving potential of current related systems has been briefly discussed, the new system proposed in this paper includes additional components, such as cooling tower pumps; new system proposed in this paper includes additional components, such as cooling tower pumps; thus, the total energy consumption and actual benefits of this system need to be studied in detail; thus, the total energy consumption and actual benefits of this system need to be studied in detail; and, and, these results are discussed below. these results are discussed below. Figure 2. Schematic diagram of distributed variable-frequency pump (DVFP) and water storage Figure 2. Schematic diagram of distributed variable-frequency pump (DVFP) and water storage (WS) (WS) system. system. 3. Project Case Study and Cooling Load Profile 3. Project Case Study and Cooling Load Profile A district cooling project employing CCCPs located in Northeast Beijing, China is selected as a case A district cooling project employing CCCPs located in Northeast Beijing, China is selected as a study. Field tests were performed to obtain basic information and system operating data, including energy case study. Field tests were performed to obtain basic information and system operating data, consumption, water flow rate, and temperature. Based on these data, several models were developed to including energy consumption, water flow rate, and temperature. Based on these data, several simulate cooling loads and system operation; the results have been compared to the test data. models were developed to simulate cooling loads and system operation; the results have been compared to the test data. The entire project is a commercial district comprising twelve independent sub-buildings noted as S1–S12, neighboring the central cooling plant. The location of the sub-buildings, in addition to a Appl. Sci. 2017, 7, 1139 6 of 16 Appl. Sci. 2017, 7, 1139 6 of 16 The entire project is a commercial district comprising twelve independent sub-buildings noted as topol S1–S12, ogical nei diagra ghboring m of the the cool central ing wa cooling ter networks, is plant. The shown i location n Figure 3. The of the subto -buildings, tal floor area in is 78,000 additionm to. a Most topological of these buil diagram dings of are the commercia cooling water l build networks, ings, includ is ing shown a cin in ema, re Figurst e a 3u . ran The ts, and total floor retail ar stea ores. is 78,000 The time m of o . Most peration of the of e se buildings ach of the ar se b e commer uildings, cial which is buildings, shown including in Figua re cinema, 4, is dependent on thei restaurants, andr r function etail stor . For es. The example time of , bui operation ldings S2, S of each 9, and S of these 10 oper buildings, ate 24 h a d which ay,is whereas the other build shown in Figure 4, is dependent ings only on operate their dur function. ing daytime For example, hours; further buildings more, the S2, S9, op and ening S10 time o operate f each buildin 24 h a dayg , is wher diffe eas rent. These the other characteristics significantly influence the load profile. Additionally, there are chillers fixed at each buildings only operate during daytime hours; furthermore, the opening time of each building is dif end-u ferent. se bu These ilding t characteristics o generate chil significantly led water; on- influence site inve the stigat load ion reve profile. ale Additionally d that these chil , ther ler e ar s are e chillers of the same model (nominal cooling capacity = 700 kW and COP = 3.5). fixed at each end-use building to generate chilled water; on-site investigation revealed that these chillers The t areool u of the sed same in th model is stud (nominal y to simu cooling late cooling capacity loads = i 700 s a commerci kW and COP al soft = 3.5). ware package named DeST, which has been proven to be useful in performing building load simulations [26]. Besides, there The tool used in this study to simulate cooling loads is a commercial software package named are many other simulation tools on the market and each tool has its own advantages. Many studies DeST, which has been proven to be useful in performing building load simulations [26]. Besides, there have focused on the use of efficient tool to perform effective energy profile simulation of buildings are many other simulation tools on the market and each tool has its own advantages. Many studies have [27,28]. The meteorological parameters are embedded in the software and 15 July is the full-load day focused on the use of efficient tool to perform effective energy profile simulation of buildings [27,28]. (i.e., design day) in this study. All of the model settings, including building structure, materials, The meteorological parameters are embedded in the software and 15 July is the full-load day (i.e., equipment, and lighting power density, are based on architectural drawings and the investigation of design day) in this study. All of the model settings, including building structure, materials, equipment, actual operation. This enabled simulation of the hourly cooling load of each sub-building on the and lighting power density, are based on architectural drawings and the investigation of actual design day. The hourly superposition of all of the building loads and a comparison with field test operation. This enabled simulation of the hourly cooling load of each sub-building on the design results are shown in Figure 5. The accumulated cooling load on the full-load day derived by day. The hourly superposition of all of the building loads and a comparison with field test results simulation is 69,900 kWh, while the field test result is 68,100 kWh. It can be concluded that the are shown in Figure 5. The accumulated cooling load on the full-load day derived by simulation is simulation results are in agreement with the field test results. Thus, the modeling and simulation 69,900 kWh, while the field test result is 68,100 kWh. It can be concluded that the simulation results are process are confirmed to be reasonable and can be implemented to calculate cooling loads under in agreement with the field test results. Thus, the modeling and simulation process are confirmed to be various conditions. The basic information for each of the sub-buildings is presented in Table 1, which reasonable and can be implemented to calculate cooling loads under various conditions. The basic also includes the peak cooling load and estimated cooling water flow, calculated at the ΔT = 4.5 °C information for each of the sub-buildings is presented in Table 1, which also includes the peak cooling and COP = 3.5; these results are presented in the next chapter. The maximum cooling load for all load and estimated cooling water flow, calculated at the DT = 4.5 C and COP = 3.5; these results are 2 2 buildings is 5500 kW, 70.5 W/m . presented in the next chapter. The maximum cooling load for all buildings is 5500 kW, 70.5 W/m . Figure 3. Locations of sub-buildings and water networks. Figure 3. Locations of sub-buildings and water networks. Appl. Sci. 2017, 7, 1139 7 of 16 Appl. Sci. 2017, 7, 1139 7 of 16 Appl. Sci. 2017, 7, 1139 7 of 16 Figure Figure 4. 4. Operating Operating schedule schedulessof ofS1–S12. S1–S12. Figure 4. Operating schedules of S1–S12. Figure 5. Comparison between simulation and field test results for the entire district cooling project. Figure 5. Comparison between simulation and field test results for the entire district cooling project. Figure 5. Comparison between simulation and field test results for the entire district cooling project. Table 1. Basic information of sub-buildings. Table 1. Basic information of sub-buildings. Table 1. Basic information of sub-buildings. Sub- Estimated Cooling Estimated Cooling 2 2 Floor Area/m Function Cooling Load/kW Sub-Buildings Sub- Floor Area/m Function Cooling Load/kW Estimated Cooling 2 Water Flow m /h Buildings Water Flow m /h Floor Area/m Function Cooling Load/kW Buildings Water Flow m /h S1 4287.3 Retail 337.6 74.4 S1 4287.3 Retail 337.6 74.4 S1 4287.3 Retail 337.6 74.4 S2 8033.4 24 h book store 665.6 146.7 S2 8033.4 24 h book store 665.6 146.7 S2 8033.4 24 h book store 665.6 146.7 S3 2696.8 Restaurants 246.8 54.4 S3 2696.8 Restaurants 246.8 54.4 S4 7776.2 Retail, restaurant 595.2 131.2 S3 2696.8 Restaurants 246.8 54.4 S4 7776.2 Retail, restaurant 595.2 131.2 S5 2872.8 Retail, restaurant 213.5 47.0 S4 7776.2 Retail, restaurant 595.2 131.2 S5 2872.8 Retail, restaurant 213.5 47.0 S6 8033.3 Retail, restaurant 665.7 146.7 S5 2872.8 Retail, restaurant 213.5 47.0 S6 80 S7 33.35745.3 Retail, rest Exhibitionaurant 665. 433.97 14 95.66.7 S6 8033.3 Retail, restaurant 665.7 146.7 S8 2872.8 Retail, restaurant 213.5 47.0 S7 5745.3 Exhibition 433.9 95.6 S7 57 S9 45.3 9298.9 Exhib Retail,itionr estaurant 433.9 612.1 95 134.9.6 S8 2872.8 Retail, restaurant 213.5 47.0 S10 4870.1 Retail, cafe (24 h) 486.6 107.2 S8 2872.8 Retail, restaurant 213.5 47.0 S9 9298.9 Retail, restaurant 612.1 134.9 S11 10,791.0 Retail, cinema 756.6 166.8 S9 9298.9 Retail, restaurant 612.1 134.9 S10 4870.1 Retail, cafe (24 h) 486.6 107.2 S12 10,791.0 Retail, cinema 756.6 166.8 S10 4870.1 Retail, cafe (24 h) 486.6 107.2 S11 10,791.0 Retail, cinema 756.6 166.8 S11 10,791.0 Retail, cinema 756.6 166.8 S12 10,791.0 Retail, cinema 756.6 166.8 S12 10,791.0 Retail, cinema 756.6 166.8 Appl. Sci. 2017, 7, 1139 8 of 16 4. Methods Appl. Sci. 2017, 7, 1139 8 of 16 The new system presented in this paper comprises two critical components: the DVFP component and the WS component. Two systems, the CCCP and the DVFP and WS, are evaluated, 4. Methods and their system performance is compared. Water distribution network models and equipment The new system presented in this paper comprises two critical components: the DVFP component models are developed for each system to obtain hydraulic performance data, as well as thermal and the WS component. Two systems, the CCCP and the DVFP and WS, are evaluated, and their system performance, respectively. The simulation flow of each system is designed via MATLAB software performance is compared. Water distribution network models and equipment models are developed and links the aforementioned models. Based on the cooling load results that are calculated in Section for each system to obtain hydraulic performance data, as well as thermal performance, respectively. 3, the operating parameters of the system, such as temperature and water flow rate, can be calculated The simulation flow of each system is designed via MATLAB software and links the aforementioned hourly. Subsequently, the electricity consumption and operation cost can be easily acquired for models. Based on the cooling load results that are calculated in Section 3, the operating parameters comparison. This chapter provides the details of the system-specific simulation methods, models, of the system, such as temperature and water flow rate, can be calculated hourly. Subsequently, and process; the results are presented in the next chapter. the electricity consumption and operation cost can be easily acquired for comparison. This chapter provides the details of the system-specific simulation methods, models, and process; the results are 4.1. CCCP System presented in the next chapter. In the current operating system, a branched network is used for cooling water distribution. In this occasion, there is a unidirectional flow from the cooling plant to the end use. The topological 4.1. CCCP System diagram with marked pipe length, as is shown in Figure 3, is developed for water distribution In the current operating system, a branched network is used for cooling water distribution. In this network models via HACNET software (a hydraulic simulation software developed by Tsinghua occasion, there is a unidirectional flow from the cooling plant to the end use. The topological diagram University). It should be noted that the marked pipe length includes the main pipe length and the with marked pipe length, as is shown in Figure 3, is developed for water distribution network models branched pipe length inside the building. This software is proven useful in calculating the hydraulic via HACNET software (a hydraulic simulation software developed by Tsinghua University). It should performance of a given water network system [29]. Pipe resistance, as well as the pressure loss in end be noted that the marked pipe length includes the main pipe length and the branched pipe length uses, is derived from field test results. Generally, during the full-load hour (i.e., 15:00), the total inside the building. This software is proven useful in calculating the hydraulic performance of a given cooling water flow rate required for all of the condensers is approximately 1200 m /h; at this time, the water network system [29]. Pipe resistance, as well as the pressure loss in end uses, is derived from flow rate