Direct Method to Design Solar Photovoltaics to Reduce Energy Consumption of Aeration Tanks in Wastewater Treatment Plants
Direct Method to Design Solar Photovoltaics to Reduce Energy Consumption of Aeration Tanks in...
Zacchei, Enrico;Colacicco, Antonio
2022-06-06 00:00:00
infrastructures Article Direct Method to Design Solar Photovoltaics to Reduce Energy Consumption of Aeration Tanks in Wastewater Treatment Plants 1 , 2 , 3 Enrico Zacchei * and Antonio Colacicco Itecons, 3030-289 Coimbra, Portugal University of Coimbra, CERIS, 3004-531 Coimbra, Portugal Environmental Engineer-Freelancer, Luigi Pernier Avenue, 00124 Rome, Italy; antonio_colacicco@hotmail.it * Correspondence: enricozacchei@gmail.com Abstract: Photovoltaic (PV) energy systems are considered good renewable energy technologies due to their high production of clean energy. This paper combines a PV system with wastewater treatment plants (WWTPs), which are usually designed separately. For this, a recent methodology was adopted, which provides direct steps to estimate the peak powers of PV plants (PVPs) by using the airflow of blowers. The goal was to reduce the energy consumption of aeration tanks in WWTPs. Analytical equations and parameters based on the air temperature, solar irradiation, biological kinetic, dissolved oxygen, and mechanical oxygenation are adopted. The key parameter in this methodology is the air temperature variation that represents an approximated temperature in the WWTP’s oxidation tanks. It is shown, through the analysis of small WWTPs, that since the temperature changes for each season, there is a peak in the function of the quantity of oxidation, which is high in the summer season. Further, the curve trends of temperature for WWRPs are similar to PVPs. Therefore, it could be possible to design the PV system with the WWTPs well. The results show that the air temperature curves increase in a directly proportional way with the consumption of energy from Citation: Zacchei, E.; Colacicco, A. oxidation blowers; this could induce a more conservative PVP design. Furthermore, the results show Direct Method to Design Solar that the mean trend of the energy consumption of the analyzed aeration systems reaches about 8.0% Photovoltaics to Reduce Energy at a temperature of 20–25 C, covering a good part of the oxidation tank consumption. Consumption of Aeration Tanks in Wastewater Treatment Plants. Keywords: auto-consumption systems; clean energy; oxidation tanks; PVP; WWTP Infrastructures 2022, 7, 79. https:// doi.org/10.3390/ infrastructures7060079 Academic Editors: Susana Lagüela 1. Introduction López and GM Shafiullah Photovoltaic (PVPs) plants are considered good renewable energy technologies since Received: 6 April 2022 they have a high potential for clean energy productivities [1]. They have various environ- Accepted: 2 June 2022 mental advantages, for instance, in producing low fossil-fuel and CO emissions. Moreover, Published: 6 June 2022 PVPs are based on auto-consumption due to the free input energy. This paper aims to develop a smart method for designing PVs by optimizing the Publisher’s Note: MDPI stays neutral auto-consumption of oxidation tanks in wastewater treatment plants (WWTPs). For this, with regard to jurisdictional claims in the key design parameters are the air and wastewater temperatures and their correlations. published maps and institutional affil- iations. Some parameters that consider the bacteria respiration have also been accounted for in accordance with innovative projects [2,3]. PVPs are treated in the literature at the level of forecasting power generations, where several time series prediction statistical methods and algorithms on artificial intelligence Copyright: © 2022 by the authors. are introduced, investigating the effect of prediction time horizon variation [1] and of the Licensee MDPI, Basel, Switzerland. design in extreme conditions, where mathematical models to predict the energy generation This article is an open access article of PVPs in hot and humid climatic condition are studied [4]. In [1,4], some parameters were distributed under the terms and studied that impact the electrical power generation, e.g., the type of solar cells and their conditions of the Creative Commons conditions, electrical circuits of modules, solar incidence angle, and weather conditions. Attribution (CC BY) license (https:// In [5], a state-of-the-art PV solar energy generator has been made, showing the ways of creativecommons.org/licenses/by/ obtaining the energy, its advantages and disadvantages, applications, current market, costs, 4.0/). Infrastructures 2022, 7, 79. https://doi.org/10.3390/infrastructures7060079 https://www.mdpi.com/journal/infrastructures Infrastructures 2022, 7, 79 2 of 13 and technologies. Here, the possible applications are shown, e.g., for telecommunications, water pumping, agriculture, water heating, grain drying, water desalination, and space vehicles and satellites. WWTPs have been treated by considering the aeration energy consumption, where a fuzzy logic supervisory control system for optimizing nitrogen removal has been devel- oped [6], the influence of seasonal temperature fluctuations on raw domestic wastewater composition and collected sludge filterability [7], and the balance of the micropollutant flows, where a simple balancing method using passive samplers over a period has been tested to determine the elimination rates of several common micropollutants of household and industrial sources in full-scale WWTPs of different performances [8]. In [9], a complete review has been shown to provide a technical contribution to the regulations as well as to support stakeholders by recommending