Research on deep peaking cost allocation mechanism considering peaking demand subject and thermal power unit
The current peak-shaving auxiliary service cost allocation mechanism balances the revenue and expenditure of the power plant side, the peak-valley difference of the power grid is mainly caused by the peak-valley characteristics of the load and renewable energy. It is not reasonable that not reasonab...
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Published in | Energy reports Vol. 12; pp. 158 - 172 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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Elsevier Ltd
01.12.2024
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ISSN | 2352-4847 2352-4847 |
DOI | 10.1016/j.egyr.2024.06.011 |
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Abstract | The current peak-shaving auxiliary service cost allocation mechanism balances the revenue and expenditure of the power plant side, the peak-valley difference of the power grid is mainly caused by the peak-valley characteristics of the load and renewable energy. It is not reasonable that not reasonable the peak-shaving cost allocation mechanism does not consider user allocation. Therefore, this paper establishes a peak-shaving cost allocation mechanism that considers the peak-shaving demand subject, this article incorporates renewable energy power plants and loads into the peak-shaving demand subject. Firstly, this paper constructs an alternative scenario without peak-shaving demand through the mean line of load and available energy output and establishes an optimal scheduling model with deep peak-shaving and pumped storage power stations, this article takes the difference of system peak-shaving cost between two scenarios with and without peak-shaving demand as the marginal peak-shaving cost. Then, the Shapley value method in cooperative game is used to establish the peak-shaving cost allocation mechanism considering the main body of peak-shaving demand. In addition, It is used that the equal-kWh following load method constructed the equivalent output curve of renewable energy, following load method improves the existing allocation mechanism by comprehensive similarity. Finally, this paper analyzes and compares three different peaking cost allocation mechanisms. The example analysis shows that the peaking cost allocation mechanism considering peaking demand subjects. The example can reflect the peaking cost caused by different subjects and reduce the peaking pressure of thermal power units.
•Proposes a model for including peaking demand subjects in cost sharing.•Develops scenarios for calculating peaking costs via Shapley values.•Enhances fairness in cost allocation with equivalent output curves.•Analyzes the effectiveness of three peaking cost allocation methods.•Validates benefits through comparative simulations. |
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AbstractList | The current peak-shaving auxiliary service cost allocation mechanism balances the revenue and expenditure of the power plant side, the peak-valley difference of the power grid is mainly caused by the peak-valley characteristics of the load and renewable energy. It is not reasonable that not reasonable the peak-shaving cost allocation mechanism does not consider user allocation. Therefore, this paper establishes a peak-shaving cost allocation mechanism that considers the peak-shaving demand subject, this article incorporates renewable energy power plants and loads into the peak-shaving demand subject. Firstly, this paper constructs an alternative scenario without peak-shaving demand through the mean line of load and available energy output and establishes an optimal scheduling model with deep peak-shaving and pumped storage power stations, this article takes the difference of system peak-shaving cost between two scenarios with and without peak-shaving demand as the marginal peak-shaving cost. Then, the Shapley value method in cooperative game is used to establish the peak-shaving cost allocation mechanism considering the main body of peak-shaving demand. In addition, It is used that the equal-kWh following load method constructed the equivalent output curve of renewable energy, following load method improves the existing allocation mechanism by comprehensive similarity. Finally, this paper analyzes and compares three different peaking cost allocation mechanisms. The example analysis shows that the peaking cost allocation mechanism considering peaking demand subjects. The example can reflect the peaking cost caused by different subjects and reduce the peaking pressure of thermal power units.
