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- Hindawi Publishing Corporation
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- Copyright © 2022 Junwen Che et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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- 10.1155/2022/6951040
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Abstract
Hindawi International Transactions on Electrical Energy Systems Volume 2022, Article ID 6951040, 8 pages https://doi.org/10.1155/2022/6951040 Research Article Optimal Pricing Model of Environmental Quality Index Futures from the Perspective of Green Finance 1 2 1 1 1 Junwen Che , Shenghe Zhou , Rui Shan , Hui Jia , and Zheng Liu Yantai Nanshan University, Longkou, Shandong 265713, China ShandongNanshan Aluminum Co, LTD., Longkou, Shandong 265713, China Correspondence should be addressed to Rui Shan; 3100502016@caa.edu.cn Received 14 July 2022; Revised 29 July 2022; Accepted 3 August 2022; Published 28 August 2022 Academic Editor: Nagamalai Vasimalai Copyright © 2022 Junwen Che et al. *is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In order to establish the optimal price of low-carbon products and set the optimal target carbon emissions in the production cycle so as to maximize profits, this paper proposes the optimal pricing model of environmental quality index futures from the perspective of green finance. *is paper mainly studies the optimal pricing and carbon emission strategy of low-carbon products of a single enterprise under the carbon trading system based on the quota system. When enterprises join the carbon trading system, how to optimally determine their target carbon emissions in the production cycle and the optimal price of their low- carbon products in order to maximize their own profits, based on the carbon emission quotas freely allocated by the government in the face of exogenous carbon trading prices and different consumer preferences for low-carbon products in the market, is discussed in detail. *e experimental results show that the low marginal cost of emission reduction will urge enterprises to implement low-emission strategies as much as possible, and the marginal cost of a specific size will enable enterprises to implement low-carbon policies with low emissions, and the optimal emissions will decline with the increase of carbon prices. However, from the perspective of 50–300 carbon trading prices, the profits generated are less than those of the minimum emission strategy, and the difference between the two is generally one order of magnitude. *erefore, if the internal conditions permit and the external carbon trading price is reasonable, enterprises should reduce carbon emissions as much as possible. *e properties obtained from the model analysis and the numerical conclusions given in the example part reflect the relationship between the enterprise product pricing, the marginal cost of emission reduction, and the target emission decision-making and draw some valuable information for the enterprise and the government decision-making. the EU Emission Rights Trading System have been gradually 1. Introduction established. Driven by the government’s policy of low- International carbon futures trading originated from the carbon economic transformation and the promotion of spot trading of carbon emission rights. In 2003, the Chicago relevant financial institutions, the carbon spot trading Climate Exchange (CCX) was established. Based on “quota market has developed rapidly, and the trading volume is and trade,” it became the world’s first legally binding rising day by day. greenhouse gas emission registration, voluntary emission In April 2005, the European Climate Exchange launched reduction, and trading platform based on international rules the first EU carbon emission quota (EUA) futures and [1, 2]. In 2005, the EU established the EU Emissions Trading operated on the electronic futures trading platform of the System (EUETS), which has become the largest total carbon London International Petroleum Exchange (IPE). *e emission control and trading system in the world. Since Chicago Climate Exchange, the European Climate Ex- then, the European Climate Exchange (ECX), the French change, and the European energy exchange (EEX) have electricity exchange, the BlueNext trading market, the Eu- successively launched certified emission reduction (CER) ropean energy exchange (EEX), the Italian electricity ex- futures contracts. Once