possible advanced treatment options, in particular, the removal of contaminants of emerging concern and antibiotics, antibiotic-resistant bacteria, and antibiotic resistance genes. In [10], some strategies to achieve environmental sustainability for wastewater treat- ments are presented; in particular, it examines how environmental technology contributes to wastewater improvement in several countries. Annualized information was used and collected from various official sources of information and subsequently processed with various econometric approaches. As mentioned, this paper combines PVP with a WWTP since solar PV has a great generation potential in WWTPs. It is known that technical, economic, and socio-political factors influence the decision to adopt solar PVs in WWTPs as treated in [11,12]. Some papers that combine PVs with WWTPs have been published. In [13], a direct connection of PV modules to the electrochemical reactor was carried out to reduce the non-renewable primary energy consumption; for this, a solar PV electro-oxidation process for WWTP was modeled; in [14], both plants are combined with each other to design floating PVs installed on, e.g., natural lakes, dams reservoirs, and offshore areas, where a simple and economic design solution in South Australia with optimal orientation and distance among rows was suggested; in [15], where a wastewater-to-hydrogen processor was proposed to maximize the hydrogen and minimize the energy consumption. In [16], the control and planning for energy durations, where the feasibility of using solar PV cells and a battery system as a renewable energy source for driven electrochemical WWTPs were studied; whereas in [17], the feasibility and utility of using an electro-oxidation system directly powered by a PV array for the treatment of wastewater was demonstrated. More recent papers have carried out a quantitative analysis of the solar energy gen- erated from WWTPs where specific 105 Californian WWTPs were examined, of which 41 installed a solar PV system [18]. In [19], it was shown that the synergy of small and medium WWTPs with PV is of great interest from an energetic/environmental/economic point of view; it was stated that “this synergy is worth exploring and implementing on a large scale for all new WWTP”. Therefore, more studies are necessary. Moreover, in [20], electric energies from PV modules were used to remove aniline in wastewater, showing that this process is feasible, and aniline can be removed in a safer and lower-cost way. In [21], it was highlighted that small and insular communities are sometimes not served by an efficient WWTP, and this was a hazard for both the environment and public health. For this, it was shown that a PV system covers the electricity needs of the apparatus. Thus no external electricity source should be necessary for its use. This coupling could be used to minimize the community’s costs. The motivation of this research is based on some critical analyses published in previous studies [22,23], which should justify the two main hypotheses for this work: (i) the oxidation tanks consume ~30.0% of the total cost of the energy of a WWTP. Thus the use of a PV could cover part of this consumption in a clean way; (ii) for a small treatment plant, the energy consumption is high in the function of the oxygenation in aeration blowers where a PV could be installed. Infrastructures 2022, 7, x FOR PEER REVIEW 3 of 14 oxidation tanks consume ~30.0% of the total cost of the energy of a WWTP. Thus the use of a PV could cover part of this consumption in a clean way; (ii) for a small treatment Infrastructures 2022, 7, 79 3 of 13 plant, the energy consumption is high in the function of the oxygenation in aeration blow- ers where a PV could be installed. Further, through the analysis of the Zurich WWTP, in [24], it is shown that the tem- Further, through the analysis of the Zurich WWTP, in [24], it is shown that the tem- perature of wastewater in the entrance changes for each season. For a small WWTP, a peak perature of wastewater in the entrance changes for each season. For a small WWTP, a of energy consumption in the summer was verified since when the temperature of the peak of energy consumption in the summer was verified since when the temperature wastewater increases the oxygen consumption, thus the aeration blowers need to work of the wastewater increases the oxygen consumption, thus the aeration blowers need to more. work more. Therefore, through critical analyses, some preliminary data have been collected that, Therefore, through critical analyses, some preliminary data have been collected that, with the relations and parameters on the oxygen consumption and temperature, provide with the relations and parameters on the oxygen consumption and temperature, provide several materials to be used in this work (Section 2.1). Section 2.2 shows the model, where several materials to be used in this work (Section 2.1). Section 2.2 shows the model, its goal is to provide some analytical relations to design PVPs to reduce the energy con- where its goal is to provide some analytical relations to design PVPs to reduce the energy sumption of WWTPs since they represent an important part of the “anthropic water cycle” consumption of WWTPs since they represent an important part of the “anthropic water [12]. Finally, in Section 3, analyses and results have been presented in terms of energy cycle” [12]. Finally, in Section 3, analyses and results have been presented in terms of consumption of blower’s aeration systems with respect to PV plants to evaluate the good energy consumption of blower ’s aeration systems with respect to PV plants to evaluate the and/or optimum