•Proposes a model for including peaking demand subjects in cost sharing.•Develops scenarios for calculating peaking costs via Shapley values.•Enhances fairness in cost allocation with equivalent output curves.•Analyzes the effectiveness of three peaking cost allocation methods.•Validates benefits through comparative simulations. |
Author | Han, Peitong Zhang, Hong Jin, Peihua Pang, Wei |
Author_xml | – sequence: 1 givenname: Hong surname: Zhang fullname: Zhang, Hong email: zhanghong@ccit.edu.cn organization: School of Electrical Engineering, Changchun Institute of Technology, Changchun, Jilin 130012, China – sequence: 2 givenname: Peihua surname: Jin fullname: Jin, Peihua organization: School of Electrical Engineering, Changchun Institute of Technology, Changchun, Jilin 130012, China – sequence: 3 givenname: Wei surname: Pang fullname: Pang, Wei organization: School of Electrical Engineering, Changchun Institute of Technology, Changchun, Jilin 130012, China – sequence: 4 givenname: Peitong surname: Han fullname: Han, Peitong organization: College of Biological and Agricultural Engineering, Jilin University, Changchun, Jilin 130012, China |
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Cites_doi | 10.3390/su142416337 10.1016/j.energy.2021.122960 10.1007/s10115-022-01776-4 10.1016/j.rser.2022.112279 10.1016/j.enconman.2022.115811 10.1109/TIE.2018.2840498 10.1109/TSTE.2021.3090463 10.1109/TSTE.2021.3105529 10.1016/j.rser.2015.10.052 10.1016/j.energy.2023.127386 10.1088/1748-9326/aca9e6 10.3390/en12173314 10.1016/j.ijhydene.2019.06.035 10.1504/IJBIC.2023.133505 10.1016/j.egyr.2021.05.042 10.1016/j.apenergy.2017.08.008 10.1016/j.apenergy.2022.120540 10.1109/ACCESS.2020.2974050 10.1007/s41066-022-00318-1 10.1016/j.jclepro.2020.122859 10.1109/TPWRS.2017.2690404 10.3390/en15134588 10.1109/ACCESS.2020.2983183 10.1007/s10586-016-0718-y 10.1016/j.eneco.2023.107011 10.1016/j.apenergy.2022.120131 10.1016/j.cnsns.2019.104867 10.1016/j.apenergy.2023.121637 10.1109/TIA.2022.3208866 10.1109/TPWRS.2017.2732921 |
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Keywords | Shapley allocation method Cost allocation Renewable energy generation Peak-load regulation Equal-kWh following load |
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References | U.S. Energy Information Administration, “Construction cost data for electric generators installed in 2021,” 2023. [Online]. Available: https://www.eia.gov/electricity/generatorcosts/. Cui, Andriamahery, Ao (bib29) 2022; 14 Energy Research Institute, China’s Electrification Pathways: Findings from the China Energy Outlook 2022, Beijing, China, November, 2022. [Online]. Available:https://www.efchina.org/Attachments/Report/report-lceg-20221104/On-the-Road-to-Carbon-Neutrality-Green-Investment-Needs-in-China.pdf. Verma, Mittal (bib34) 2023; 8 Efkarpidis, Imoscopi, Geidl (bib15) 2023; 34 Yang, Cao, Cai (bib20) 2020; 8 Rahman, Aziz, Deeba (bib2) 2021; 7 Rahman, Farrok, Haque (bib1) 2022; 161 Li, Feng, Li (bib4) 2018; 210 Chakraborty, Baeyens, Khargonekar (bib10) 2017; 33 Ye, Li, Pei (bib39) 2022; 327 Kang, Ye, Lam (bib14) 2023; 349 Yang, Wang, Gao (bib16) 2022; 15 Yang, Yibo, Chuang (bib25) 2023; 11 Li, Bu, Li (bib32) 2023; 333 Gangopadhyay, Seshadri, Toumi (bib31) 2023; 18 Li, Wang, Yang (bib5) 2022; 13 Tian, Xie, Hu (bib21) 2019; 12 Mays (bib24) 2017; 33 Li, Yang, Li (bib9) 2019; 66 Wen, Duan, Jiang (bib36) 2019; 78 Kou, Wu, Zhang, Ji, Ke, Wan, Liu, Li, Yuan (bib8) 2023; 22 National Energy Administration, “Management of Electricity Auxiliary Services”,2021-12-21, [Online]. Available: http://zfxxgk.nea.gov.cn/2021-12/21/c_1310391161.htm. Wu, Li, Zhao (bib38) 2022; 242 Hogan (bib23) 2017; 2008 Wang, Mao (bib37) 2018; 35 Liu, Zhai, Hu (bib6) 2023; 276 Zhang, Yan, Yuan (bib18) 2020; 275 Peng, Gao, Hu (bib28) 2020; 8 Jiang, Deng, You (bib33) 2019; 44 Gu, Xu, Chen (bib17) 2016; 54 Ma, Yan, Li (bib19) 2019; 5 Wahbah, Mohandes, EL-Fouly (bib7) 2022; 266 