is found to be dependent on the water temperature difference (∆T) and COP. Under this field test results. Generally, during the full-load hour (i.e., 15:00), the total cooling water flow rate condition, the frictional pressure losses in the main pipes, end-use loops, and cooling tower are 10, 10, required for all of the condensers is approximately 1200 m /h; at this time, the flow rate is found to and 5 m, respectively. The losses in the first two components include the losses in pipes and valves be dependent on the water temperature difference (DT) and COP. Under this condition, the frictional and other equipment. Consequently, six primary pumps (nominal parameters: 200 m /h, 25 m pump pressure losses in the main pipes, end-use loops, and cooling tower are 10, 10, and 5 m, respectively. head) must be running to satisfy cooling water requirements. The characteristics of these pipes and The losses in the first two components include the losses in pipes and valves and other equipment. equipment, including the pump curve, are input into the model and water flow distribution for each Consequently, six primary pumps (nominal parameters: 200 m /h, 25 m pump head) must be running end use can be calculated hourly. The distributed water flow during the full-load hour (15:00), as to satisfy cooling water requirements. The characteristics of these pipes and equipment, including the compared to the estimated requirement according to the cooling load given in Table 1, is illustrated pump curve, are input into the model and water flow distribution for each end use can be calculated in Figure 6 as an example. hourly. The distributed water flow during the full-load hour (15:00), as compared to the estimated requirement according to the cooling load given in Table 1, is illustrated in Figure 6 as an example. Figure 6. Water flow rate in each end use at 15:00. Figure 6. Water flow rate in each end use at 15:00. In most sub-buildings, the simulated flow rate (Figure 6) is significantly different from the In most sub-buildings, the simulated flow rate (Figure 6) is significantly different from the estimated requirement because of the differences in pipe length and the succeeding resistance. estimated requirement because of the differences in pipe length and the succeeding resistance. The The nearest end use receives the largest water flow, while the most unfavorable end-use receives Appl. Sci. 2017, 7, 1139 9 of 16 the least flow. In sub-building S8, the water flow difference between requirement and simulation 3 3 results can be as much as 96 m /h, while in building S1 and S6 the difference is only 3 m /h. This leads to an imbalance in cold supplies and DT values. Regarding the pumps, the operating point and efficiency was calculated via HACNET software, as based on water flow and pressure loss results. A schematic diagram of the CCCP system has been presented in Figure 1. It should be noted that, although the cooling load is only simulated once per hour, the minimum calculation time interval is set as one minute in consideration of the precision requirement of the control system and water tank simulation. For any minute in the day, the cooling load for each end use is calculated via ways talked above in Section 3, and noted as Q , Q . . . Q ; then, heat rejection in the i-th condenser Q is e1 e2 e12 ci ei Q = (COP + 1) (7) ci i COP Based on the water flow rate for each end-use G that was calculated via HACNET software, the si cooling water temperature difference in the i-th condenser DT can be determined as follows: ci DT = (8) c G si where c is the heat capacity of the water. Because of the piping insulation and minimal temperature difference between the cooling water and environment, the thermal loss during transportation is neglected in this study. However, this hypothesis is applied to each system and does not significantly affect the results of comparison between systems. The outlet water from each condenser flows into the main pipe, and the confluent water temperature before this water enters the cooling tower (t ) is clwoutz given as DT  G + DT  G + DT  G + . . . + DT  G 2 s2 3 s3 1 s1 12 s12 t = t + (9) clwoutz clwin total t is the chiller inlet water temperature, which is considered as the same for each end use clwin under the hypothesis that heat loss is neglected. The subsequent water flow through the cooling tower and the outlet water temperature of the cooling tower is defined as t = t E  (t t ) (10) towerout clwoutz tower clwoutz wet where E is the efficiency of the cooling tower, which is set as 70% in this study. t is the wet-bulb tower wet temperature outdoors, as derived from the meteorology database. In the CCCP system, because there is no water storage, the outlet water from cooling tower flows directly to the end uses, and t is the towerout cooling water inlet temperature t for the next time interval. Subsequently, a closed-loop successive clwin simulation is designed. The COP and chiller model implemented in this simulation is a function of the chilled water temperature set point of the supply t , average cooling water temperature in the chwset condenser t , and the cooling load ratio of the chiller R . This function is curve-fitted by using the clwaver q actual operation curve of the chiller that was determined via the field test. COP , which is the ratio ratio of the operating chiller COP to its nominal COP (COP ), is expressed as follows: 1 116.647144 454.060748 COP = ( 1.645386)sin 4.070436R + 2.876142 ratio 7 t t clwaver clwaver (11) sin(0.765403R )  0.7287 t + 0.00355t 0.1574t chwout chwout chwout Then the operating COP is given as COP = COP  COP (12) ratio In this study, t is preset as 7 C, and thus remains constant. chwset Appl. Sci. 2017, 7, 1139 10 of 16 When considering the above Equations (7)–(12), t , which is calculated once per minute, towerout affects the COP in the succeeding time interval. All of the operating parameters can be continuously calculated via this process. As previously mentioned, the only control strategy is the quantity control for the pumps and cooling tower. Because no water storage system is included, all of the equipment must be operated overnight. During the daytime hours, the condenser inlet water temperature is regulated for minimal deviation from the 27 C target temperature; this is the nominal parameter that is necessary to ensure high efficiency of the chiller. 4.2. Integrated Distributed Variable-Frequency Pump and Water Storage Systems As previously mentioned, in the proposed system, the water storage tank has partitioned the water loop such that there are two sides: the transportation side and the source side, as is shown in Figure 2. On the transportation side, the variable-frequency pumps are fixed at each end use to control water flow. As has been described, these pumps initiate the pressure loss in the end-use and corresponding main pipes, which is significantly reduced to 15 mH O as the equations presented in Section 4.1. The nominal flow rate G of these pumps is determined as based on the information presented inominal in Table 1. During the simulation, the water temperature difference DT is maintained at 4.5 C, which is the nominal parameter for the chiller. Then, the required frequency of the i-th end-use pump n is ei cDt n =  50 (13) inominal However, the variable frequency range of the pump is 25–50 Hz. Thus, if the calculated frequency exceeds this interval, the pump can only operate under the conditions of maximum or minimum frequency. The pump efficiency can be calculated because the operating point is determined as the intersection of the pump curve and loop curve. Then, the flow rate for each end use is determined. The chiller model is the same as that presented in Equations (11) and (12) in Section 4.1. On the source side, six cooling tower pumps with the same nominal water flow (200 m /h) are fixed, but each of their pump heads are re-adjusted to 5 m because they only need to account for the pressure loss on the source side. Control of the cooling towers and pumps is interdependent, and their models can be described via Equation (10). The source-side water loop is relatively simple; this means that it possesses relatively few valves to maintain stable resistance characteristics and relatively high pump efficiency. In accordance with the electricity tariff, operation of the pumps and cooling towers is increased at night and is reduced during the peak cost period. As mentioned in Section 3, the water tank is stratified into five layers to preserve the distinction between water temperature levels. The volume of each layer is 400 m , which is defined as V . The total cooling water flow rate is G , which is calculated via processes occurring on the transportation side; total alternatively, the cooling tower flow rate G is determined as based on the number of operating tower towers and pumps. The relative amounts of these two water flows determine the real-time vertical flow direction inside the water tank. Specifically, if G is larger than G , then an increased amount of tower total water is pumped into the cooling tower and the water inside the tanks flows upwards. Conversely, if G is smaller than G , then the water flows downwards. Thus, the water tank models have tower total two operating modes: the larger G mode and larger G mode. For each step in the simulation total tower process, the program must compare the flow rate and decide which mode to run. The former mode is presented here as an example. Another point to be stated is that, in this study, water within one layer is assumed to be well mixed within one calculation step. In the first layer, the water temperature is determined as follows: G /60 t + V  t total clwoutz 0 l ayer1 t 0 = (14) l ayer1 G /60 + V total 0 Appl. Sci. 2017, 7, 1139 11 of 16 Appl. Sci. 2017, 7, 1139 11 of 16 The unit of and is m 3 /h. is the current temperature, and ′ is the The unit of G and G is m /h. t is the current temperature, and t 0 is the tower total l ayer1 l ayer1 temperature for the succeeding time interval following mixture; at this point, ′ becomes the temperature for the succeeding time interval following mixture; at this point, t 0 becomes the l ayer1 inlet temperature of the cooling tower. The cooling tower model is identical to that expressed via inlet temperature of the cooling tower. The cooling tower model is identical to that expressed via Equation (10); the outlet temperature is noted as . Equation (10); the outlet temperature is noted as t . towerout For the second to fourth layers, the temperature for the succeeding time interval can be For the second to fourth layers, the temperature for the succeeding time interval can be determined as determined as (G G )/60 t 0 + V  t tower total layer1 0 l ayer2 ( − )/60∗ ′+ ∗ t 0 = (15) l ayer2 (15) ′= (G G )/60 + V tower total 0 ( − )/60+ (G G )/60 t 0 + V  t tower total layer2 0 l ayer3 ( − )/60∗ ′+ ∗ t 0 = (16) l ayer3 ′= (16) (G G )/60 + V tower total 0 ( − )/60+ (G G )/60 t 0 + V  t tower total layer3 0 l ayer4 ( − )/60∗ ′+ ∗ t 0 = (17) l ayer4 (17) ′= (G G )/60 + V tower total 0 ( − )/60+ After flowing through a transition layer, the water flows into the fifth layer with outlet water from After flowing through a transition layer, the water flows into the fifth layer with outlet water the cooling tower. Thus, the temperature in the fifth layer following mixture is given as from the cooling tower. Thus, the temperature in the fifth layer following mixture is given as ((G G ))/60 t 0 + G /60 t + V  t − tower /60∗ ′+ tower /60∗ towerout + ∗ total l ayer4 0 l ayer5 t 0 = (1 (18) 8) ′= l ayer5 G //60 60 ++V t otal Then, the water is pumped to the transportation side as the inlet water of chillers in the Then, the water is pumped to the transportation side as the inlet water of chillers in the succeeding succeeding time step; this completes the one-step calculations. For an initial chiller inlet temperature time step; this completes the one-step calculations. For an initial chiller inlet temperature and a given and a given cooling load, the operating parameters can be gradually calculated. The simulation flow cooling load, the operating parameters can be gradually calculated. The simulation flow chart is shown chart is shown in Figure 7. in Figure 7. Figure 7. Simulation flow chart of the DVFP and WS system. Figure 7. Simulation flow chart of the DVFP and WS system. 