performance of the system. good and/or optimum performance of the system. This work could help the sector make decisions over PV investments, especially re- This work could help the sector make decisions over PV investments, especially garding wastewater utilities, which ultimately lead to more sustainable management regarding wastewater utilities, which ultimately lead to more sustainable management practices. Thus, we encourage a further contribution to promoting the integration of re- practices. Thus, we encourage a further contribution to promoting the integration of newable energy sources as PVPs, together with WWTPs and their sectors. renewable energy sources as PVPs, together with WWTPs and their sectors. This purpose is consistent with goal 7 of the 2030 Agenda [25] in order to “ensure This purpose is consistent with goal 7 of the 2030 Agenda [25] in order to “ensure access to affordable, reliable, sustainable and modern energy for all”. access to affordable, reliable, sustainable and modern energy for all”. 2. Materials and Methods 2. Materials and Methods 2.1. Materials 2.1. Materials 2.1.1. 2.1.1. Re Refer feren ence ce Data Data The electricity consumption of an “anthropic water cycle”, considering the final uses The electricity consumption of an “anthropic water cycle”, considering the final uses (e.g., (e.g., agri agricultural, cultural, ci civil, vil, and and i industrial ndustrial uses), uses),ranges ranges be between tween 1.0 1.0 and and 8. 8.00 kW kWh/m h/m .. Thi Thiss consumption of energy includes a percentage, without including the final uses, between consumption of energy includes a percentage, without including the final uses, between 1.0% and 5.0% of the national electricity requirements and between 5% and 20%, including 1.0% and 5.0% of the national electricity requirements and between 5% and 20%, including the final uses [22]. the final uses [22]. The flowchart in Figure 1 shows the process diagram of the water management The flowchart in Figure 1 shows the process diagram of the water management cycle cycle (water source ! water body) from withdrawal (i.e., pumping and transport) to (water source → water body) from withdrawal (i.e., pumping and transport) to the the wastewater disposal, where the water body is re-introduced in accordance with the wastewater disposal, where the water body is re-introduced in accordance with the Euro- European directive [26]. It is shown that the “wastewater treatment” phase (yellow box in pean directive [26]. It is shown that the “wastewater treatment” phase (yellow box in Fig- Figure 1) allows the closing/opening and continuation of this cycle. ure 1) allows the closing/opening and continuation of this cycle. Figure 1. Water management cycle: process diagram (adapted from [22]). Figure 1. Water management cycle: process diagram (adapted from [22]). As already mentioned, in urban WWTPs, it is estimated that ~30% of the costs of the management are attributed to energy consumption, even if ~50% can include additional costs of the other treatments, as shown in [22,23]. The electricity consumption of a WWTP with anaerobic sludge digestion is between 0.40 and 0.70 kWh/month in function of the type/size of the studied plant. In general, WWTPs have an electricity consumption between 10 and 40 kWh/PE per year (PE is the population equivalent estimated as 1 PE 60 gBOD /d [8], where BOD is the biochemical 5 5 Infrastructures 2022, 7, 79 4 of 13 oxygen demand during the day, d), whereas in a WWTP, with digestion of an aerobic-type, the electricity consumption can reach values of 40–70 kWh/PE per year due to the lack of energy to be recovered [23]. The BOD parameter includes the biodegradable portion of the organic substances with respect to the chemical oxygen demand (COD) parameter, which measures the global oxidation of (in)organic substances. The biological oxidation regards the highest percentage of total consumption (e.g., 50–65%), then there are the treatment lines of the sludge, which can reach a con- sumption of 20%, and, finally, there is the pumping phase, using ~15% [23]. In the WWTPs of urban sludges, a great part of the electricity is used in the oxidation tanks by the aeration process. The percentage incidence of the consumption of the energy, in the function of the operation costs, as well as maintenance costs, are shown in [23], with the following weight: 50% energy, 21% management, 13% chemical, 11% maintenance, 5% others. In [23], it is shown that the distribution of the electricity in the various steps of tradi- tional WWTPs, in particular, the oxygen aeration in tanks, is the greatest with a value of 55.6%, whereas the lowest value refers to pre-treatment of the wastewater process with a value of 0.4%. Moreover, by analyzing 253 WWTPs, an acceptable agreement between the total consumption of the energy of WWTPs and the volume of sewage flows was shown. In the same way, the impact of the large plants, which have low energy consump- tion (expressed in m ) of treated sewages and removed organic substances (in kg), has been highlighted. Finally, an example of the specific consumption per kg of COD removed (expressed in kWh/kgCOD ) has been shown, which identifies the quality of the water by the variation rem of treatment classes for WWTPs. For a potential class < 2000 PE corresponds to a mean value of 3.21 kWh/kgCOD , whereas for >100,000 PE, we have 0.85 kWh/kgCOD . rem rem All these data represent the input parameters that have incentivized this study. 