the carbon futures contract was change (IPEX), and the UK emission rights exchange under launched, it was sought after by many investors, and the 2 International Transactions on Electrical Energy Systems established carbon emission allocation quota and cus- trading volume increased rapidly. At present, the main carbon futures products in the global carbon finance market tomers with different low-carbon preferences in the market so as to maximize profits. Enterprises need to include the European Climate Exchange carbon finance contract (ECXCFI), emission index futures (EUAFutures), balance the following issues: reducing emissions will gain certified emission reduction futures (CERFutures), and the carbon trading benefits and will positively affect the Chicago Climate Exchange carbon trading financial futures market demand for products due to better low-carbon (CCXCFIFutures) [3]. Figure 1 shows the organizational performance, but at this time, enterprises will bear higher structure of the green industry fund. emission reduction input costs. On the contrary, if the enterprise relaxes the control on emission reduction, the 2. Literature Review cost will be relatively reduced, but on the one hand, it may not get the carbon trading income. On the other hand, it In response to this research problem, Lee et al. took the will have an adverse impact on product sales due to poor carbon emission trading pilot as the background, considered environmental performance and a negative corporate that when there was dual pressure of emission reduction image [10]. In this paper, carbon emissions are directly policy and low-carbon demand, they introduced the manu- taken as decision variables. *e main reasons for this facturer’s carbon emission per unit product decision vari- assumption are (1) it can clearly reflect the relationship ables, and analyzed the manufacturer’s optimal pricing and between enterprise emissions, the trading market, the optimal emissions by constructing the manufacturer’s sim- carbon quota, and the government’s low-carbon policy; plified decision model [4]. Wu et al. studied the optimal (2) as an indicator or task, emissions have a very intuitive pricing and carbon emission strategy of low-carbon products guiding significance in the actual production process. We for a single enterprise under the carbon trading system based think this assumption is also reasonable from the per- on the quota system. In the carbon trading environment, the spective of enterprise production because carbon emis- government allocates a certain carbon emission quota to sions mainly come from energy consumption. Enterprises enterprises for free. Facing the carbon trading price given by can change the energy input structure or use efficiency to the carbon trading market and the different preferences of reduce carbon emissions under the condition of ensuring consumers on the low-carbon degree of products in the a certain output. For example, some agricultural product product market, it provides solutions on how to optimally production enterprises’ CDM projects change the power determine the target carbon emissions within the production access from thermal power to wind power or biogas power cycle of enterprises and the optimal price of low-carbon generation, which will not affect the final production. products produced so as to maximize their own profits [5]. Another example is the energy-saving projects related to CSS et al. pointed out in their research on the establishment of cement production. an emission rights market in China that carbon taxation, a Pigou mean, and carbon emission rights trading, a Coase mean, are based on internalizing the external effects of en- 3. Research Methods vironmental problems and combining policy intervention 3.1. Symbol Description. *e symbols used in this article are with market mechanisms to affect enterprises’ emission and explained one by one: pollution control behavior. However, carbon tax mostly relies on government intervention, while carbon emission rights p: Low carbon product market pricing, as a decision trading focuses on using market mechanisms to solve envi- variable; ronmental problems [6]. Pan et al. pointed out that the carbon e *e total carbon emission in the production cycle of tax is levied on the carbon content of energy consumption the enterprise, which is a decision variable; products, which is conducive to the realization of carbon D(p, e ): *e market