5. Results 5. Results An appropriate inlet water temperature for chillers on a full-load day is illustrated in Figure 8. An appropriate inlet water temperature for chillers on a full-load day is illustrated in Figure 8. As expected, the water temperature in the CCCP system fluctuates more frequently than that in the As expected, the water temperature in the CCCP system fluctuates more frequently than that in the DVFP and WS system because there is no water storage. However, with the implementation of water DVFP and WS system because there is no water storage. However, with the implementation of water tanks, the DVFP and WS system stores cold water at night when the inlet temperature is lower and tanks, the DVFP and WS system stores cold water at night when the inlet temperature is lower and releases it during daytime hours. It is found that this low inlet temperature improves the average chiller COP Figure 9. Another advantage of the proposed system is the implementation of the DVFP, Appl. Sci. 2017, 7, 1139 12 of 16 Appl. Sci. 2017, 7, 1139 12 of 16 Appl. Sci. 2017, 7, 1139 12 of 16 releases it during daytime hours. It is found that this low inlet temperature improves the average chiller COP Figure 9. Another advantage of the proposed system is the implementation of the DVFP, which distributes water flow as required, and regulates the temperature difference ∆T to ensure high which distributes water flow as required, and regulates the temperature difference ∆T to ensure high which distributes water flow as required, and regulates the temperature difference DT to ensure high chiller efficiency. chiller efficiency. chiller efficiency. 0:00 4:00 8:00 12:00 16:00 20:00 0:00 0:00 4:00 8:00 12:00 16:00 20:00 0:00 Time Time CCCP DVFP&WS CCCP DVFP&WS Figure 8. Inlet cooling water temperature for chillers. Figure 8. Inlet cooling water temperature for chillers. Figure 8. Inlet cooling water temperature for chillers. Figure Figure 9. 9. Box Box chart chart of chi of chiller ller coef coeffici ficient ent of of pe performance rformance (COP) for the (COP) for the two two dif different ferent systems. systems. Figure 9. Box chart of chiller coefficient of performance (COP) for the two different systems. The effective total electric power of all equipment, including the chillers, pumps, and cooling The effect The effective ive total electr total electric ic power of all power of all equipm equipment, ent, iincluding ncluding tthe he chil chillers lers, , pum pumps, ps, and co and cooling oling towers, is shown in Figure 10. It can be observed that, although the new system consumes more towers, is shown in Figure 10. It can be observed that, although the new system consumes more towers, is shown in Figure 10. It can be observed that, although the new system consumes more power at night, the benefits afforded by this system during the daytime hours are more significant, power a power at t ni night, ght, the benef the benefits its a af fffor orded b ded by y thi this s syst system em durin during g the d the daytime aytime hour hours s are more are more sign significant, ificant, particularly during the peak hour at approximately 12:00, when the cooling tower and pump usage particularly during the peak hour at approximately 12:00, when the cooling tower and pump usage particularly during the peak hour at approximately 12:00, when the cooling tower and pump usage is reduced and the water tanks release cold. However, as it is limited by the size of the water tanks is is red reduced uced an and d tthe he w water ater ttanks anks re release lease c cold. old. However However ,, as as it it is is lim limit ited by ed by tthe he si size ze of of tthe he wat water er ttanks anks and capacity of water storage, the low temperature of the cold water stored in the tanks can only be and capacity of water storage, the low temperature of the cold water stored in the tanks can only be and capacity of water storage, the low temperature of the cold water stored in the tanks can only be sustained for a few hours. During the second peak hour of the day, which occurs at approximately sust sustained ained for fora a few few hour hours. s. During During tthe he se second cond p peak eak ho hour ur o of f tthe he d day ay,, which which occur occurs s at at ap appr proxi oximately mately 18:00, the comparative advantage of the proposed system is insignificant. A summary of electricity 18:00, the comparative advantage of the proposed system is insignificant. A summary of electricity 18:00, the comparative advantage of the proposed system is insignificant. A summary of electricity consumption on a full-load day is provided in Table 2, which also provides details of the field test consumpt consumption ion on a on afu full-load ll-load day day iis s provi provide ded in d in Tab Table le 2, wh 2, which ich al also so provides provides det details ails o of f tthe he fie fielld d ttest est results for comparison. results for comparison. results for comparison. Cooling water temperature (℃) Cooling water temperature (℃) Appl. Sci. 2017, 7, 1139 13 of 16 Appl. Sci. 2017, 7, 1139 13 of 16 0:00 4:00 8:00 12:00 16:00 20:00 0:00 Time CCCP DVFP&WS Figure 10. Total electric power for each system. Figure 10. Total electric power for each system. Table 2. Summary of electricity consumption on a full-load day (kWh). Table 2. Summary of electricity consumption on a full-load day (kWh). Systems Chiller PP DVFP CTP CTF Total Systems Chiller PP DVFP CTP CTF Total Field Test 20,645 3149 3335 27,129 Field Test 20,645 3149 3335 27,129 CCCP 20,151 3030 2970 26,151 CCCP 20,151 3030 2970 26,151 DVFP DVand FP aWS nd WS 19,260 19,260 949 949 342 342 2904 2904 23,455 23,455 The labels CTF and CTP in Table 2 are abbreviations for the cooling tower fans and The labels CTF and CTP in Table 2 are abbreviations for the cooling tower fans and corresponding corresponding cooling tower pumps, respectively. It is observed that the simulated energy cooling tower pumps, respectively. It is observed that the simulated energy consumption in the CCCP consumption in the CCCP system is lower than that measured via field testing, particularly for the system is lower than that measured via field testing, particularly for the pumps and cooling towers. pumps and cooling towers. This can be explained by the control strategy and the actual performance This can be explained by the control strategy and the actual performance of the equipment. During of the equipment. During operation, the pump control precision was observed to occasionally operation, the pump control precision was observed to occasionally decrease to an undesirable level; decrease to an undesirable level; moreover, the equipment was aging in some way that decreased moreover, the equipment was aging in some way that decreased efficiency, specifically affecting pump efficiency, specifically affecting pump efficiency and cooling tower efficiency. However, regarding efficiency and cooling tower efficiency. However, regarding the total energy consumption, as compared the total energy consumption, as compared to the CCCP system, the DVFP and WS system consumes to the CCCP system, the DVFP and WS system consumes 2696 kWh less electricity, equating to an 2696 kWh less electricity, equating to an approximately 10.3% in energy saved. As for transportation approximately 10.3% in energy saved. As for transportation system (including all of the pumps), the system (including all of the pumps), the DVFP and WS system consumes 1739 kWh less electricity DVFP and WS system consumes 1739 kWh less electricity than CCCP system, accounting for 57.4% than CCCP system, accounting for 57.4% of the energy in transportation system. Furthermore, as of the energy in transportation system. Furthermore, as compared to the field test results, the total compared to the field test results, the total energy saved on a full-load day is 3674 kWh, equating to energy saved on a full-load day is 3674 kWh, equating to nearly 14%. Although CTPs are added to nearly 14%. Although CTPs are added to the DVFP and WS system, the sum of DVFP and CTP the DVFP and WS system, the sum of DVFP and CTP remains as less than PP for reasons, such as remains as less than PP for reasons, such as fluctuation in frequency and water loop pressure fluctuation in frequency and water loop pressure optimization. Despite this, the transportation system optimization. Despite this, the transportation system only consumes less than 15% of the total energy, only consumes less than 15% of the total energy, thereby limiting the energy-saving potential. thereby limiting the energy-saving potential. Based on the simulation results of energy consumption, the daily electricity cost is calculated as Based on the simulation results of energy consumption, the daily electricity cost is calculated as according to the current tariff in Beijing. Calculations reveal the daily cost for the CCCP system to according to the current tariff in Beijing. Calculations reveal the daily cost for the CCCP system to be be 30,855 RMB, whereas the cost is 27,585 RMB for the DVFP and WS system. The daily cost saving 30,855 RMB, whereas the cost is 27,585 RMB for the DVFP and WS system. The daily cost saving equates to 10.6%. equates to 10.6%. In addition to the full-load-day study, energy consumption on a partial-load day is investigated In addition to the full-load-day study, energy consumption on a partial-load day is investigated to present a comprehensive view of system performance. The date is 30 May, and the simulated to present a comprehensive view of system performance. The date is 30 May, and the simulated cooling load as simulated via DeST software is 56,000 kWh, which is 80% of the maximum cooling cooling load as simulated via DeST software is 56,000 kWh, which is 80% of the maximum cooling load. The simulation described above is performed, and energy consumption and cost are calculated. load. The simulation described above is performed, and energy consumption and cost are calculated. Table 3 provides a comparison of the two days. It is found that the energy-saving potential is 13%, Table 3 provides a comparison of the two days. It is found that the energy-saving potential is 13%, which is similar to that observed on a full-load day. which is similar to that observed on a full-load day. Total electric power (kW) Appl. Sci. 2017, 7, 1139 14 of 16 Table 3. Comparison of systems on typical days with different cooling loads. Cooling Loads Systems Energy Consumption (kWh) Cost (RMB) CCCP 26,151 30,030 Full Load DVFP and WS 23,455 27,191 CCCP 21,651 25,969 80% Load DVFP and WS 18,843 23,736 6. Conclusions In this paper, the operating performance and energy efficiency of a novel DVFP and WS system that is applied to the cooling water operations in a DCS was analyzed. The basic principles and a schematic diagram of the proposed system have been presented, along with an analysis of the energy-saving potential. A DCS located in Beijing, China was selected for a case study; this included an on-site investigation of the system. Using this DCS as a reference, a series of simulations were conducted and effective operating data for two different systems exposed to various weather conditions were calculated. Through comparison with field test results and a simulated CCCP system, the proposed system demonstrates a 10% saving for both energy and cost part for the whole system. The throttling valves present in the CCCP system were replaced with variable-frequency pumps to ensure appropriate water flow regulation; additionally, in contrast to the CCCP system, water pressure loss via valves was prevented. This resulted in increased pump efficiency, the prevention of excessive water flow, and a reduction of transportation energy consumption. In addition, the water storage tanks enabled the resourceful exploitation of the electric tariff and pump control flexibility. The cold water was stored at night and was released during the period when the cost of electricity was highest. Via the proposed system, not only were the operating costs of pumps and cooling towers reduced, but also the chiller COP was increased because of the low cooling water inlet temperature of the condenser. It can be concluded that the size of the transportation system and the cooling load profile play an important role in the applicability of this new system. In a large district energy system with long pipes and various end uses, the transportation system consumes a majority of the energy; under these conditions, the advantages of the proposed system are more notable. As the concept of distributed variable-frequency pumps is currently being applied in large city-scale district heating systems, it would not be exceedingly difficult to begin implementing the proposed cooling system on an equivalent scale. Moreover, the DVFP and WS system is also applicable in systems with changing end-use cooling loads, as it can promptly initiate the changes that are necessary to maintain its level of efficiency by quickly adjusting flow as required. Thus, from what has been presented in this paper, it can be ascertained that there is significant potential of the DVFP and WS system application in many cases to save energy and reduce operating costs. However, some defects still exist in this study, in that