2.1.2. Oxygen and Temperature Role In the oxidation tanks, to activate the reactions of biological substances, the presence of dissolved oxygens (DOs) is necessary; thus, its continuous creation to equilibrate the consumption of the carbon-oxidant bacteria respiration is also necessary [2,9,27]. DO is a parameter that allows the control of the biological process in relation to the energy reduction [6,28]; also, the biological oxidation processes are correlated to the temperature, T. The biological reactions can increase with a temperature between 0 and 40 C with an estimated optimum T between 25 and 35 C. However, in the aeration tanks, the latter temperatures are rarely achieved. With a temperature T < 5 C, the biological activity can strongly decrease [29]. The respiration of the bacteria is quantified by two different coefficients: active breath- ing, a (Equation (1)), and endogenous respiration, c (Equation (2)). The a-coefficient is correlated to the oxidative reactions as well as synthesis reactions where the microorganisms take energy by their own metabolism and by the creation of new cell synthesis. Further, this coefficient represents the consumption of oxygen for the destruction of the organic substances, which is proportional to the removed substrate of carbonaceous [30]. This a-coefficient varies with respect to the WWTP used, and it can be evaluated by [30]: 0.65 kg a = (1) kg BOD where kg is the mass of the consumption of oxygen (O ), and kg is the mass of the O2 2 BOD5 BOD concentration. Both parameters are correlated with each other through the volume of the oxidation reactor, V , by kg = V BOD . oxi BOD5 oxi 5 The other coefficient, i.e., endogenous respiration, is related to the use of the available substrate for critical temperature and demolition of bacteria cells. In this sense, it regards Infrastructures 2022, 7, 79 5 of 13 the metabolism of the bacteria. This endogenous respiration coefficient, c , can be described by [30,31]: 0.13 kg T 20 2 T 20 c = c 1.084 = 1.084 (2) T 20 kg d VSS where c refers to a c value of 20 C (i.e., c ! c ), and kg is the mass of volatile 20 T = 20 20 VSS suspended solids (VSSs). Therefore, the oxygen consumption can be expressed by [6,30]: a kg c kg BOD T 5 Biomass R = + (3) o2 d d where kg is the biomass (= V VSS; here approximated by kg VSS [12]). Biomass oxi Biomass If there are no relevant variations of the kg during a season, the requirement of BOD5 oxygen mainly varies due to the function of the T increasing due to Equation (2). Fur- thermore, in the wastewater, the oxygen concentration depends on Henry’s law, which correlates the concentration of O present in the liquid phase with respect to its concentra- tion present in the gas phase [32]. In this study, this correlation indicates that the amount of DO is inversely proportional to the increase in the wastewater temperature. Therefore, to maintain an acceptable aerobic degradation of kg with an increasing wastewater T, in BOD5 the oxygenation tanks, some oxygen “surplus” must be supplied. This implies that the aera- tor systems could work hard during the hot months to guarantee a sufficient concentration of DO [6,29]. In [7,29], the fluctuation of the wastewater T as a function of time is shown. In [26], the air temperature curve where it is evident that the curves of the high/low temperatures of the wastewater vary, with a maximum value in summer months (i.e., July in the Mediterranean area) is also plotted. These fluctuations of the curves refer to a small plant since they do not fluctuate (i.e., they are quasi-constant) in large plants. An important phenomenon regards the overlapping of the wastewater temperature curves (high and low) with the curve that shows the maximum air temperature. This overlap happens in small WWTPs, because of the seasonality, which is directly correlated with the irradiation/temperature. Therefore, the adoption of the air temperature values for the design could provide a good estimation regarding the thermal trend of the wastewater overdesign, in favor of safety, the PVPs. Finally, some aspects should also be mentioned to indicate the increase in the tem- perature of the wastewater (influent) flow in hot periods, which are associated with high proliferation of organic substances in WWTPs with small and/or medium size. This in- crease can amplify the total consumption of energy, mainly involving the aeration systems for producing oxygen. These aspects regard the energy (see two hypotheses in Section 1), chemical–physical, and biological factors. Regarding the chemical–physical factors in the wastewater: (1) the temperature oscillates due to its seasonality, and due to the wastewater flow rate; (2) the increase of the T reduces the solubility of the oxygen. The biological factors include (3) the increasing of the wastewater flow rate and the oxygen requirement of organic substances for the kinetic digestions. Small WWTPs have greater power consumption than large plants, making them more sensitive to increases in energy cost [33]. Therefore, it is important for small plants to find alternative energy sources to increase resilience to energy cost fluctuations. Solar PV represents a suitable source of energy for small WWTPs for two main reasons: the lack of biogas recovery opportunities and land availability [18]. Table 1 shows the parameters used to carry out the analyses. Some parameters have already been explained, whereas other ones will be explained in Section 2.2. Infrastructures 2022, 7, 79 6 of 13 Table 1. Data used for the analysis. Parameter Value Active breathing coefficient, a 0.65 (Equation (1)) Biochemical oxygen demand, BOD 0.8 kg BOD5 Endogenous respiration coefficient, c 0.09–0.19 (Equation (2)) Volatile suspended solids, VSS 4.0 kg [12] VSS Correction factor, 0.80 [30] Aerators fouling factor, F 0.90 [12] Correction factor, 1.0 [30] Standard aeration efficiency, SAE 1.55–3.0 kg /kWh [34] 20 O2 a b Assuming kg = kg . The value is correlated to the sludge loading rate (SLR) by: SLR = BOD /VSS = 0.20 [8,12]. O2 BOD5 5 c d With c = 0.13 and T = 15–25 C. For clean water at 20 C, pressure of 101.32 kPa, and DO = 0 mg/L. The SAE value depends on the adopted aeration system. 