Dong, Xue, Li (bib26) 2017; 20 Kirişci (bib35) 2023; 65 Li, Han, Yang (bib13) 2021; 12 Wu, Zhu, Chen (bib27) 2022; 59 Wang, Zhou, Qin (bib30) 2023 Newbery (bib3) 2023; 126 Mays (10.1016/j.egyr.2024.06.011_bib24) 2017; 33 10.1016/j.egyr.2024.06.011_bib22 Kirişci (10.1016/j.egyr.2024.06.011_bib35) 2023; 65 Newbery (10.1016/j.egyr.2024.06.011_bib3) 2023; 126 Peng (10.1016/j.egyr.2024.06.011_bib28) 2020; 8 Kang (10.1016/j.egyr.2024.06.011_bib14) 2023; 349 Liu (10.1016/j.egyr.2024.06.011_bib6) 2023; 276 Gu (10.1016/j.egyr.2024.06.011_bib17) 2016; 54 Tian (10.1016/j.egyr.2024.06.011_bib21) 2019; 12 Yang (10.1016/j.egyr.2024.06.011_bib25) 2023; 11 Efkarpidis (10.1016/j.egyr.2024.06.011_bib15) 2023; 34 Zhang (10.1016/j.egyr.2024.06.011_bib18) 2020; 275 Dong (10.1016/j.egyr.2024.06.011_bib26) 2017; 20 Cui (10.1016/j.egyr.2024.06.011_bib29) 2022; 14 Wang (10.1016/j.egyr.2024.06.011_bib37) 2018; 35 Ma (10.1016/j.egyr.2024.06.011_bib19) 2019; 5 Wen (10.1016/j.egyr.2024.06.011_bib36) 2019; 78 Kou (10.1016/j.egyr.2024.06.011_bib8) 2023; 22 Wang (10.1016/j.egyr.2024.06.011_bib30) 2023 10.1016/j.egyr.2024.06.011_bib12 Rahman (10.1016/j.egyr.2024.06.011_bib1) 2022; 161 Wahbah (10.1016/j.egyr.2024.06.011_bib7) 2022; 266 Yang (10.1016/j.egyr.2024.06.011_bib16) 2022; 15 Li (10.1016/j.egyr.2024.06.011_bib4) 2018; 210 Jiang (10.1016/j.egyr.2024.06.011_bib33) 2019; 44 Chakraborty (10.1016/j.egyr.2024.06.011_bib10) 2017; 33 10.1016/j.egyr.2024.06.011_bib11 Hogan (10.1016/j.egyr.2024.06.011_bib23) 2017; 2008 Rahman (10.1016/j.egyr.2024.06.011_bib2) 2021; 7 Li (10.1016/j.egyr.2024.06.011_bib9) 2019; 66 Ye (10.1016/j.egyr.2024.06.011_bib39) 2022; 327 Wu (10.1016/j.egyr.2024.06.011_bib27) 2022; 59 Wu (10.1016/j.egyr.2024.06.011_bib38) 2022; 242 Li (10.1016/j.egyr.2024.06.011_bib5) 2022; 13 Li (10.1016/j.egyr.2024.06.011_bib13) 2021; 12 Gangopadhyay (10.1016/j.egyr.2024.06.011_bib31) 2023; 18 Li (10.1016/j.egyr.2024.06.011_bib32) 2023; 333 Yang (10.1016/j.egyr.2024.06.011_bib20) 2020; 8 Verma (10.1016/j.egyr.2024.06.011_bib34) 2023; 8 |
References_xml | – volume: 161 year: 2022 ident: bib1 article-title: Environmental impact of renewable energy source based electrical power plants: Solar, wind, hydroelectric, biomass, geothermal, tidal, ocean, and osmotic publication-title: Renew. Sustain. Energy Rev. – volume: 210 start-page: 1073 year: 2018 end-page: 1081 ident: bib4 article-title: Optimal distributed generation planning in active distribution networks considering integration of energy storage publication-title: Appl. Energy – volume: 13 start-page: 159 year: 2022 end-page: 169 ident: bib5 article-title: Optimal scheduling of isolated microgrids using automated reinforcement learning-based multi-period forecasting publication-title: IEEE Trans. Sustain. Energy – reference: Energy Research Institute, China’s Electrification Pathways: Findings from the China Energy Outlook 2022, Beijing, China, November, 2022. [Online]. Available:https://www.efchina.org/Attachments/Report/report-lceg-20221104/On-the-Road-to-Carbon-Neutrality-Green-Investment-Needs-in-China.pdf. – reference: National Energy Administration, “Management of Electricity Auxiliary Services”,2021-12-21, [Online]. Available: http://zfxxgk.nea.gov.cn/2021-12/21/c_1310391161.htm. – volume: 242 year: 2022 ident: bib38 article-title: Usage of correlation analysis and hypothesis test in optimizing the gated recurrent unit network for wind speed forecasting publication-title: Energy – volume: 349 year: 2023 ident: bib14 article-title: Sustainable electric vehicle charging coordination: balancing CO2 emission reduction and peak power demand shaving publication-title: Appl. Energy – volume: 65 start-page: 855 year: 2023 end-page: 868 ident: bib35 article-title: New cosine similarity and distance measures for Fermatean fuzzy sets and TOPSIS approach publication-title: Knowl. Inf. Syst. – volume: 15 start-page: 4588 year: 2022 ident: bib16 article-title: Peak shaving