all of the research works are based on a field test of the current system and simulation of the proposed system. There is a lack of the applications of DVFP and WS system in real operating projects and the real performance of this new system, which would be our future focus. Acknowledgments: This work was supported by the Natural Science Foundation of China (Grant No. 51521005), the 13th Five-Year National Key Technology R & D Program of China (Grant No. 2016YFC0700704). Author Contributions: Yichi Zhang and Jianjun Xia conceived and designed the experiments; Yichi Zhang and Chuanxin Chen performed the experiments; Yichi Zhang and Chuanxin Chen analyzed the data; Jianjun Xia contributed analysis tools; Yichi Zhang and Jianjun Xia wrote the paper. Conflicts of Interest: The authors declare no conflict of interest. Appl. Sci. 2017, 7, 1139 15 of 16 Nomenclature DCS district cooling system DVFP distributed variable-frequency pump WS water storage CCCP conventional central circulating pump COP coefficient of performance DT temperature difference VFP variable frequency pump twelve independent sub-buildings selected as S1–S12 testbeds G volume flow rate, m /h H pump head, mH O Q electric power, W t confluent water temperature before cooling tower clwoutz t chiller inlet water temperature clwin E efficiency of the cooling tower tower t wet-bulb temperature outdoors wet t cooling water temperature after cooling tower towerout t average cooling water temperature in the condenser clwaver R cooling load ratio of the chiller COP ratio of the operating chiller COP to its nominal COP ratio COP nominal COP t chilled water temperature set point chwset layer1–layer5 five layers inside water tank V volume of each layer h efficiency of the pump n operating frequency t temperature pp primary pump total summary of all sub-buildings ct cooling tower m main pipe si i-th pump nominal nominal condition of equipment ‘ parameter in the succeeding time interval References 1. 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Hydraulic Regime Analysis of On-Off Valve Regulation. Appl. Mech. Mater. 2014, 522–524, 1009–1014. [CrossRef] © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Sciences Multidisciplinary Digital Publishing Institute

Energy Performance Analysis of an Integrated Distributed Variable-Frequency Pump and Water Storage System for District Cooling Systems

Applied Sciences , Volume 7 (11) – Nov 6, 2017

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applied sciences Article Energy Performance Analysis of an Integrated Distributed Variable-Frequency Pump and Water Storage System for District Cooling Systems Yichi Zhang, Chuanxin Chen and Jianjun Xia * Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China; zhangyic16@mails.tsinghua.edu.cn (Y.Z.); cindychen528@126.com (C.C.) * Correspondence: xiajianjun@tsinghua.edu.cn; Tel.: +86-010-6277-5553 Received: 30 September 2017; Accepted: 3 November 2017; Published: 6 November 2017 Abstract: In a district cooling system (DCS), the distribution system (i.e., cooling water system or chilled water system) will continue to be a critical consideration because it substantially contributes to the total energy consumption. Thus, in this paper, a new distributed variable-frequency pump (DVFP) system with water storage (WS) for cooling water is adapted to a DCS with large end-use cooling load fluctuations. The basic principle and energy saving potential of the new system is analyzed. A case study of a DCS with a conventional central circulating pump (CCCP) system is presented to compare the energy consumption and the operating performance of CCCP and DVFP systems that are exposed to various weather conditions. The methods to perform this case study include, cooling load simulation and the modeling of two water distribution networks and systems via several commercial software packages. By replacing the throttling valves with a DVFP, the pump efficiency is increased and transportation energy consumption is reduced. Additionally, by introducing water tank storage, the cooling water is cooled at night and is released at a peak hour during the daytime, thereby further reducing the energy cost. As compared to the field test results of the CCCP system, the daily electrical energy saved by the DVFP and WS system is approximately 57% for a cooling water pump system on the hottest day in summer. This value also corresponds to approximately 10% of the energy saved for the entire system. Furthermore, additional energy could be saved under partial loading conditions. Keywords: district cooling; distributed variable-frequency pumps; water storage; cooling water; energy saving 1. Introduction District cooling systems (DCSs), which generate cold water in a central plant that is distributed to end uses to fulfill its cooling demands, have become a widely used solution for large-area buildings in many countries [1,2]. Generally, there are two types of DCSs that differ according to the type of water that is produced at the central plant; the two types are as follows: (1) a centralized chilled water system; and, (2) a centralized cooling water system. In the first type, the central chiller is designed to have large cooling capacity to promote a high coefficient of performance (COP); additionally, the removal of terminal chillers makes it possible to more efficiently utilize the building space [3]. It also provides an ideal platform for interrelated thermal technologies implementing tri-generation [2] or thermal storage [4]. The second system, also referred to as the water-loop heat pump system, produces cooling water via a cooling tower or natural sources, such as seawater and transports it to end-use chillers [5]. This system is designed to utilize the distributed chillers to achieve variable cooling loads in end uses. Another advantage of this system is that it can incorporate vast varieties of cooling sources and recover Appl. Sci. 2017, 7, 1139; doi:10.3390/app7111139 www.mdpi.com/journal/applsci Appl. Sci. 2017, 7, 1139 2 of 16 the rejected heat inside of a building [6–8]. Because systems with variable cooling loads are the focus of this study, the second system with centralized cooling water was selected for further research. However, it should be noted that DCSs do possess limitations. For instance, the water transportation system consumes a large amount of energy, as an America-based study showed that the pumping system in a typical DCS consumed 30% of the total energy of the system [9]. The reason for this can be explained by the design and control strategy of conventional central circulation pump (CCCP) systems. The central circulating pumps are designed for the most remote consumer; thus, the flow rate and pump head are quite excessive for the other consumers. Therefore, the remaining consumers must employ valves to control water flow, which responds slow and causes additional losses in local pressure. The use of throttling valves alters the resistance characteristics of the network, resulting in the low efficiency of pump operation. In addition, the precision of water flow control is reduced when the end-use cooling demand varies according to each consumer, which leads to an imbalance in cold supply. Under the assumption that a large flow of water would offset the cold supply imbalance, most of the pumps currently in use generate large flows, which again increases transport energy consumption [10]. However, these problems can be solved by employing distributed variable-frequency pumps (DVFPs). When the cooling load varies, the chiller adjusts the heat that is released to condensing water side and the DVFP adjusts the pump speed to control the cooling water flow, maintain the supply, and return water temperature difference (DT) at a preset value. Each DVFP is designed to provide the pressure drop in corresponding end-use building and main pipes. Thus, the main circulating pumps, which are also referred to as primary pumps (PPs), are removed and the transportation energy is reduced. By replacing the valves with pumps, the pump head is reduced and the resistance characteristics of the main pipes become relatively stable, thereby increasing pump efficiency. Additionally, variable-frequency pumps are able to rapidly and precisely adjust water flow, while maintaining a level of high-efficiency operation, preventing extra flow, and satisfying the specific cooling demand of each end-user. Variable frequency pumps (VFPs) have been studied for many years and are implemented in a wide variety of applications in fields related to air-conditioning, district heating, and municipal water distribution. Some studies have focused on control strategies for VFPs. Ma and Wang optimized pump speed and sequence control in a complex air-conditioning system to save energy [11]. Wang and Burnett developed a control strategy that implements an adaptive and derivative strategy to optimize the speed of pumps by resetting the pressure set point [12]. Marchi studied the components in pumping systems to provide insight into the assessment of VFPS efficiency and energy consumption [13]. Pan studied the performance of several check valves that were connected to DVFPs and the influence of these valves on energy consumption [14]. Some studies also focused on the performance of DVFPs in actual projects and calculated the energy-saving and cost-saving potential; this includes the hydraulic performance of a district heating project in Kuerle, China [15], the minimum of capital cost and energy consumption in a district heating projects in Dalian, China [16], and a project involving a municipal water distribution system [17]. Gamberi et al. simulated a multi-zone heating system and developed the Newton-Raphson method to solve various hydraulic problems [18]. Sheng analyzed the factors affecting energy saving rate in the DVFPs system [19]. Although these studies yielded significant contributions to the field, most current studies are focused on chilled water pumps and fail to adequately investigate cooling water pumps, the influence of cooling water temperature on the entire system, and, more significantly, the chiller performance. Furthermore, there is a lack of studies on timely effective system performance in response to cooling loads that fluctuate in real time. Alternatively, thermal storage systems including water storage, ice storage, and eutectic salt storage systems have also been widely used in DCSs. Under the conditions of time-of-use tariff of electricity, thermal storage systems produce and store hot/cold water overnight at relatively cheaper electricity costs and release the stored contents at the peak price time. As a result, the system has been proven as cost-saving and peak shaving, which is beneficial for electric power plants [20,21]. Furthermore, the Appl. Sci. 2017, 7, 1139 3 of 16 nominal cooling capacity can be reduced. As an example, many studies focusing on cold storage have aimed to optimize the control and performance. Kawashima et al. presented an optimal control strategy based on artificial neural networks to predict cooling loads [22]. Chan et al. conducted simulations to evaluate the performance of a combined DCS and ice storage system, and studied the influence of tariff structures on the combined system [23]. Hasnain reviewed the research on thermal storage and compared three cold storage media and rated ice storage [24]. In contrast to the numerous studies on other types of storage systems, there is a lack of studies and applications on cooling water storage. Water temperature from cooling towers is low, due to the low environmental wet bulb temperature at night, plus the valley electrical price it is cost-efficient to use cooling towers to generate cooling water and store it overnight. Furthermore, cooling water with lower temperature supplied during daytime hours would increase the COP of the chiller, thereby further decreasing the electricity consumption. Additionally, with the assistance of water tanks, there is no need to keep pumps and cooling towers in constant operation; this provides a greater flexibility for the controlling system. Therefore, by exploiting the advantages of each of the related components, a novel DVFP system with water storage (DVFP and WS) designed for implementation in a DCS with variable end-user-required cooling loads has been developed and is proposed in this paper. In this new system, chillers and variable-frequency pumps are installed at each end-use building and independently controlled while sharing a single cooling water loop. Cooling water is generated at a central cooling tower and is stored in a water tank that is located near the cooling tower. Then, the cold water in the water tank is transported to the end users. In this study, only the cooling water loop is discussed because the chilled water loop is distributed at each end use and operates independently. This paper first presents a schematic of the new system and introduces the principles of its design. Subsequently, a DCS with CCCPs in Beijing, China was selected for a case study. The system performance and energy consumption of CCCP and DVFP and WS systems are accordingly compared based on the results of the DCS case study. This procedure includes a field test of the current CCCP system to obtain operating data, a cooling load simulation by implementing DeST software (Designer ’s Simulation Toolkit) under various weather conditions, modeling of the water networks and equipment, and a calculation of the operating parameters. The simulated building load and energy consumptions of the current system are found to be in agreement with the field test results, and, as compared to the current system, the DVFP and water storage (WS) system has been proven to have energy-saving potential. 