2.2. Methodology For estimating the maximum consumption of energy of a selected aeration system, direct analytical equations, recently introduced in [12], have been used. These equations should verify the energy consumption variations of a certain aeration system regarding the oxygen requirements and wastewater temperature in oxidation tanks. Considering the relations already mentioned in Section 2.1.2, i.e., kg = V VSS Biomass oxi and kg = V BOD , Equation (3), by multiplying for d and dividing for V , BOD5 oxi 5 oxi describes the incremental parameter of R , I , which estimates the increasing of R 02 RO2 02 with respect the standard temperature T (i.e., T = 20 C) in the wastewater. It is defined, as a percentage (%), as: [(a BOD ) + (c VSS)] [(a BOD ) + (c VSS)] 5 T 5 20 I = (4) RO2 [(a BOD ) + (c VSS)] 5 20 An aeration blower should be defined by the oxygen transfer capacity, i.e., the oxygen transfer rate (OTR): (C C ) (T 20) s L (T 20) OTR = SOTR 1.024 F with SOTR = 1.024 F (5) where C is the service oxygen concentration and C is the saturated oxygen concentration. L s Both concentrations are expressed in mg/L, and here, they are assumed to be C = C , s L neglecting the dynamic component of gas concentration. , , and F (i.e., aerator fouling factors) are constants. SOTR is the standard-OTR, which refers to the oxygen measurements in the clean water under standard pressures and temperatures. OTR is expressed in kg /h. O2 From Equation (5), the incremental parameter of SOTR, I (in %), is: SOTR (T 20) 1.024 F F ( ) I = (6) SOTR ( F) For measuring the variation of the SAE, I , with respect 20 C (i.e., SAE ), and by SAE 20 considering Equation (6), Equation (7), expressed in kg /kWh, is used: O2 I = SAE + (SAE I ) (7) SAE 20 20 SOTR Finally, to correlate I with the I (Equation (4)) Equation (8), in %, is used: SAE RO2 Ip = I (8) RO2 RO2 SAE Equation (8) provides the main output that allows the energy consumption values for different aeration blowers adopted in the oxidation tanks to be plotted. Infrastructures 2022, 7, x FOR PEER REVIEW 7 of 14 I =SAE + (SAE × I ) (7) Finally, to correlate ISAE with the IRO2 (Equation (4)) Equation (8), in %, is used: Ip = × I (8) Infrastructures 2022, 7, 79 7 of 13 Equation (8) provides the main output that allows the energy consumption values for different aeration blowers adopted in the oxidation tanks to be plotted. The general methodology can be described step-by-step as follows: (i) collection of The general methodology can be described step-by-step as follows: (i) collection of data by database, the literature, and Equations (1)–(3) (see Table 1); (ii) plotting the average data by database, the literature, and Equations (1)–(3) (see Table 1); (ii) plotting the aver- monthly energy production curves, E (see Section 3); (iii) estimation of I curves by the m RO2 age monthly energy production curves, Em (see Section 3); (iii) estimation of IRO2 curves by proposed equation, Equation (8), for 5 aeration systems; (iv) defining the performances of the proposed equation, Equation (8), for 5 aeration systems; (iv) defining the performances the coupled system (see Section 3). of the coupled system (see Section 3). 3. Analyses and Results 3. Analyses and Results The analyses consist of developing the above-mentioned equations for a general The analyses consist of developing the above-mentioned equations for a general case case and then for a specific example. The correlation key of the analyses regards the fact and then for a specific example. The correlation key of the analyses regards the fact that that the energy consumption of the aeration blowers should measure the whole energy the energy consumption of the aeration blowers should measure the whole energy con- consumption of the WWTP. This correlation represents an important issue for the whole sumption of the WWTP. This correlation represents an important issue for the whole sys- system in order to maintain the equilibrium of the energy. tem in order to maintain the equilibrium of the energy. In Equations (4) and (6), the following (some) values have been calculated for wastew- In Equations (4) and (6), the following (some) values have been calculated for ater T = {15, 20, was 25} tew C: ate Ir T == {1 { 5, 2 16.6, 0, 250, } °C 24.8}%, : IR02 = {and −16.6 I, 0, 24.8 = }{11.2, %, and 0, ISO TR 12.6}%. = {11.2, Thus, 0, −12.6 the }%. Thus, the R02 SOTR I (Equation (7)) and Ip (Equation (8)) values are obtained for five aeration systems: ISAE (Equation (7)) and IpRo2 (Equation (8)) values are obtained for five aeration systems: SAE Ro2 (1) large bubble (1ventilation; ) large bubble vent (2) surface ilation; ( aerators 2) surfwith ace aer low atospeed; rs with (3) low speed surface; ( turbines 3) surface with turbines with downward flow; (4) superficial brushes; and (5) submerged turbines with injector. downward flow; (4) superficial brushes; and (5) submerged turbines with injector. Figure 2 shows the results of IpRO2 with respect to the wastewater T in the oxidation Figure 2 shows the results of Ip with respect to the wastewater T in the oxidation RO2 tanks. These curves are calibrated at T = 20 °C (middle point), which represents, as already tanks. These curves are calibrated at T = 20 C (middle point), which represents, as already mentioned, the standard conditions. mentioned, the standard conditions. Figure 2. IpRO2 