analysis of power demand response with dual uncertainty of unit and demand-side resources under carbon neutral target publication-title: Energies – volume: 275 year: 2020 ident: bib18 article-title: A realistic pathway for coal-fired power in China from 2020 to 2030 publication-title: J. Clean. Prod. – volume: 54 start-page: 723 year: 2016 end-page: 731 ident: bib17 article-title: Overall review of peak shaving for coal-fired power units in China publication-title: Renew. Sustain. Energy Rev. – volume: 327 year: 2022 ident: bib39 article-title: A novel integrated method for short-term wind power forecasting based on fluctuation clustering and history matching publication-title: Appl. Energy – volume: 22 start-page: 53 year: 2023 end-page: 64 ident: bib8 article-title: Image encryption for Offshore wind power based on 2D-LCLM and Zhou Yi Eight trigrams publication-title: Int. J. Bio-Inspired Comput. – volume: 18 year: 2023 ident: bib31 article-title: Beneficial role of diurnal smoothing for grid integration of wind power publication-title: Environ. Res. Lett. – volume: 126 year: 2023 ident: bib3 article-title: High renewable electricity penetration: Marginal curtailment and market failure under “subsidy-free” entry publication-title: Energy Econ. – volume: 8 start-page: 33151 year: 2020 end-page: 33162 ident: bib28 article-title: Bilateral coordinated dispatch of multiple stakeholders in deep peak regulation publication-title: IEEE Access – year: 2023 ident: bib30 article-title: Coordinated power smoothing control strategy of multi-wind turbines and energy storage systems in wind farm based on madrl publication-title: IEEE Trans. Sustain. Energy – volume: 44 start-page: 19658 year: 2019 end-page: 19666 ident: bib33 article-title: Size optimization and economic analysis of a coupled wind-hydrogen system with curtailment decisions publication-title: Int. J. Hydrogen Energy – volume: 14 start-page: 16337 year: 2022 ident: bib29 article-title: Analysis of optimal operation of multi-energy alliance based on multi-scale dynamic cost equilibrium allocation publication-title: Sustainability – reference: U.S. Energy Information Administration, “Construction cost data for electric generators installed in 2021,” 2023. [Online]. Available: https://www.eia.gov/electricity/generatorcosts/. – volume: 20 start-page: 391 year: 2017 end-page: 400 ident: bib26 article-title: Research on peak shaving costs and allocation of wind power integration using scalable computing method publication-title: Clust. Comput. – volume: 333 year: 2023 ident: bib32 article-title: Optimal scheduling of island integrated energy systems considering multi-uncertainties and hydrothermal simultaneous transmission: A deep reinforcement learning approach publication-title: Appl. Energy – volume: 266 year: 2022 ident: bib7 article-title: Unbiased cross-validation kernel density estimation for wind and PV probabilistic modelling publication-title: Energy Convers. Manag. – volume: 66 start-page: 1565 year: 2019 end-page: 1575 ident: bib9 article-title: Optimal scheduling of an isolated microgrid with battery storage considering load and renewable generation uncertainties publication-title: IEEE Trans. Ind. Electron. – volume: 33 start-page: 70 year: 2017 end-page: 83 ident: bib10 article-title: Cost causation based allocations of costs for market integration of renewable energy publication-title: IEEE Trans. Power Syst. – volume: 2008 year: 2017 ident: bib23 article-title: Revenue sufficiency guarantees, cost causation, and cost allocation publication-title: Retrieved August – volume: 12 start-page: 3314 year: 2019 ident: bib21 article-title: A deep peak regulation auxiliary service bidding strategy for CHP units based on a risk-averse model and district heating network energy storage publication-title: Energies – volume: 7 start-page: 3189 year: 2021 end-page: 3198 ident: bib2 article-title: A time of use tariff scheme for demand