demand of the final product, emission reduction. However, the carbon tax will have an c which is the function of the above two decision vari- impact on the competitiveness, distribution, and environ- ables, and the demand will decrease with the increase of ment of enterprises’ products, so some enterprises are re- price or carbon emission; luctant to adopt it [7]. Yu et al. found that if the marginal emission reduction cost (MAC) and marginal loss and other e : Minimum possible carbon emission, i.e., the min- cost and benefit functions of enterprises can be clearly de- imum emission that the enterprise can achieve within fined, carbon trading and carbon tax can achieve the optimal its production cycle with all efforts; goal of carbon emission reduction through appropriate e : Maximum carbon emission refers to the total pricing [8]. Yang et al. found that when other conditions carbon emission generated during the production cycle remain unchanged, the optimal environmental economic of an enterprise without any emission reduction means can be selected by comparing the size of the marginal technology; management cost and marginal transaction cost. When the p : *e market price of general products, an exogenous degree of marketization is low, the carbon tax means are more variable, is the market-accepted price of similar but appropriate [9]. nonlow-carbon products; *e problem we need to solve is how to set the optimal c : Marginal production cost without emission re- low-carbon product price and set the optimal target 0 duction technology input; carbon emissions in the production cycle in the face of the International Transactions on Electrical Energy Systems 3 CCB International Item A Joint Administration investment contribution CCB urban investment Green environmental Item B environmental protection Equity protection Investment Management industry fund Co., Ltd. (fund manager) Urban Investment Other items Figure 1: Organizational structure of the green industry fund. c (e ): Low carbon input cost, set as the convex in- (2) Considering the government subsidy to the market d c creasing function of the enterprise’s target carbon rather than the low-carbon subsidy to enterprises emissions; because the government policy orientation in this paper focuses on the market rather than adminis- β: Emission reduction coefficient; trative means, and a corresponding part of the profits e: *e carbon emission limit for specific enterprises of enterprises will come from carbon trading rather shall be allocated by the government free of charge; than the subsidy amount. ε: Carbon trading price; *e subsidy to the market is to stimulate consumption δ: Low carbon preference of consumers; and improve citizens’ awareness of environmental protection t: Government subsidy coefficient for low-carbon [11]. products; M: *e total market capacity of the same type of low- carbon products and general products of the enterprise. 3.3. Product Demand. Suppose that consumers’ cognition of low-carbon products (or environmental satisfaction) in the market obeys the uniform distribution on [δ, δ]. δ means 3.2. Enterprise Decision. After the carbon emission quota is that for consumers who will buy any low-carbon products, δ known, the enterprise must make the optimal target carbon is a customer who has no low-carbon awareness and is only emission and product pricing decisions before the start of its willing to buy general products. Set the government subsidy production cycle to maximize its profits after the production amount for consumers to purchase low-carbon products as cycle. *e objective function is as follows: t(e − e ), which indicates that the low-carbon degree is m c based on the maximum carbon emission of enterprises. *e maxΠ � D p, e p − c − c e + ε e − e , c 0 d c c p,e government can adjust the subsidy coefficient t to change the (1) subsidy amount, which is an exogenous variable [12, 13]. s.L. e ≤ e ≤ e , l c m Here, for the convenience of analysis, we assume that where if e − e is positive, it means that the enterprise can consumers’ information on the carbon emissions of enter- sell the carbon quota, and if it is negative, it means that the prises is complete. At the same time, in practice, e and e m c enterprise should purchase the quota from the outside; c are generally large, so t should be a small number in reality. will use the classic AJ model for reference and set the For consumers, whether they buy low-carbon