values as a function of wastewater T for five aeration systems. Figure 2. Ip values as a function of wastewater T for five aeration systems. RO2 The curves in Figure 2 allow the quantification of not only the aerator technology that The curves in Figure 2 allow the quantification of not only the aerator technology that can be classified can be as most classified energy-ef as mo ficient st en but ergy- also effic the ient incr but a easing lso the of t he increa seasonal sing of the season consumption al consump- of energy of the tion consider of energ edyaerator of the considered , independently aerator of , in the deinfluent pendently flow of the influent flow rate of BOD . rate of BOD5. It is shown that the trend of the IpRO2 curves for the five aeration systems ranges be- It is shown that the trend of the Ip curves for the five aeration systems ranges RO2 tween −10% and 18% for 15–25 °C. The “superficial brushes” (blue solid line) systems rep- between 10% and 18% for 15–25 C. The “superficial brushes” (blue solid line) systems resent the technologies’s more energy intensiveness. represent the technologies’s more energy intensiveness. The “large bubble ventilation” (black solid line) is less energy-intensive; in fact, the The “large bubble ventilation” (black solid line) is less energy-intensive; in fact, the presence of the bubbles in an aeration system is correlated to the energy generation; in presence of the bubbles in an aeration system is correlated to the energy generation; in particular, the dimension of the air bubbles affects the airflow and its velocity, as treated in [31]. Wastewater temperature mainly depends on the external air temperature and season- ality; therefore, this temperature could be approximated to the air temperature, as shown in [12]. The idea of using the air temperature curve should be in favor of safety since this curve would overestimate the PV system in terms of power outcomes covering the peaks of energy demands. In fact, in [29], it is shown that between ~8 and 20 C, the external air temperature curve is higher than the high wastewater temperature curve. To validate the methodology and the results shown in Figure 2, an example has been carried out. To design the peak powers, in a preliminary way, of a PV system, data (from the period 2007–2016 year retrieved from database [35]) regarding the solar radiations and Infrastructures 2022, 7, x FOR PEER REVIEW 8 of 14 Infrastructures 2022, 7, x FOR PEER REVIEW 8 of 14 particular, the dimension of the air bubbles affects the airflow and its velocity, as treated particular, the dimension of the air bubbles affects the airflow and its velocity, as treated in [31]. in [31]. Wastewater temperature mainly depends on the external air temperature and sea- Wastewater temperature mainly depends on the external air temperature and sea- sona sona lili ty; ty; ther ther efore, efore, thi thi ss te te m m pp erat erat ure ure co co uld uld b b ee ap ap pp ro ro xx im im aa ted ted to to t t hh e air e air tem tem pp ee rat rat ure ure , as , as shown in [12]. The idea of using the air temperature curve should be in favor of safety shown in [12]. The idea of using the air temperature curve should be in favor of safety since this curve would overestimate the PV system in terms of power outcomes covering since this curve would overestimate the PV system in terms of power outcomes covering the peaks of energy demands. In fact, in [29], it is shown that between ~8 and 20 °C, the the peaks of energy demands. In fact, in [29], it is shown that between ~8 and 20 °C, the external air temperature curve is higher than the high wastewater temperature curve. external air temperature curve is higher than the high wastewater temperature curve. Infrastructures 2022, 7, 79 8 of 13 To validate the methodology and the results shown in Figure 2, an example has been To validate the methodology and the results shown in Figure 2, an example has been carr carr ied ou ied ou t. T t. T oo design design the the peak powers peak powers , in a prel , in a prel imin imin ary w ary w aa y, o y, o f a f a PV s PV s yy ss tem, d tem, d aa ta ( ta ( from from the period 2007–2016 year retrieved from database [35]) regarding the solar radiations and the period 2007–2016 year retrieved from database [35]) regarding the solar radiations and air temperatures for “Is Arenas” WWTP, Cagliari region, Italy, have been collected. Figure air temperatures for “Is Arenas” WWTP, Cagliari region, Italy, have been collected. Figure air temperatures for “Is Arenas” WWTP, Cagliari region, Italy, have been collected. Figure 3 3 shows the correlated data plotted by blue points highlighting the widespread trends and 3 shows the correlated data plotted by blue points highlighting the widespread trends and shows the correlated data plotted by blue points highlighting the widespread trends and a 2 2 a high concentration from 300.0 W/m for 15–25 °C. a high concentration from 300.0 W/m for 15–25 °C. high concentration from 300.0 W/m for 15–25 C. Figure 3. Figure 3. Solar Solar irradiance/air t irradiance/air t ee m m pp eratu eratu re po re po ints at ints at “Is Aren “Is Aren as” WWTP (Ca as” WWTP (Ca gg liari, liari, Italy) [35 Italy) [35 ]. ]. Figure 3. Solar irradiance/air temperature points at “Is Arenas” WWTP (Cagliari, Italy) [35]. Fig Figur ure e 4 sho 4 shows ws the so the solar lar i irradiance rradiance an and d ai airr temperatur temperature c e curve urve d during uring a a day, in day, indicating dicat- Figure 4 shows the solar irradiance and air temperature curve during a day, indicat- ing their thei possible r possible cor correlation relatio [n [1 15].5The ]. The air aiT r T curve co curve