2. Design Schematic and Principles A descriptive schematic diagram of the current CCCP system is shown in Figure 1. S1–S12 illustrate the terminal end users with chillers; the primary pumps are responsible for circulating the whole cooling water loop, whereas cooling towers are designed to coordinate with them. The power of primary pumps Q in units W is given as: p p 2.72G H total p p Q = (1) p p where H is the pump head (unit: mH O), G is the total flow rate (unit: m /h), and h is the p p 2 1 total efficiency of the pump. The pump head, which is the total pressure drop of the entire water loop, is simply described as H = H + H + H (2) p p ct sn m where H is cooling tower pressure loss. H is the pressure loss in most unfavorable end use. H is ct sn m the loss in main pipes. All of the units are in mH O. The losses in auxiliary equipment, such as check valves are also considered in corresponding components. For a CCCP system, because quantity control is only implemented on the primary pumps and cooling tower, the power of cooling towers is the product of the number of operating towers and nominal power. For water pumps, the relationship between the pump head and water flow rate can be written as a polynomial below: Appl. Sci. 2017, 7, 1139 4 of 16 H = a + a G + a G (3) p p 0 1 p p 2 p p Appl. Sci. 2017, 7, 1139 4 of 16 where a , a , and a are obtained through pump operation curve-fitting data. Additionally, the 0 1 2 relationship where between , , and pr essur are obtai e lossn and ed through p flow rateuin mp opera water loops tion curve- can be fitting da written ta. asAdditionally, the relationship between pressure loss and flow rate in water loops can be written as H = H + bG (4) total (4) H= + where H is the static pressure loss and b is calculated from the resistance characteristics of the pipes where is the static pressure loss and is calculated from the resistance characteristics of the and auxiliary equipment. The pumps operate at the intersection of the pump curve (3) and loops pipes and auxiliary equipment. The pumps operate at the intersection of the pump curve (3) and curve (4). loops curve (4). End-use water flow is controlled by throttling valves fixed at each branch. During operation, the End-use water flow is controlled by throttling valves fixed at each branch. During operation, the pumps operate at a constant speed and valve operation is variable; this alters the parameter in pumps operate at a constant speed and valve operation is variable; this alters the parameter b in Equation Equation (4), as well as the loops resistance curve, thereby changing the operating point of the pumps (4), as well as the loops resistance curve, thereby changing the operating point of the pumps and decreasing and decreasing pump efficiency as a result. Furthermore, water flow cannot be controlled by valves pump efficiency as a result. Furthermore, water flow cannot be controlled by valves as precisely as is as precisely as is required by the end user; thus, imbalance of the cold supply between the nearest required by the end user; thus, imbalance of the cold supply between the nearest building and building building and building frequently occurs. The actual water flow distributed at each end use is not frequently occurs. The actual water flow distributed at each end use is not related to the cooling load; related to the cooling load; thus, the ∆T and the subsequent COP of the chiller is affected. A common thus, the DT and the subsequent COP of the chiller is affected. A common way to offset this DT imbalance way to offset this ∆T imbalance is to increase the circulating water flow, which would also increase is to increase the circulating water flow, which would also increase energy consumption. energy consumption. Figure 1. Schematic diagram of the current conventional central circulating pump (CCCP) system. Figure 1. Schematic diagram of the current conventional central circulating pump (CCCP) system. However, the DVFP and WS system shown in Figure 2 has made many improvements. The However, the DVFP and WS system shown in Figure 2 has made many improvements. The water water tank has partitioned the cooling water into two different sides: the source side and tank has partitioned the cooling water into two different sides: the source side and transportation side. transportation side. On the transportation side, DVFPs fixed at each terminal are designed to initiate On the transportation side, DVFPs fixed at each terminal are designed to initiate the pressure drop the pressure drop in the end-use water loop and corresponding main pipes. It is capable of varying in the end-use water loop and corresponding main pipes. It is capable of varying the pump speed to the pump speed to control water flow. The flow rate of the i-th pump in pump curve (3) is control water flow. The flow rate of the i-th pump G in pump curve (3) is si = (5) G = G (5) si nominal where n is the operating frequency, which can be a 50ltered and is the nominal flow rate of the pump, which is designed according to the maximum cooling load. is the sum of . where n is the operating frequency, which can be altered and G is the nominal flow rate of the nominal The resistance curve at the end use remains stable as the speed of the pumps changes, assuring pump, which is designed according to the maximum cooling load. G is the sum of G . si pump efficiency. Note that the PPs are removed for this observation, the tota total l power of DVFPs can The resistance curve at the end use remains stable as the speed of the pumps changes, assuring be calculated as pump efficiency. Note that the PPs are removed for this observation, the total power of DVFPs can be calculated as Q=2.72 (6) si Q = 2.72G (6) å si si where is the pump head of the i-th pump. Thus, the transportation energy-saving potential is i=1 feasible because the following occurs: Appl. Sci. 2017, 7, 1139 5 of 16 Appl. Sci. 2017, 7, 1139 5 of 16 where H is the pump head of the i-th pump. Thus, the transportation energy-saving potential is si feasible because the following occurs: • Water flow is controlled as required so there is no extra water flow. • The pump operating point remains stable to ensure pump efficiency. Water flow is controlled as required so there is no extra water flow. • The removal of valves prevents extra pressure loss. The pump operating point remains stable to ensure pump efficiency. • The PPs are removed, and not all of the water flow needs to overcome main pipe resistance. The removal of valves prevents extra pressure loss. The PPs are removed, and not all of the water flow needs to overcome main pipe resistance. On the source side, the cooling towers and cooling tower pumps are quantity controlled to change the flow rate as required. In this case, the cooling tower pumps only provide the pressure loss On the source side, the cooling towers and cooling tower pumps are quantity controlled to change on the source side; this drop is quite small. Additionally, the storage tank affords increased pump the flow rate as required. In this case, the cooling tower pumps only provide the pressure loss on the flexibility and cooling tower control flexibility. As based on the time-of-use electricity tariff, the source side; this drop is quite small. Additionally, the storage tank affords increased pump flexibility cooling source would generate an increased amount of cold water and store it in the water tank and cooling tower control flexibility. As based on the time-of-use electricity tariff, the cooling source during the time of minimum electricity cost, and subsequently reduce the usage during the peak cost would generate an increased amount of cold water and store it in the water tank during the time of time. In order to make full use of the water tank, it is stratified into several horizontal layers [25]. minimum electricity cost, and subsequently reduce the usage during the peak cost time. In order to Small holes exist throughout the partition to allow water to freely flow between layers. This study make full use of the water tank, it is stratified into several horizontal layers [25]. Small holes exist takes a five-layer water tank as an example. The relatively hot water returning from each chiller throughout the partition to allow water to freely flow between layers. This study takes a five-layer condenser flows into the top layer, where it is extracted and pumped into the cooling tower. The water tank as an example. The relatively hot water returning from each chiller condenser flows into the outlet water from the cooling tower flows into the bottom layer and is then pumped to the top layer, where it is extracted and pumped into the cooling tower. The outlet water from the cooling transportation side. Middle layers 2–4 are storage and transition layers between the relatively hot tower flows into the bottom layer and is then pumped to the transportation side. Middle layers 2–4 are upper layer and cold bottom layer. This design minimizes the intermixing of the water, which is storage and transition layers between the relatively hot upper layer and cold bottom layer. This design partitioned according to temperature level, to ensure that the water transported into the end use is minimizes the intermixing of the water, which is partitioned according to temperature level, to ensure always the coldest. It is considered as energy-saving because colder water decreases the condensing that the water transported into the end use is always the coldest. It is considered as energy-saving temperature and increases the COP of the chiller. because colder water decreases the condensing temperature and increases the COP of the chiller. Although the energy-saving potential of current related systems has been briefly discussed, the Although the energy-saving potential of current related systems has been briefly discussed, the new system proposed in this paper includes additional components, such as cooling tower pumps; new system proposed in this paper includes additional components, such as cooling tower pumps; thus, the total energy consumption and actual benefits of this system need to be studied in detail; thus, the total energy consumption and actual benefits of this system need to be studied in detail; and, and, these results are discussed below. these results are discussed below. Figure 2. Schematic diagram of distributed variable-frequency pump (DVFP) and water storage Figure 2. Schematic diagram of distributed variable-frequency pump (DVFP) and water storage (WS) (WS) system. system. 