products of emission reduction cost as the quadratic form the enterprise depends on whether their consumption utility c � β(e − e ) . Compared with previous models, the is less than that of purchasing similar to nonlow-carbon d m c differences and innovations of this paper are as follows: products. Considering such marginal customers, their low- carbon awareness is δ, and they hold an “indifferent” attitude (1) *e construction of this model takes carbon emis- towards whether to buy low-carbon products, that is, for sions as the cornerstone and adds the positive and them, the utility of buying two types of products is the same, negative benefits generated by the carbon trading i.e., p − p � k(δ − δ) + t(e − e ), where k is a normal 0 m c process to the profits; 4 International Transactions on Electrical Energy Systems number, indicating the utility coefficient of consumers’ low- Conclusion 1. *e higher the government subsidy, the carbon awareness. higher the product pricing of enterprises. *is can be directly *e following equation is obtained: observed from equation (5). *erefore, government sub- sidies to consumers can indirectly help enterprises that p − p − t e − e + k δ 0 m c (2) implement low-carbon production to make profits. δ � . Conclusion 2. Under the same target emission level, the Meanwhile, the market demand for such low-carbon greater the maximum carbon emissions of enterprises, the products is as follows: higher the product price. Obviously, the larger e shows the 1 t e − e + p − p characteristics of higher energy consumption in the industry m c 0 ⎝ ⎠ ⎛ ⎞ D p, e � M dx � M 1 + . [14]. *e difference between e and EC essentially reflects the δ δ − δ kδ − δ efforts of enterprises to reduce emissions. (3) Conclusion 3. *e higher the target carbon emissions, the lower the product price. From equation (5), it can be seen that without considering the emission reduction cost and 3.4. Optimal Pricing. Considering that the enterprise makes other factors, the increase in carbon emissions will affect the pricing decision first, for a given EC, there is the fol- consumers’ preference for environmental protection prod- lowing formula: ucts through e − e [15]. When the emissions increase, some p + t e − e − p customers with strong environmental awareness will not 0 m c ⎛ ⎝ ⎞ ⎠ maxΠ � M 1 + (p − c) choose such products, and the market demand will decline. kδ − δ (4) At this time, enterprises will have to reduce the product price. − β e − e + ε e − e . m c c Conclusion 4. *e stronger the consumers’ awareness of *e optimal solution obtained from formula (4) F.O.C is low-carbon δ, the higher the price of low-carbon products. as follows: *is conclusion is not only tenable in the model but also logical in practice because the improvement of low-carbon (5) p � c + p + t e − e + kδ − δ. awareness will bring more sales. 0 m c *e following conclusions can be drawn: 3.5. Optimal Carbon Emissions. Substitute (5) into (4) to obtain p + t e − e − 1/2c + p + t e − e + kδ − δ 0 m c 0 m c ⎝ ⎠ ⎛ ⎞ max Π � M 1 + 0⩽e ⩽e c m kδ − δ c + p + t e − e + kδ − δ − c − β e − e 2 + ε e − e 0 m c m c c (6) Formula (6) Mc − p + te − te − hδ + h δ 2 0 c m max Π& � ε e − e − β e − e + . c m c 0⩽e ⩽e c m 4k δ − δ Find the second derivative of e for (6) and obtain the cases according to the marginal cost of emission reduction of following equation: different sizes. 2 2 z Π Mt � − 2β. (7) Case 1. β � Mt /4k(δ − δ) ze 2kδ − δ At this time, the profit function has a linear relationship When looking for the optimal carbon emission e , we with the decision variable e . *e following properties can be c c take Mt /4k(δ − δ) as the threshold and discuss it in three obtained: International Transactions on Electrical Energy Systems 5 Property 1. When β � Mt /4k(δ − δ), the lowest emission 180000 will be the best choice for the enterprise. 