could uld be cons be consistent istent wi with th the the da daily ily power power ing their possible correlation [15]. The air T curve could be consistent with the daily power outputs of a PVP: it assumes a null value between 7:00 p.m. and 4:00 a.m. and a very outputs of a PVP: it assumes a null value between 7:00 p.m. and 4:00 a.m. and a very low outputs of a PVP: it assumes a null value between 7:00 p.m. and 4:00 a.m. and a very low low value between 4 and 6 h and 17 and 19 h; therefore, in this example, only the values value betw value betw ee ee n 4 n 4 and and 6 h 6 h and 17 an and 17 an d 19 d 19 h; ther h; ther efore efore , in this ex , in this ex ample, only ample, only the the value value ss be- be- between 7 and 16 h have been considered. tween 7 and 16 h have been considered. tween 7 and 16 h have been considered. Figure 4. Solar irradiance/air temperature curves over time [35] (adapted from [12]). Figure 4. Solar irradiance/air temperature curves over time [35] (adapted from [12]). Figure 4. Solar irradiance/air temperature curves over time [35] (adapted from [12]). By us By using ing the the est estimated imated glglobal obal irrirradiances adiances (Fig (Figur ure 3) e, a 3 p ), o assib possib le esle tim estimation ation of the of pr the o- By using the estimated global irradiances (Figure 3), a possible estimation of the pro- produced mean energy for PVPs is defined. To verify the overlapping of the production duced duced mean mean energy energy for for P P V V Ps is d Ps is d ee fine fine d. To ve d. To ve rify rify the overlapping of th the overlapping of th e pro e pro dd uction o uction o f f of PV energy with the collected data due to the increasing of the energy consumption of aeration blowers, the following restraints were assumed: (i) the PV production during the months of a PVP has a peak power of 1 kWp; (ii) the energy consumption of WWTPs happen under the standard condition at 20 C, for the curve fluctuations of the air temper- ature during the months. Moreover, the used hypothesis is that, during the whole year, R = 150 kg /month (Equation (3)). O2 RO2 Table 2 lists the energy production of PVs by several parameters processed by database [35]. The peak value of the average daily sum of global irradiation received by the modules, H(i) , is H(i) = 7.28 kWh/m /d, which is consistent with the literature’s [4] d d reference peak. Infrastructures 2022, 7, 79 9 of 13 Table 2. PV energy production values processed by database [35]. E (kWh/m) 2 2 Month E (kWh/d) H(i) (kWh/m /d) H(i) kWh/m /m) (kWh) m m d d (Figures 5 and 6) 1 (January) 3.05 94.57 3.65 113.01 9.44 2 3.62 101.28 4.34 121.58 12.23 3 4.27 132.23 5.21 161.45 11.9 4 4.73 141.80 5.90 177.0 10.24 5 5.05 156.45 6.41 198.65 10.81 6 5.42 162.68 7.04 211.10 4.26 7 5.52 171.09 7.28 225.59 5.55 8 5.44 168.51 7.14 221.44 6.85 9 4.73 142.04 6.10 182.91 5.0 10 4.11 127.39 5.16 160.10 7.57 11 3.20 95.88 3.90 117.13 9.91 12 (December) 2.89 89.50 3.47 107.48 9.46 Mean 4.34 131.95 5.47 166.45 2.40 Temperature/solar AOI loss (%) Spectral effects (%) Combined loss (%) irradiance loss (%) 2.65 0.66 5.93 20.73 Note: E = Average daily energy production (kWh/d). E = Average monthly energy production (kWh/month). d m H(i) = Average daily sum of global irradiation per square meter received by the modules (kWh/m /d). H(i) = Average monthly the solar irradiation sum per square meter received by the modules (kWh/m /mm). = Standard deviation of the monthly energy production due to year-to-year variation (kWh). AOI = Angle of incidence. Figure 5 shows the results in terms of the air temperature and PV energy production, E (Table 2), for each month. The air T curve considers the daily thermal variation; Infrastructures 2022, 7, x FOR PEER REVIEW 10 of 14 thus, it would measure only the seasonal trend (it refers to mean values for a period of 2007–2016 [35]). Figure Figure 5. 5. Air Air te temperatur mperature curve and mean e curve and meanen ener ergy, E gy, E m, of , of PV PV histog histograms rams [35] (adapted [35] (adapted from fr [12]). om [12 ]). The results shown in Figure 2 should facilitate, in a parallel way, the design of PVPs with aeration systems to estimate a possible power value that optimizes the energy auto- consumption, improving future economic analyses for the investments of PVPs. The E histograms, shown in Figures 5 and 6, are proportional to the fluctuations of the air temperature during a season, where, as already mentioned, T is strongly correlated to the solar radiation curves in terms of amplitude and trend. Infrastructures 2022, 7, x FOR PEER REVIEW 11 of 14 The results shown in Figure 2 should facilitate, in a parallel way, the design of PVPs with aeration systems to estimate a possible power value that optimizes the energy auto- consumption, improving future economic analyses for the investments of PVPs. The Em histograms, shown in Figures 5 and 6, are proportional to the fluctuations of the air tem- perature during a season, where, as already mentioned, T is strongly correlated to the solar radiation curves in terms of amplitude and trend. By combining these Em histograms with the IpRO2 curves (see Figure 2), plotted in Infrastructures 2022, 7, 79 10 of 13 function of the months, new results are obtained, as shown in Figure 6. In this way, the idea to correlate PVs to WWTPs is more evident, i.e., PV Em histograms ↔ IpRO curves. Figure 6. PV energy Em and IpRO2 in WWTP for each aeration system. Figure 6. PV energy E and Ip in WWTP for each aeration system. RO2 By combining The five cu these E histograms rves in Figu with re 6 ind the iIp cate a r curves eduction in (see Figur the energy co e 2), plotted nsumption in in the m RO2 winter