3. Project Case Study and Cooling Load Profile 3. Project Case Study and Cooling Load Profile A district cooling project employing CCCPs located in Northeast Beijing, China is selected as a case A district cooling project employing CCCPs located in Northeast Beijing, China is selected as a study. Field tests were performed to obtain basic information and system operating data, including energy case study. Field tests were performed to obtain basic information and system operating data, consumption, water flow rate, and temperature. Based on these data, several models were developed to including energy consumption, water flow rate, and temperature. Based on these data, several simulate cooling loads and system operation; the results have been compared to the test data. models were developed to simulate cooling loads and system operation; the results have been compared to the test data. The entire project is a commercial district comprising twelve independent sub-buildings noted as S1–S12, neighboring the central cooling plant. The location of the sub-buildings, in addition to a Appl. Sci. 2017, 7, 1139 6 of 16 Appl. Sci. 2017, 7, 1139 6 of 16 The entire project is a commercial district comprising twelve independent sub-buildings noted as topol S1–S12, ogical nei diagra ghboring m of the the cool central ing wa cooling ter networks, is plant. The shown i location n Figure 3. The of the subto -buildings, tal floor area in is 78,000 additionm to. a Most topological of these buil diagram dings of are the commercia cooling water l build networks, ings, includ is ing shown a cin in ema, re Figurst e a 3u . ran The ts, and total floor retail ar stea ores. is 78,000 The time m of o . Most peration of the of e se buildings ach of the ar se b e commer uildings, cial which is buildings, shown including in Figua re cinema, 4, is dependent on thei restaurants, andr r function etail stor . For es. The example time of , bui operation ldings S2, S of each 9, and S of these 10 oper buildings, ate 24 h a d which ay,is whereas the other build shown in Figure 4, is dependent ings only on operate their dur function. ing daytime For example, hours; further buildings more, the S2, S9, op and ening S10 time o operate f each buildin 24 h a dayg , is wher diffe eas rent. These the other characteristics significantly influence the load profile. Additionally, there are chillers fixed at each buildings only operate during daytime hours; furthermore, the opening time of each building is dif end-u ferent. se bu These ilding t characteristics o generate chil significantly led water; on- influence site inve the stigat load ion reve profile. ale Additionally d that these chil , ther ler e ar s are e chillers of the same model (nominal cooling capacity = 700 kW and COP = 3.5). fixed at each end-use building to generate chilled water; on-site investigation revealed that these chillers The t areool u of the sed same in th model is stud (nominal y to simu cooling late cooling capacity loads = i 700 s a commerci kW and COP al soft = 3.5). ware package named DeST, which has been proven to be useful in performing building load simulations [26]. Besides, there The tool used in this study to simulate cooling loads is a commercial software package named are many other simulation tools on the market and each tool has its own advantages. Many studies DeST, which has been proven to be useful in performing building load simulations [26]. Besides, there have focused on the use of efficient tool to perform effective energy profile simulation of buildings are many other simulation tools on the market and each tool has its own advantages. Many studies have [27,28]. The meteorological parameters are embedded in the software and 15 July is the full-load day focused on the use of efficient tool to perform effective energy profile simulation of buildings [27,28]. (i.e., design day) in this study. All of the model settings, including building structure, materials, The meteorological parameters are embedded in the software and 15 July is the full-load day (i.e., equipment, and lighting power density, are based on architectural drawings and the investigation of design day) in this study. All of the model settings, including building structure, materials, equipment, actual operation. This enabled simulation of the hourly cooling load of each sub-building on the and lighting power density, are based on architectural drawings and the investigation of actual design day. The hourly superposition of all of the building loads and a comparison with field test operation. This enabled simulation of the hourly cooling load of each sub-building on the design results are shown in Figure 5. The accumulated cooling load on the full-load day derived by day. The hourly superposition of all of the building loads and a comparison with field test results simulation is 69,900 kWh, while the field test result is 68,100 kWh. It can be concluded that the are shown in Figure 5. The accumulated cooling load on the full-load day derived by simulation is simulation results are in agreement with the field test results. Thus, the modeling and simulation 69,900 kWh, while the field test result is 68,100 kWh. It can be concluded that the simulation results are process are confirmed to be reasonable and can be implemented to calculate cooling loads under in agreement with the field test results. Thus, the modeling and simulation process are confirmed to be various conditions. The basic information for each of the sub-buildings is presented in Table 1, which reasonable and can be implemented to calculate cooling loads under various conditions. The basic also includes the peak cooling load and estimated cooling water flow, calculated at the ΔT = 4.5 °C information for each of the sub-buildings is presented in Table 1, which also includes the peak cooling and COP = 3.5; these results are presented in the next chapter. The maximum cooling load for all load and estimated cooling water flow, calculated at the DT = 4.5 C and COP = 3.5; these results are 2 2 buildings is 5500 kW, 70.5 W/m . presented in the next chapter. The maximum cooling load for all buildings is 5500 kW, 70.5 W/m . Figure 3. Locations of sub-buildings and water networks. Figure 3. Locations of sub-buildings and water networks. Appl. Sci. 2017, 7, 1139 7 of 16 Appl. Sci. 2017, 7, 1139 7 of 16 Appl. Sci. 2017, 7, 1139 7 of 16 Figure Figure 4. 4. Operating Operating schedule schedulessof ofS1–S12. S1–S12. Figure 4. Operating schedules of S1–S12. Figure 5. Comparison between simulation and field test results for the entire district cooling project. Figure 5. Comparison between simulation and field test results for the entire district cooling project. Figure 5. Comparison between simulation and field test results for the entire district cooling project. Table 1. Basic information of sub-buildings. Table 1. Basic information of sub-buildings. Table 1. Basic information of sub-buildings. Sub- Estimated Cooling Estimated Cooling 2 2 Floor Area/m Function Cooling Load/kW Sub-Buildings Sub- Floor Area/m Function Cooling Load/kW Estimated Cooling 2 Water Flow m /h Buildings Water Flow m /h Floor Area/m Function Cooling Load/kW Buildings Water Flow m /h S1 4287.3 Retail 337.6 74.4 S1 4287.3 Retail 337.6 74.4 S1 4287.3 Retail 337.6 74.4 S2 8033.4 24 h book store 665.6 146.7 S2 8033.4 24 h book store 665.6 146.7 S2 8033.4 24 h book store 665.6 146.7 S3 2696.8 Restaurants 246.8 54.4 S3 2696.8 Restaurants 246.8 54.4 S4 7776.2 Retail, restaurant 595.2 131.2 S3 2696.8 Restaurants 246.8 54.4 S4 7776.2 Retail, restaurant 595.2 131.2 S5 2872.8 Retail, restaurant 213.5 47.0 S4 7776.2 Retail, restaurant 595.2 131.2 S5 2872.8 Retail, restaurant 213.5 47.0 S6 8033.3 Retail, restaurant 665.7 146.7 S5 2872.8 Retail, restaurant 213.5 47.0 S6 80 S7 33.35745.3 Retail, rest Exhibitionaurant 665. 433.97 14 95.66.7 S6 8033.3 Retail, restaurant 665.7 146.7 S8 2872.8 Retail, restaurant 213.5 47.0 S7 5745.3 Exhibition 433.9 95.6 S7 57 S9 45.3 9298.9 Exhib Retail,itionr estaurant 433.9 612.1 95 134.9.6 S8 2872.8 Retail, restaurant 213.5 47.0 S10 4870.1 Retail, cafe (24 h) 486.6 107.2 S8 2872.8 Retail, restaurant 213.5 47.0 S9 9298.9 Retail, restaurant 612.1 134.9 S11 10,791.0 Retail, cinema 756.6 166.8 S9 9298.9 Retail, restaurant 612.1 134.9 S10 4870.1 Retail, cafe (24 h) 486.6 107.2 S12 10,791.0 Retail, cinema 756.6 166.8 S10 4870.1 Retail, cafe (24 h) 486.6 107.2 S11 10,791.0 Retail, cinema 756.6 166.8 S11 10,791.0 Retail, cinema 756.6 166.8 S12 10,791.0 Retail, cinema 756.6 166.8 S12 10,791.0 Retail, cinema 756.6 166.8 Appl. Sci. 2017, 7, 1139 8 of 16 4. Methods Appl. Sci. 2017, 7, 1139 8 of 16 The new system presented in this paper comprises two critical components: the DVFP component and the WS component. Two systems, the CCCP and the DVFP and WS, are evaluated, 4. Methods and their system performance is compared. Water distribution network models and equipment The new system presented in this paper comprises two critical components: the DVFP component models are developed for each system to obtain hydraulic performance data, as well as thermal and the WS component. Two systems, the CCCP and the DVFP and WS, are evaluated, and their system performance, respectively. The simulation flow of each system is designed via MATLAB software performance is compared. Water distribution network models and equipment models are developed and links the aforementioned models. Based on the cooling load results that are calculated in Section for each system to obtain hydraulic performance data, as well as thermal performance, respectively. 3, the operating parameters of the system, such as temperature and water flow rate, can be calculated The simulation flow of each system is designed via MATLAB software and links the aforementioned hourly. Subsequently, the electricity consumption and operation cost can be easily acquired for models. Based on the cooling load results that are calculated in Section 3, the operating parameters comparison. This chapter provides the details of the system-specific simulation methods, models, of the system, such as temperature and water flow rate, can be calculated hourly. Subsequently, and process; the results are presented in the next chapter. the electricity consumption and operation cost can be easily acquired for comparison. This chapter provides the details of the system-specific simulation methods, models, and process; the results are 4.1. CCCP System presented in the next chapter. In the current operating system, a branched network is used for cooling water distribution. In this occasion, there is a unidirectional flow from the cooling plant to the end use. The topological 4.1. CCCP System diagram with marked pipe length, as is shown in Figure 3, is developed for water distribution In the current operating system, a branched network is used for cooling water distribution. In this network models via HACNET software (a hydraulic simulation software developed by Tsinghua occasion, there is a unidirectional flow from the cooling plant to the end use. The topological diagram University). It should be noted that the marked pipe length includes the main pipe length and the with marked pipe length, as is shown in Figure 3, is developed for water distribution network models branched pipe length inside the building. This software is proven useful in calculating the hydraulic via HACNET software (a hydraulic simulation software developed by Tsinghua University). It should performance of a given water network system [29]. Pipe resistance, as well as the pressure loss in end be noted that the marked pipe length includes the main pipe length and the branched pipe length uses, is derived from field test results. Generally, during the full-load hour (i.e., 15:00), the total inside the building. This software is proven useful in calculating the hydraulic performance of a given cooling water flow rate required for all of the condensers is approximately 1200 m /h; at this time, the water network system [29]. Pipe resistance, as well as the pressure loss in end uses, is derived from flow rate is found to be dependent on the water temperature difference (∆T) and COP. Under this field test results. Generally, during the full-load hour (i.e., 15:00), the total cooling water flow rate condition, the frictional pressure losses in the main pipes, end-use loops, and cooling tower are 10, 10, required for all of the condensers is approximately 1200 m /h; at this time, the flow rate is found to and 5 m, respectively. The losses in the first two components include the losses in pipes and valves be dependent on the water temperature difference (DT) and COP. Under this condition, the frictional and other equipment. Consequently, six primary pumps (nominal parameters: 200 m /h, 25 m pump pressure losses in the main pipes, end-use loops, and cooling tower are 10, 10, and 5 m, respectively. head) must be running to satisfy cooling water requirements. The characteristics of these pipes and The losses in the first two components include the losses in pipes and valves and other equipment. equipment, including the pump curve, are input into the model and water flow distribution for each Consequently, six primary pumps (nominal parameters: 200 m /h, 25 m pump head) must be running end use can be calculated hourly. The distributed water flow during the full-load hour (15:00), as to satisfy cooling water requirements. The characteristics of these pipes and equipment, including the compared to the estimated requirement according to the cooling load given in Table 1, is illustrated pump curve, are input into the model and water flow distribution for each end use can be calculated in Figure 6 as an example. hourly. The distributed water flow during the full-load hour (15:00), as compared to the estimated requirement according to the cooling load given in Table 1, is illustrated in Figure 6 as an example. Figure 6. Water flow rate in each end use at 15:00. Figure 6. Water flow rate in each end use at 15:00. In most sub-buildings, the simulated flow rate (Figure 6) is significantly different from the In most sub-buildings, the simulated flow rate (Figure 6) is significantly different from the estimated requirement