3.5.1. Nature 1: Certification. Finding the first-order partial derivative of e for π yields zΠ/ze � Mt((c − p ) − k c e c 0 (δ − δ))/2k(δ − δ) − ε⩽0, (6) is a monotonic nonincreasing function of e . Obviously, when e � e , the profit reaches the c c l maximum. *e certificate is completed. *e following conclusions are drawn: Conclusion 5. When the marginal cost of enterprise emis- sion reduction is equal to a certain value, the larger the carbon emission, the smaller the profit. Property 1 illustrates 0 50 100 150 200 250 this problem, and at this time, the enterprise should reduce emissions as much as possible [16]. The impact of targeted emissions on profits 4. Result Analysis Figure 2: ε � 50, e � 200, e ∈ [0, 250]. *e established model and its related properties and con- clusions are analyzed with examples. For different marginal costs and carbon prices, we discuss the optimal decision under specific examples according to the basic properties of the objective function. *e specific values are set as follows: M � 500, e � 250, e � 100, t � 0.2, k � 0.1, δ � 10, m l . (8) δ � 0, c � 10p � 20, ε � 50, e � 200 100000 4.1. Linear Objective Function. At this time, β � Mt /4k(δ − δ) and zΠ/ze � Mt((c − p ) − k(δ − δ))/2k(δ − δ) − ε≤ 0 c 0 are used to analyze the impact of target emissions on profits, as shown in Figures 2 and 3. As can be seen from Figure 2, when the target emissions 0 50 100 150 200 250 300 increase, the profits decrease rapidly. It is obvious from Figure 3 that the increase in carbon trading prices will improve the overall profit level. Figure 4 analyzes the sen- e 100" sitivity of profit to the carbon price. As stated in conclusion e 120" 6, higher prices will increase the absolute value of the slope of e 150" profits to emissions, that is, when the carbon price is higher, Figure 3: ε ∈ [0, 300], e � 200, e � 100. the profits of enterprises will decline faster with the increase of emissions. At this time, if enterprises loosen the control of the marginal cost of emission reduction on the optimal emissions, on the one hand, they will encounter lower carbon emission, and Figure 6 is obtained. *e results show market demand; on the other hand, they will bear the op- that when the marginal cost of emission reduction increases, portunity cost of carbon trading [17]. the decision-maker will increase the target carbon emissions, and the graph is concave to β and takes the maximum 4.2. Nonlinear Objective Function. Combining the carbon emission of 250 as the limit value. *is shows that the price and the marginal cost of emission reduction, we an- positive impact of the marginal cost of emission reduction alyze it based on inference 4. on carbon emissions is limited by the capacity of enterprises. Known by Figure 6 analyzes the impact of the corresponding op- when Mt /4k(δ − δ) � 5< β⩽kMt(δ − δ) +2kε(δ − δ) timal emissions on profits when β∈ [6.3, 20]. Compared −Mt(te − te − p + c)/4k(e − e )(δ − δ) � 6.26, the with Figure 4, it is found that when the emission reduction l m 0 m l change of profit to marginal cost is analyzed in Figure 5. It is cost is large, the overall profit level decreases significantly, found that when other conditions remain unchanged, the and the impact of cost on profit is also different. *e former profit will rapidly decline with the increase of emission is linear in a limited range, whereas the latter is nonlinear, reduction marginal cost. and its influence degree varies from large to small [18]. When β≥ kMt(δ − δ) + 2kε(δ − δ) − Mt(te − te − Figure 7 analyzes the sensitivity of profit to carbon price l m p + c)/4k(e − e )(δ − δ) � 6.26, we analyze the impact of under the concave function (β � 6.3 ). From the change 0 m l Profit Profit 6 International Transactions on Electrical Energy Systems 0 50 100 150 200 250 6 8 10121416182022 c m 50 e =250 Figure 6: β ∈ [6.3, 20]. Figure 4: ε � 50, 100, 150, e ∈ [0, 250]. 0 50 100 150 200 250 300 350 400 5.0 5.2 5.4 5.6 5.8 6.0 6.2 6.4 e 0 400 Change in profit versus marginal cost 200 600 Figure 5: e � 0, β ∈ [5, 6.3]. Figure 7: e � [0, 400], ε � 0, 200, 400, 600. external carbon trading price is reasonable, the enterprise track of the stable point, a higher carbon price will enable should reduce carbon emissions as much as possible [22]. enterprises to obtain the global optimal profit with less emissions. At the same time, if enterprises expand emissions, their profits will decline faster [19, 20]. When e � 200, the c 5. Conclusion enterprise profits under the four carbon prices are the same, and beyond this point, the enterprise profits under the *is paper discusses how enterprises make the optimal price higher carbon prices will be lower [21]. of low-carbon products and emission reduction strategies *e low marginal cost of emission reduction will urge under the carbon trading system. enterprises to implement low emission strategies as much as In terms of carbon emission decision-making, we first possible. *e marginal cost of a specific size will enable analyze different decisions based on linear, concave, and