months and an increase in the summer months in the Mediterranean area (i.e., from function of the months, new results are obtained, as shown in Figure 6. In this way, the June to August). Thus, if the blower’s aeration system is known, it is possible to design an idea to correlate PVs to WWTPs is more evident, i.e., PV E histograms $ Ip curves. m RO easy way to power the peak of PVPs that maximizes the annual auto-consumption of the The five curves in Figure 6 indicate a reduction in the energy consumption in the oxidation tanks by using only the mean variation of the air temperature over a month. It winter months and an increase in the summer months in the Mediterranean area (i.e., from is also possible to see that the energy consumption curves of the different aerator systems June to August). Thus, if the blower ’s aeration system is known, it is possible to design an overlap in some points with a PV energy production of 1 kWp. These points indicate the easy way to power the peak of PVPs that maximizes the annual auto-consumption of the optimum performance of the PV system. oxidation tanks by using only the mean variation of the air temperature over a month. It is Therefore, when Em histograms of PV overlap the IpRo2 curves, the energy consump- also possible to see that the energy consumption curves of the different aerator systems tion is covered in an optimum way, for example, from March to August (see the green overlap in some points with a PV energy production of 1 kWp. These points indicate the area in Figure 6). For the other cases, the performance is considered good (September– optimum performance of the PV system. October) or poor (other months, not shown in Table 3). Finally, Table 3 shows the auto- Therefore, when E histograms of PV overlap the Ip curves, the energy consump- m Ro2 consumption for the five blower systems. tion is covered in an optimum way, for example, from March to August (see the green area in Figure 6). For the other cases, the performance is considered good (September–October) or poor (other months, not shown in Table 3). Finally, Table 3 shows the auto-consumption for the five blower systems. Table 3. Auto-consumption for each aeration system (from March to October). Auto-Consumption (%) for Aeration Systems Superficial Surface Turbines with Low-Speed Large Bubble Submerged Turbines Month Performance Brushes Downward Flow Surface Aerators Ventilation with Injector 3 (March) 100.0 98.0 96.0 94.0 99.0 4 100.0 100.0 100.0 99.0 100.0 5 100.0 100.0 100.0 100.0 100.0 Optimum 6 100.0 100.0 100.0 100.0 100.0 7 97.0 99.0 100.0 100.0 97.0 8 94.0 96.0 98.0 100.0 94.0 9 85.0 86.0 87.0 89.0 85.0 Good 10 (October) 83.0 83.0 83.0 84.0 83.0 Mean 87.0 87.0 87.0 86.0 87.0 - The mean is calculated for the whole year (from January to December). In Table 3, the mean auto-consumption in 1 year is86.0% for all systems, whereas the mean auto-consumption in the months ranges between 63.0% and 100.0%, with a spread of 8.0% (i.e., DIp = 18–10 = 8% in August up to 14% by considering other aeration systems RO2 as shown in [13]), which should cover a part of 30.0% mentioned in Section 2.1.1. Considering the energy production for PVs in a year, it is possible to conclude that in summer, spring, and in part of autumn (March to October), the mean auto-consumption Infrastructures 2022, 7, 79 11 of 13 oscillates between 83.0% and 100.0%, whereas the mean auto-consumption in winter (from November to February, not shown in Table 3) reduces and oscillates between 63.0% and 77.0%. 4. Conclusions This work presents a recent method proposed by authors to design PVs to optimize the energy auto-consumption of oxidation tanks in WWTPs. This method consists of providing, in a direct way, analytical equations to quantify the energy generation of PVs only using the air temperature, T, and the standard conditions of WWTPs. We conclude that: (1) If the air temperature curve increases, the energy consumption in oxidation blowers also increase. Therefore, the designing of PVs should be carried out without a punctual measurement of the energy consumption of the oxidation tanks; however, just considering chemical parameters, e.g., biochemical oxygen demand, BOD , volatile suspended solids, VSS, as there are easily recoverable in WWTPs. Thus, by considering the air temperature, the proposed equations should be excellent proxy functions for designing the necessary photovoltaic power and avoiding expensive energy and electric analyses in terms of time and analytical resolutions. (2) The overlap of the energy consumption curves of the system and photovoltaic production curves should make the calculation of the power sufficient to individuate the maximize the energy auto-consumption. In this sense, the proposed approach would sim- plify the energy consumption analyses since traditional measurements used for controlling need available data (which, in many cases, can be difficult to retrieve) on WWTPs. (3) The results show that the mean trend of Ip of the five aeration systems reaches RO2 a value of ~8.0% of the consumption of energy, with a temperature that varies between 20.0 and 25.0 C. The consumption curves regarding the “superficial brushes” aeration system represent the technologies’s more energy intensiveness. Author Contributions: Conceptualization, A.C.; methodology, A.C. and E.Z.; software, A.C.; validation, E.Z. and A.C.; formal analysis, A.C.; investigation, E.Z. and A.C.; data curation, A.C. and E.Z.; writing—original draft preparation, E.Z. and A.C.; writing—review and editing, E.Z. and A.C.; supervision, E.Z. and A.C. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. 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