because of the differences in pipe length and the succeeding resistance. estimated requirement because of the differences in pipe length and the succeeding resistance. The The nearest end use receives the largest water flow, while the most unfavorable end-use receives Appl. Sci. 2017, 7, 1139 9 of 16 the least flow. In sub-building S8, the water flow difference between requirement and simulation 3 3 results can be as much as 96 m /h, while in building S1 and S6 the difference is only 3 m /h. This leads to an imbalance in cold supplies and DT values. Regarding the pumps, the operating point and efficiency was calculated via HACNET software, as based on water flow and pressure loss results. A schematic diagram of the CCCP system has been presented in Figure 1. It should be noted that, although the cooling load is only simulated once per hour, the minimum calculation time interval is set as one minute in consideration of the precision requirement of the control system and water tank simulation. For any minute in the day, the cooling load for each end use is calculated via ways talked above in Section 3, and noted as Q , Q . . . Q ; then, heat rejection in the i-th condenser Q is e1 e2 e12 ci ei Q = (COP + 1) (7) ci i COP Based on the water flow rate for each end-use G that was calculated via HACNET software, the si cooling water temperature difference in the i-th condenser DT can be determined as follows: ci DT = (8) c G si where c is the heat capacity of the water. Because of the piping insulation and minimal temperature difference between the cooling water and environment, the thermal loss during transportation is neglected in this study. However, this hypothesis is applied to each system and does not significantly affect the results of comparison between systems. The outlet water from each condenser flows into the main pipe, and the confluent water temperature before this water enters the cooling tower (t ) is clwoutz given as DT  G + DT  G + DT  G + . . . + DT  G 2 s2 3 s3 1 s1 12 s12 t = t + (9) clwoutz clwin total t is the chiller inlet water temperature, which is considered as the same for each end use clwin under the hypothesis that heat loss is neglected. The subsequent water flow through the cooling tower and the outlet water temperature of the cooling tower is defined as t = t E  (t t ) (10) towerout clwoutz tower clwoutz wet where E is the efficiency of the cooling tower, which is set as 70% in this study. t is the wet-bulb tower wet temperature outdoors, as derived from the meteorology database. In the CCCP system, because there is no water storage, the outlet water from cooling tower flows directly to the end uses, and t is the towerout cooling water inlet temperature t for the next time interval. Subsequently, a closed-loop successive clwin simulation is designed. The COP and chiller model implemented in this simulation is a function of the chilled water temperature set point of the supply t , average cooling water temperature in the chwset condenser t , and the cooling load ratio of the chiller R . This function is curve-fitted by using the clwaver q actual operation curve of the chiller that was determined via the field test. COP , which is the ratio ratio of the operating chiller COP to its nominal COP (COP ), is expressed as follows: 1 116.647144 454.060748 COP = ( 1.645386)sin 4.070436R + 2.876142 ratio 7 t t clwaver clwaver (11) sin(0.765403R )  0.7287 t + 0.00355t 0.1574t chwout chwout chwout Then the operating COP is given as COP = COP  COP (12) ratio In this study, t is preset as 7 C, and thus remains constant. chwset Appl. Sci. 2017, 7, 1139 10 of 16 When considering the above Equations (7)–(12), t , which is calculated once per minute, towerout affects the COP in the succeeding time interval. All of the operating parameters can be continuously calculated via this process. As previously mentioned, the only control strategy is the quantity control for the pumps and cooling tower. Because no water storage system is included, all of the equipment must be operated overnight. During the daytime hours, the condenser inlet water temperature is regulated for minimal deviation from the 27 C target temperature; this is the nominal parameter that is necessary to ensure high efficiency of the chiller. 4.2. Integrated Distributed Variable-Frequency Pump and Water Storage Systems As previously mentioned, in the proposed system, the water storage tank has partitioned the water loop such that there are two sides: the transportation side and the source side, as is shown in Figure 2. On the transportation side, the variable-frequency pumps are fixed at each end use to control water flow. As has been described, these pumps initiate the pressure loss in the end-use and corresponding main pipes, which is significantly reduced to 15 mH O as the equations presented in Section 4.1. The nominal flow rate G of these pumps is determined as based on the information presented inominal in Table 1. During the simulation, the water temperature difference DT is maintained at 4.5 C, which is the nominal parameter for the chiller. Then, the required frequency of the i-th end-use pump n is ei cDt n =  50 (13) inominal However, the variable frequency range of the pump is 25–50 Hz. Thus, if the calculated frequency exceeds this interval, the pump can only operate under the conditions of maximum or minimum frequency. The pump efficiency can be calculated because the operating point is determined as the intersection of the pump curve and loop curve. Then, the flow rate for each end use is determined. The chiller model is the same as that presented in Equations (11) and (12) in Section 4.1. On the source side, six cooling tower pumps with the same nominal water flow (200 m /h) are fixed, but each of their pump heads are re-adjusted to 5 m because they only need to account for the pressure loss on the source side. Control of the cooling towers and pumps is interdependent, and their models can be described via Equation (10). The source-side water loop is relatively simple; this means that it possesses relatively few valves to maintain stable resistance characteristics and relatively high pump efficiency. In accordance with the electricity tariff, operation of the pumps and cooling towers is increased at night and is reduced during the peak cost period. As mentioned in Section 3, the water tank is stratified into five layers to preserve the distinction between water temperature levels. The volume of each layer is 400 m , which is defined as V . The total cooling water flow rate is G , which is calculated via processes occurring on the transportation side; total alternatively, the cooling tower flow rate G is determined as based on the number of operating tower towers and pumps. The relative amounts of these two water flows determine the real-time vertical flow direction inside the water tank. Specifically, if G is larger than G , then an increased amount of tower total water is pumped into the cooling tower and the water inside the tanks flows upwards. Conversely, if G is smaller than G , then the water flows downwards. Thus, the water tank models have tower total two operating modes: the larger G mode and larger G mode. For each step in the simulation total tower process, the program must compare the flow rate and decide which mode to run. The former mode is presented here as an example. Another point to be stated is that, in this study, water within one layer is assumed to be well mixed within one calculation step. In the first layer, the water temperature is determined as follows: G /60 t + V  t total clwoutz 0 l ayer1 t 0 = (14) l ayer1 G /60 + V total 0 Appl. Sci. 2017, 7, 1139 11 of 16 Appl. Sci. 2017, 7, 1139 11 of 16 The unit of and is m 3 /h. is the current temperature, and ′ is the The unit of G and G is m /h. t is the current temperature, and t 0 is the tower total l ayer1 l ayer1 temperature for the succeeding time interval following mixture; at this point, ′ becomes the temperature for the succeeding time interval following mixture; at this point, t 0 becomes the l ayer1 inlet temperature of the cooling tower. The cooling tower model is identical to that expressed via inlet temperature of the cooling tower. The cooling tower model is identical to that expressed via Equation (10); the outlet temperature is noted as . Equation (10); the outlet temperature is noted as t . towerout For the second to fourth layers, the temperature for the succeeding time interval can be For the second to fourth layers, the temperature for the succeeding time interval can be determined as determined as (G G )/60 t 0 + V  t tower total layer1 0 l ayer2 ( − )/60∗ ′+ ∗ t 0 = (15) l ayer2 (15) ′= (G G )/60 + V tower total 0 ( − )/60+ (G G )/60 t 0 + V  t tower total layer2 0 l ayer3 ( − )/60∗ ′+ ∗ t 0 = (16) l ayer3 ′= (16) (G G )/60 + V tower total 0 ( − )/60+ (G G )/60 t 0 + V  t tower total layer3 0 l ayer4 ( − )/60∗ ′+ ∗ t 0 = (17) l ayer4 (17) ′= (G G )/60 + V tower total 0 ( − )/60+ After flowing through a transition layer, the water flows into the fifth layer with outlet water from After flowing through a transition layer, the water flows into the fifth layer with outlet water the cooling tower. Thus, the temperature in the fifth layer following mixture is given as from the cooling tower. Thus, the temperature in the fifth layer following mixture is given as ((G G ))/60 t 0 + G /60 t + V  t − tower /60∗ ′+ tower /60∗ towerout + ∗ total l ayer4 0 l ayer5 t 0 = (1 (18) 8) ′= l ayer5 G //60 60 ++V t otal Then, the water is pumped to the transportation side as the inlet water of chillers in the Then, the water is pumped to the transportation side as the inlet water of chillers in the succeeding succeeding time step; this completes the one-step calculations. For an initial chiller inlet temperature time step; this completes the one-step calculations. For an initial chiller inlet temperature and a given and a given cooling load, the operating parameters can be gradually calculated. The simulation flow cooling load, the operating parameters can be gradually calculated. The simulation flow chart is shown chart is shown in Figure 7. in Figure 7. Figure 7. Simulation flow chart of the DVFP and WS system. Figure 7. Simulation flow chart of the DVFP and WS system. 5. Results 5. Results An appropriate inlet water temperature for chillers on a full-load day is illustrated in Figure 8. An appropriate inlet water temperature for chillers on a full-load day is illustrated in Figure 8. As expected, the water temperature in the CCCP system fluctuates more frequently than that in the As expected, the water temperature in the CCCP system fluctuates more frequently than that in the DVFP and WS system because there is no water storage. However, with the implementation of water DVFP and WS system because there is no water storage. However, with the implementation of water tanks, the DVFP and WS system stores cold water at night when the inlet temperature is lower and tanks, the DVFP and WS system stores cold water at night when the inlet temperature is lower and releases it during daytime hours. It is found that this low inlet temperature improves the average chiller COP Figure 9. Another advantage of the proposed system is the implementation of the DVFP, Appl. Sci. 2017, 7, 1139 12 of 16 Appl. Sci. 2017, 7, 1139 12 of 16 Appl. Sci. 2017, 7, 1139 12 of 16 releases it during daytime hours. It is found that this low inlet temperature improves the average chiller COP Figure 9. Another advantage of the proposed system is the implementation of the DVFP, which distributes water flow as required, and regulates the temperature difference ∆T to ensure high which distributes water flow as required, and regulates the temperature difference ∆T to ensure high which distributes water flow as required, and regulates the temperature difference DT to ensure high chiller efficiency. chiller efficiency. chiller efficiency. 0:00 4:00 8:00 12:00 16:00 20:00 0:00 0:00 4:00 8:00 12:00 16:00 20:00 0:00 Time Time CCCP DVFP&WS CCCP DVFP&WS Figure 8. Inlet cooling water temperature for chillers. Figure 8. Inlet cooling water temperature for chillers. Figure 8. Inlet cooling water temperature for chillers. Figure Figure 9. 