enterprises to implement low-carbon policies with low convex objective functions according to the size of enterprise emissions, and the optimal emissions will decline with the marginal cost and obtain some valuable information com- increase in carbon prices. However, from the perspective of bined with numerical examples. For example, when there is a 50–300 carbon trading prices, the profits generated are less linear relationship between corporate profits and carbon than those of the minimum emission strategy, and the emissions, profits will decrease with the increase of carbon difference between the two is generally one order of mag- emissions, and this trend will intensify with the rise in the nitude. *erefore, if the internal conditions permit and the carbon trading prices. Under the nonlinear function, when Profit Profit Profit Optimal emission International Transactions on Electrical Energy Systems 7 the price of carbon trading market rises, the larger marginal References cost of emission reduction will lead to lower optimal target [1] M. Song, X. Zhao, Y. Shang, and B. Chen, “Realization of emissions. When the marginal cost of emission reduction is green transition based on the anti-driving mechanism: an within a certain range, enterprises will try their best to re- analysis of environmental regulation from the perspective of duce carbon emissions. In addition, when the carbon price is resource dependence in China,” 3e Science of the Total higher, lower carbon emissions will enable enterprises to Environment, vol. 698, no. Jan.1, pp. 134317.1–134317.12, obtain higher profits, and at this time, the opportunity cost of increasing emissions will be greater. In general, the overall [2] X. Zhou, X. Tang, and R. Zhang, “Impact of green finance on profit level of a convex function (lower marginal cost of economic development and environmental quality: a study emission reduction) is larger than that of a concave function. based on provincial panel data from China,” Environmental Based on the above discussion, we further analyzed the Science and Pollution Research, vol. 27, no. 16, 2020. [3] A. Shokri and G. Li, “Green implementation of lean six sigma carbon trading price and obtained some valuable infor- projects in the manufacturing sector,” International Journal of mation for enterprises and government decision-making. Lean Six Sigma, vol. 11, no. 4, pp. 711–729, 2020. For example, for enterprises, if their marginal cost of [4] J. H. Lee and K. S. Im, “Effect of in-situ silicon carbon nitride emission reduction is low in the carbon trading environ- (sicn) cap layer on performances of algan/gan mishfets,” IEEE ment, they should try to reduce their carbon emissions in the Journal of the Electron Devices Society, vol. 9, no. 99, production cycle. In particular, when the carbon price rises, pp. 728–734, 2021. emission reduction becomes a top priority for enterprises [5] S. Wu and Z. Huang, “Coordination of an environmentally because there will be a large profit space in the trading responsible supply chain with cost disturbance under carbon market at this time. As far as the government is concerned, it price fluctuations,” Mathematical Problems in Engineering, should try to increase the carbon price if its capacity permits, vol. 2020, no. 3, pp. 1–17, 2020. such as through administrative intervention, so as to [6] A. Css, A. Rddo, B. Lfqpm, and A. Cap, “Electrodeposited stimulate the enthusiasm of enterprises to voluntarily reduce cobalt hydroxide in expanded carbon graphite electrode obtained from exhausted batteries applied as energy storage emissions. If the local government does not have the ability device - sciencedirect,” Arabian Journal of Chemistry, vol. 13, to affect the carbon price, it should appropriately adjust the no. 1, pp. 3448–3459, 2020. subsidies for low-carbon products to indirectly change the [7] J. Pan, W. Zhong, Z. Gao et al., “N, S-doped silicon oxy- cost structure of enterprises and encourage enterprises to carbide-drived carbon/amorphous ball-flower-like NiO as implement emission reduction. high performance electrode in asymmetric supercapacitors,” *e limitation of this paper is that carbon emissions can Ceramics International, vol. 47, no. 19, pp. 27833–27842, 2021. indeed be measured, and the production environment in- [8] H. Yu, S. Bai, and D. Chen, An Optimal Control Model of the dicators of consumers and enterprises can also be obtained Low-Carbon Supply Chain: Joint Emission Reduction, Pricing through some of the ways described in this paper, but the Strategies and New Coordination Contract Design, IEEE Ac- marginal price of consumers’ willingness to pay for low- cess, no. 99, p. 1, NJ, USA, 2020. carbon products is a difficult value to measure. *e value of [9] Y. Yang, M. Zhao, Z. Cao, Z. Ge, Y. Ma, and Y. Chen, “Low- different consumers is different and should change over cost and scalable carbon bread used as an efficient solar steam time, but the description of low-carbon awareness in this generator with high performance for water desalination and purification,” RSC Advances, vol. 11, no. 15, pp. 8674–8681, paper is more abstract. Second, this paper assumes that the carbon emission quota for a certain enterprise is an exog- [10] S. Xia, F. Lin, Z. Chen, C. Tang, Y. Ma, and X. Yu, “A bayesian enous variable, but in practice, if the enterprise or group is game based vehicle-to-vehicle electricity trading scheme for large, its industrial energy consumption level will affect the blockchain-enabled internet of vehicles,” IEEE Transactions government’s formulation of carbon trading quota. on Vehicular Technology, vol. 69, no. 7, pp. 6856–6868, 2020. [11] X. Ji, Z. Yin, Y. Zhang, H. Gao, X. Zhang, and X. Zhang, Data Availability “Comprehensive pricing scheme of the ev charging station considering consumer differences based on integrated ahp/ *e data used to support the findings of this study are dea methodology,” Mathematical Problems in Engineering, available from the corresponding author upon request. vol. 2020, no. 3, pp. 1–11, 2020. [12] Y. Tao, J. Qiu, S. Lai, J. Zhao, and Y. Xue, “Carbon-oriented electricity network planning and transformation,” IEEE Conflicts of Interest Transactions on Power Systems, vol. 36, no. 2, pp. 1034–1048, *e authors declare that they have no conflicts of interest. [13] A. Yl, W. A. Hui, B. Dc, G. B. Lin, W. C. Xin, and J. A. Xian, “Achieving thermally stable and anti-hydrolytic sr2si5n8: Acknowledgments eu2+ phosphor via a nanoscale carbon deposition strategy - sciencedirect,” Ceramics International, vol. 47, no. 3, *is study is funded by *e Youth Fund Project of Yantai pp. 3244–3251, 2021. Nanshan University (Humanities and Social Sciences) in [14] W. Liu, X. Wu, X. Du, G. Xu, and S. Wang, Tension Networked 2021 (Humanities and Social Sciences) and Practical re- Control Strategy for Carbon Fiber Multilayer Diagonal Loom, search on Transformation and Innovation of Cultural In- IEEE Access, no. 99, p. 1, NJ, USA, 2020. dustry with Digital Empowerment of Shandong Province [15] X. Xu, Q. Yang, L. Fang, Y. Du, and Y. Fu, “Anion-cation dual (Project number: 2021QSK05). doping: an effective electronic modulation strategy of ni_2p 8 International Transactions on Electrical Energy Systems for high-performance oxygen evolution,” Journal of Energy Chemistry, vol. 48, no. 09, pp. 132–137, 2020. [16] R. Huang and X. Yang, “Analysis and research hotspots of ceramic materials in textile application,” Journal of Ceramic Processing Research, vol. 23, no. 3, pp. 312–319, 2022. [17] V. Babin, A. Talbot, A. Labiche et al., “Photochemical strategy for carbon isotope exchange with CO ,” ACS Catalysis, vol. 11, no. 5, pp. 2968–2976, 2021. [18] R. Kumar and A. Sharma, “Risk-energy aware service level agreement assessment for computing quickest path in com- puter networks,” International Journal of Reliability and Safety, vol. 13, no. 1/2, p. 96, 2019. [19] P. Ajay, B. Nagaraj, B. M. Pillai, J. Suthakorn, and M. Bradha, “Intelligent ecofriendly transport management system based on iot in urban areas,” Environment, Development and Sus- tainability, vol. 3, pp. 1–8, 2022. [20] J. Chen, J. Liu, X. Liu, X. Xu, and F. Zhong, “Decomposition of toluene with a combined plasma photolysis (CPP) reactor: influence of UV irradiation and byproduct analysis,” Plasma Chemistry and Plasma Processing, vol. 41, no. 1, pp. 409–420, [21] Z. Huang and S. Li, “Reactivation of learned reward associ- ation reduces retroactive interference from new reward learning,” Journal of Experimental Psychology: Learning Memory and Cognition, vol. 48, no. 2, pp. 213–225, 2022. [22] Q. Liu, W. Zhang, M. W. Bhatt, and A. Kumar, “Seismic nonlinear vibration control algorithm for high-rise build- ings,” Nonlinear Engineering, vol. 10, no. 1, pp. 574–582, 2021.
Journal
International Transactions on Electrical Energy Systems – Hindawi Publishing Corporation
Published: Aug 28, 2022