side management of residential energy consumers in Bangladesh publication-title: Energy Rep. – volume: 5 start-page: 533 year: 2019 end-page: 544 ident: bib19 article-title: Benefit evaluation of the deep peak-regulation market in the northeast China grid publication-title: CSEE J. Power Energy Syst. – volume: 276 year: 2023 ident: bib6 article-title: Performance evaluation of wind-solar-hydrogen system for renewable energy generation and green hydrogen generation and storage: energy, exergy, economic, and enviroeconomic publication-title: Energy – volume: 34 year: 2023 ident: bib15 article-title: Peak shaving in distribution networks using stationary energy storage systems: a Swiss case study publication-title: Sustain. Energy Grids Netw. – volume: 59 start-page: 276 year: 2022 end-page: 288 ident: bib27 article-title: Modified shapley value-based profit allocation method for wind power accommodation and deep peak regulation of thermal power publication-title: IEEE Trans. Ind. Appl. – volume: 78 year: 2019 ident: bib36 article-title: Node similarity measuring in complex networks with relative entropy publication-title: Commun. Nonlinear Sci. Numer. Simul. – volume: 12 start-page: 2321 year: 2021 end-page: 2331 ident: bib13 article-title: Coordinating flexible demand response and renewable uncertainties for scheduling of community integrated energy systems with an electric vehicle charging station: a bi-level approach publication-title: IEEE Trans. Sustain. Energy – volume: 33 start-page: 2030 year: 2017 end-page: 2039 ident: bib24 article-title: Cost allocation and net load variability publication-title: IEEE Trans. Power Syst. – volume: 11 year: 2023 ident: bib25 article-title: Research on the deep peak-shaving cost allocation mechanism considering the responsibility of the load side publication-title: Front. Energy Res. – volume: 8 start-page: 71318 year: 2020 end-page: 71325 ident: bib20 article-title: Unit commitment comprehensive optimal model considering the cost of wind power curtailment and deep peak regulation of thermal unit publication-title: IEEE Access – volume: 8 start-page: 111 year: 2023 end-page: 129 ident: bib34 article-title: Multiple attribute group decision-making based on novel probabilistic ordered weighted cosine similarity operators with Pythagorean fuzzy information publication-title: Granul. Comput. – volume: 35 start-page: 609 year: 2018 end-page: 625 ident: bib37 article-title: Aggregation similarity measure based on intuitionistic fuzzy closeness degree and its application to clustering analysis publication-title: J. Intell. Fuzzy Syst. – volume: 14 start-page: 16337 issue: 24 year: 2022 ident: 10.1016/j.egyr.2024.06.011_bib29 article-title: Analysis of optimal operation of multi-energy alliance based on multi-scale dynamic cost equilibrium allocation publication-title: Sustainability doi: 10.3390/su142416337 – volume: 242 year: 2022 ident: 10.1016/j.egyr.2024.06.011_bib38 article-title: Usage of correlation analysis and hypothesis test in optimizing the gated recurrent unit network for wind speed forecasting publication-title: Energy doi: 10.1016/j.energy.2021.122960 – volume: 35 start-page: 609 issue: 1 year: 2018 ident: 10.1016/j.egyr.2024.06.011_bib37 article-title: Aggregation similarity measure based on intuitionistic fuzzy closeness degree and its application to clustering analysis publication-title: J. Intell. Fuzzy Syst. – volume: 5 start-page: 533 issue: 4 year: 2019 ident: 10.1016/j.egyr.2024.06.011_bib19 article-title: Benefit evaluation of the deep peak-regulation market in the northeast China grid publication-title: CSEE J. Power Energy Syst. – volume: 65 start-page: 855 issue: 2 year: 2023 ident: 10.1016/j.egyr.2024.06.011_bib35 article-title: New cosine similarity and distance measures for Fermatean fuzzy sets and TOPSIS approach publication-title: Knowl. Inf. Syst. doi: 10.1007/s10115-022-01776-4 – volume: 161 year: 2022 ident: 