9. Box Box chart chart of chi of chiller ller coef coeffici ficient ent of of pe performance rformance (COP) for the (COP) for the two two dif different ferent systems. systems. Figure 9. Box chart of chiller coefficient of performance (COP) for the two different systems. The effective total electric power of all equipment, including the chillers, pumps, and cooling The effect The effective ive total electr total electric ic power of all power of all equipm equipment, ent, iincluding ncluding tthe he chil chillers lers, , pum pumps, ps, and co and cooling oling towers, is shown in Figure 10. It can be observed that, although the new system consumes more towers, is shown in Figure 10. It can be observed that, although the new system consumes more towers, is shown in Figure 10. It can be observed that, although the new system consumes more power at night, the benefits afforded by this system during the daytime hours are more significant, power a power at t ni night, ght, the benef the benefits its a af fffor orded b ded by y thi this s syst system em durin during g the d the daytime aytime hour hours s are more are more sign significant, ificant, particularly during the peak hour at approximately 12:00, when the cooling tower and pump usage particularly during the peak hour at approximately 12:00, when the cooling tower and pump usage particularly during the peak hour at approximately 12:00, when the cooling tower and pump usage is reduced and the water tanks release cold. However, as it is limited by the size of the water tanks is is red reduced uced an and d tthe he w water ater ttanks anks re release lease c cold. old. However However ,, as as it it is is lim limit ited by ed by tthe he si size ze of of tthe he wat water er ttanks anks and capacity of water storage, the low temperature of the cold water stored in the tanks can only be and capacity of water storage, the low temperature of the cold water stored in the tanks can only be and capacity of water storage, the low temperature of the cold water stored in the tanks can only be sustained for a few hours. During the second peak hour of the day, which occurs at approximately sust sustained ained for fora a few few hour hours. s. During During tthe he se second cond p peak eak ho hour ur o of f tthe he d day ay,, which which occur occurs s at at ap appr proxi oximately mately 18:00, the comparative advantage of the proposed system is insignificant. A summary of electricity 18:00, the comparative advantage of the proposed system is insignificant. A summary of electricity 18:00, the comparative advantage of the proposed system is insignificant. A summary of electricity consumption on a full-load day is provided in Table 2, which also provides details of the field test consumpt consumption ion on a on afu full-load ll-load day day iis s provi provide ded in d in Tab Table le 2, wh 2, which ich al also so provides provides det details ails o of f tthe he fie fielld d ttest est results for comparison. results for comparison. results for comparison. Cooling water temperature (℃) Cooling water temperature (℃) Appl. Sci. 2017, 7, 1139 13 of 16 Appl. Sci. 2017, 7, 1139 13 of 16 0:00 4:00 8:00 12:00 16:00 20:00 0:00 Time CCCP DVFP&WS Figure 10. Total electric power for each system. Figure 10. Total electric power for each system. Table 2. Summary of electricity consumption on a full-load day (kWh). Table 2. Summary of electricity consumption on a full-load day (kWh). Systems Chiller PP DVFP CTP CTF Total Systems Chiller PP DVFP CTP CTF Total Field Test 20,645 3149 3335 27,129 Field Test 20,645 3149 3335 27,129 CCCP 20,151 3030 2970 26,151 CCCP 20,151 3030 2970 26,151 DVFP DVand FP aWS nd WS 19,260 19,260 949 949 342 342 2904 2904 23,455 23,455 The labels CTF and CTP in Table 2 are abbreviations for the cooling tower fans and The labels CTF and CTP in Table 2 are abbreviations for the cooling tower fans and corresponding corresponding cooling tower pumps, respectively. It is observed that the simulated energy cooling tower pumps, respectively. It is observed that the simulated energy consumption in the CCCP consumption in the CCCP system is lower than that measured via field testing, particularly for the system is lower than that measured via field testing, particularly for the pumps and cooling towers. pumps and cooling towers. This can be explained by the control strategy and the actual performance This can be explained by the control strategy and the actual performance of the equipment. During of the equipment. During operation, the pump control precision was observed to occasionally operation, the pump control precision was observed to occasionally decrease to an undesirable level; decrease to an undesirable level; moreover, the equipment was aging in some way that decreased moreover, the equipment was aging in some way that decreased efficiency, specifically affecting pump efficiency, specifically affecting pump efficiency and cooling tower efficiency. However, regarding efficiency and cooling tower efficiency. However, regarding the total energy consumption, as compared the total energy consumption, as compared to the CCCP system, the DVFP and WS system consumes to the CCCP system, the DVFP and WS system consumes 2696 kWh less electricity, equating to an 2696 kWh less electricity, equating to an approximately 10.3% in energy saved. As for transportation approximately 10.3% in energy saved. As for transportation system (including all of the pumps), the system (including all of the pumps), the DVFP and WS system consumes 1739 kWh less electricity DVFP and WS system consumes 1739 kWh less electricity than CCCP system, accounting for 57.4% than CCCP system, accounting for 57.4% of the energy in transportation system. Furthermore, as of the energy in transportation system. Furthermore, as compared to the field test results, the total compared to the field test results, the total energy saved on a full-load day is 3674 kWh, equating to energy saved on a full-load day is 3674 kWh, equating to nearly 14%. Although CTPs are added to nearly 14%. Although CTPs are added to the DVFP and WS system, the sum of DVFP and CTP the DVFP and WS system, the sum of DVFP and CTP remains as less than PP for reasons, such as remains as less than PP for reasons, such as fluctuation in frequency and water loop pressure fluctuation in frequency and water loop pressure optimization. Despite this, the transportation system optimization. Despite this, the transportation system only consumes less than 15% of the total energy, only consumes less than 15% of the total energy, thereby limiting the energy-saving potential. thereby limiting the energy-saving potential. Based on the simulation results of energy consumption, the daily electricity cost is calculated as Based on the simulation results of energy consumption, the daily electricity cost is calculated as according to the current tariff in Beijing. Calculations reveal the daily cost for the CCCP system to according to the current tariff in Beijing. Calculations reveal the daily cost for the CCCP system to be be 30,855 RMB, whereas the cost is 27,585 RMB for the DVFP and WS system. The daily cost saving 30,855 RMB, whereas the cost is 27,585 RMB for the DVFP and WS system. The daily cost saving equates to 10.6%. equates to 10.6%. In addition to the full-load-day study, energy consumption on a partial-load day is investigated In addition to the full-load-day study, energy consumption on a partial-load day is investigated to present a comprehensive view of system performance. The date is 30 May, and the simulated to present a comprehensive view of system performance. The date is 30 May, and the simulated cooling load as simulated via DeST software is 56,000 kWh, which is 80% of the maximum cooling cooling load as simulated via DeST software is 56,000 kWh, which is 80% of the maximum cooling load. The simulation described above is performed, and energy consumption and cost are calculated. load. The simulation described above is performed, and energy consumption and cost are calculated. Table 3 provides a comparison of the two days. It is found that the energy-saving potential is 13%, Table 3 provides a comparison of the two days. It is found that the energy-saving potential is 13%, which is similar to that observed on a full-load day. which is similar to that observed on a full-load day. Total electric power (kW) Appl. Sci. 2017, 7, 1139 14 of 16 Table 3. Comparison of systems on typical days with different cooling loads. Cooling Loads Systems Energy Consumption (kWh) Cost (RMB) CCCP 26,151 30,030 Full Load DVFP and WS 23,455 27,191 CCCP 21,651 25,969 80% Load DVFP and WS 18,843 23,736 6. Conclusions In this paper, the operating performance and energy efficiency of a novel DVFP and WS system that is applied to the cooling water operations in a DCS was analyzed. The basic principles and a schematic diagram of the proposed system have been presented, along with an analysis of the energy-saving potential. A DCS located in Beijing, China was selected for a case study; this included an on-site investigation of the system. Using this DCS as a reference, a series of simulations were conducted and effective operating data for two different systems exposed to various weather conditions were calculated. Through comparison with field test results and a simulated CCCP system, the proposed system demonstrates a 10% saving for both energy and cost part for the whole system. The throttling valves present in the CCCP system were replaced with variable-frequency pumps to ensure appropriate water flow regulation; additionally, in contrast to the CCCP system, water pressure loss via valves was prevented. This resulted in increased pump efficiency, the prevention of excessive water flow, and a reduction of transportation energy consumption. In addition, the water storage tanks enabled the resourceful exploitation of the electric tariff and pump control flexibility. The cold water was stored at night and was released during the period when the cost of electricity was highest. Via the proposed system, not only were the operating costs of pumps and cooling towers reduced, but also the chiller COP was increased because of the low cooling water inlet temperature of the condenser. It can be concluded that the size of the transportation system and the cooling load profile play an important role in the applicability of this new system. In a large district energy system with long pipes and various end uses, the transportation system consumes a majority of the energy; under these conditions, the advantages of the proposed system are more notable. As the concept of distributed variable-frequency pumps is currently being applied in large city-scale district heating systems, it would not be exceedingly difficult to begin implementing the proposed cooling system on an equivalent scale. Moreover, the DVFP and WS system is also applicable in systems with changing end-use cooling loads, as it can promptly initiate the changes that are necessary to maintain its level of efficiency by quickly adjusting flow as required. Thus, from what has been presented in this paper, it can be ascertained that there is significant potential of the DVFP and WS system application in many cases to save energy and reduce operating costs. However, some defects still exist in this study, in that all of the research works are based on a field test of the current system and simulation of the proposed system. There is a lack of the applications of DVFP and WS system in real operating projects and the real performance of this new system, which would be our future focus. Acknowledgments: This work was supported by the Natural Science Foundation of China (Grant No. 51521005), the 13th Five-Year National Key Technology R & D Program of China (Grant No. 2016YFC0700704). Author Contributions: Yichi Zhang and Jianjun Xia conceived and designed the experiments; Yichi Zhang and Chuanxin Chen performed the experiments; Yichi Zhang and Chuanxin Chen analyzed the data; Jianjun Xia contributed analysis tools; Yichi Zhang and Jianjun Xia wrote the paper. Conflicts of Interest: The authors declare no conflict of interest. Appl. Sci. 2017, 7, 1139 15 of 16 Nomenclature DCS district cooling system DVFP distributed variable-frequency pump WS water storage CCCP conventional central circulating pump COP coefficient of performance DT temperature difference VFP variable frequency pump twelve independent sub-buildings selected as S1–S12 testbeds G volume flow rate, m /h H pump head, mH O Q electric power, W t confluent water temperature before cooling tower clwoutz t chiller inlet water temperature clwin E efficiency of the cooling tower tower t wet-bulb temperature outdoors wet t cooling water temperature after cooling tower towerout t average cooling water temperature in the condenser clwaver R cooling load ratio of the chiller COP ratio of the operating chiller COP to its nominal COP ratio COP nominal COP t chilled water temperature set point chwset layer1–layer5 five layers inside water tank V volume of each layer h efficiency of the pump n operating frequency t temperature pp primary pump total summary of all sub-buildings ct cooling tower m main pipe si i-th pump nominal nominal condition of equipment ‘ parameter in the succeeding time interval References 1. 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Journal

Applied SciencesMultidisciplinary Digital Publishing Institute

Published: Nov 6, 2017

References