10.1016/j.egyr.2024.06.011_bib1 article-title: Environmental impact of renewable energy source based electrical power plants: Solar, wind, hydroelectric, biomass, geothermal, tidal, ocean, and osmotic publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2022.112279 – volume: 266 year: 2022 ident: 10.1016/j.egyr.2024.06.011_bib7 article-title: Unbiased cross-validation kernel density estimation for wind and PV probabilistic modelling publication-title: Energy Convers. Manag. doi: 10.1016/j.enconman.2022.115811 – volume: 66 start-page: 1565 issue: 2 year: 2019 ident: 10.1016/j.egyr.2024.06.011_bib9 article-title: Optimal scheduling of an isolated microgrid with battery storage considering load and renewable generation uncertainties publication-title: IEEE Trans. Ind. Electron. doi: 10.1109/TIE.2018.2840498 – volume: 12 start-page: 2321 issue: 4 year: 2021 ident: 10.1016/j.egyr.2024.06.011_bib13 article-title: Coordinating flexible demand response and renewable uncertainties for scheduling of community integrated energy systems with an electric vehicle charging station: a bi-level approach publication-title: IEEE Trans. Sustain. Energy doi: 10.1109/TSTE.2021.3090463 – volume: 13 start-page: 159 issue: 1 year: 2022 ident: 10.1016/j.egyr.2024.06.011_bib5 article-title: Optimal scheduling of isolated microgrids using automated reinforcement learning-based multi-period forecasting publication-title: IEEE Trans. Sustain. Energy doi: 10.1109/TSTE.2021.3105529 – volume: 2008 issue: 25 year: 2017 ident: 10.1016/j.egyr.2024.06.011_bib23 article-title: Revenue sufficiency guarantees, cost causation, and cost allocation publication-title: Retrieved August – volume: 54 start-page: 723 year: 2016 ident: 10.1016/j.egyr.2024.06.011_bib17 article-title: Overall review of peak shaving for coal-fired power units in China publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2015.10.052 – volume: 276 year: 2023 ident: 10.1016/j.egyr.2024.06.011_bib6 article-title: Performance evaluation of wind-solar-hydrogen system for renewable energy generation and green hydrogen generation and storage: energy, exergy, economic, and enviroeconomic publication-title: Energy doi: 10.1016/j.energy.2023.127386 – year: 2023 ident: 10.1016/j.egyr.2024.06.011_bib30 article-title: Coordinated power smoothing control strategy of multi-wind turbines and energy storage systems in wind farm based on madrl publication-title: IEEE Trans. Sustain. Energy – volume: 18 issue: 1 year: 2023 ident: 10.1016/j.egyr.2024.06.011_bib31 article-title: Beneficial role of diurnal smoothing for grid integration of wind power publication-title: Environ. Res. Lett. doi: 10.1088/1748-9326/aca9e6 – volume: 12 start-page: 3314 issue: 17 year: 2019 ident: 10.1016/j.egyr.2024.06.011_bib21 article-title: A deep peak regulation auxiliary service bidding strategy for CHP units based on a risk-averse model and district heating network energy storage publication-title: Energies doi: 10.3390/en12173314 – ident: 10.1016/j.egyr.2024.06.011_bib12 – volume: 34 year: 2023 ident: 10.1016/j.egyr.2024.06.011_bib15 article-title: Peak shaving in distribution networks using stationary energy storage systems: a Swiss case study publication-title: Sustain. Energy Grids Netw. – volume: 44 start-page: 19658 issue: 36 year: 2019 ident: 10.1016/j.egyr.2024.06.011_bib33 article-title: Size optimization and economic analysis of a coupled wind-hydrogen system with curtailment decisions publication-title: Int. J. Hydrogen Energy doi: 10.1016/j.ijhydene.2019.06.035 – volume: 22 start-page: 53 issue: 1 year: 2023 ident: 10.1016/j.egyr.2024.06.011_bib8 article-title: Image encryption for Offshore wind power based on 2D-LCLM and Zhou Yi Eight trigrams publication-title: Int. J. Bio-Inspired Comput. doi: 10.1504/IJBIC.2023.133505 – volume: 7 start-page: 3189 year: 2021 ident: 10.1016/j.egyr.2024.06.011_bib2 article-title: A time of use tariff scheme for demand side management of residential energy consumers in Bangladesh publication-title: Energy Rep. doi: 10.1016/j.egyr.2021.05.042 – volume: 210 start-page: 1073 year: 2018 ident: 10.1016/j.egyr.2024.06.011_bib4 article-title: Optimal distributed generation planning in active distribution networks considering integration of energy storage publication-title: Appl. Energy doi: 10.1016/j.apenergy.2017.08.008 – volume: 333 year: 2023 ident: 10.1016/j.egyr.2024.06.011_bib32 article-title: Optimal scheduling of island integrated energy systems considering multi-uncertainties and hydrothermal simultaneous transmission: A deep reinforcement learning approach publication-title: Appl. Energy doi: 10.1016/j.apenergy.2022.120540 – volume: 8 start-page: 33151 year: 2020 ident: 10.1016/j.egyr.2024.06.011_bib28 article-title: Bilateral coordinated dispatch of multiple stakeholders in deep peak regulation publication-title: IEEE Access doi: 10.1109/ACCESS.2020.2974050 – volume: 8 start-page: 111 issue: 1 year: 2023 ident: 10.1016/j.egyr.2024.06.011_bib34 article-title: Multiple attribute group decision-making based on novel probabilistic ordered weighted cosine similarity operators with Pythagorean fuzzy information publication-title: Granul. Comput. doi: 10.1007/s41066-022-00318-1 – volume: 275 year: 2020 ident: 10.1016/j.egyr.2024.06.011_bib18 article-title: A realistic pathway for coal-fired power in China from 2020 to 2030 publication-title: J. Clean. Prod. doi: 10.1016/j.jclepro.2020.122859 – volume: 33 start-page: 70 issue: 1 year: 2017 ident: 10.1016/j.egyr.2024.06.011_bib10 article-title: Cost causation based allocations of costs for market integration of renewable energy publication-title: IEEE Trans. Power Syst. doi: 10.1109/TPWRS.2017.2690404 – ident: 10.1016/j.egyr.2024.06.011_bib22 – volume: 15 start-page: 4588 issue: 13 year: 2022 ident: 10.1016/j.egyr.2024.06.011_bib16 article-title: Peak shaving analysis of power demand response with dual uncertainty of unit and demand-side resources under carbon neutral target publication-title: Energies doi: 10.3390/en15134588 – volume: 8 start-page: 71318 year: 2020 ident: 10.1016/j.egyr.2024.06.011_bib20 article-title: Unit commitment comprehensive optimal model considering the cost of wind power curtailment and deep peak regulation of thermal unit publication-title: IEEE Access doi: 10.1109/ACCESS.2020.2983183 – volume: 20 start-page: 391 year: 2017 ident: 10.1016/j.egyr.2024.06.011_bib26 article-title: Research on peak shaving costs and allocation of wind power integration using scalable computing method publication-title: Clust. Comput. doi: 10.1007/s10586-016-0718-y – volume: 126 year: 2023 ident: 10.1016/j.egyr.2024.06.011_bib3 article-title: High renewable electricity penetration: Marginal curtailment and market failure under “subsidy-free” entry publication-title: Energy Econ. doi: 10.1016/j.eneco.2023.107011 – volume: 327 year: 2022 ident: 10.1016/j.egyr.2024.06.011_bib39 article-title: A novel integrated method for short-term wind power forecasting based on fluctuation clustering and history matching publication-title: Appl. Energy doi: 10.1016/j.apenergy.2022.120131 – volume: 78 year: 2019 ident: 10.1016/j.egyr.2024.06.011_bib36 article-title: Node similarity measuring in complex networks with relative entropy publication-title: Commun. Nonlinear Sci. Numer. Simul. doi: 10.1016/j.cnsns.2019.104867 – volume: 349 year: 2023 ident: 10.1016/j.egyr.2024.06.011_bib14 article-title: Sustainable electric vehicle charging coordination: balancing CO2 emission reduction and peak power demand shaving publication-title: Appl. Energy doi: 10.1016/j.apenergy.2023.121637 – volume: 11 year: 2023 ident: 10.1016/j.egyr.2024.06.011_bib25 article-title: Research on the deep peak-shaving cost allocation mechanism considering the responsibility of the load side publication-title: Front. Energy Res. – ident: 10.1016/j.egyr.2024.06.011_bib11 – volume: 59 start-page: 276 issue: 1 year: 2022 ident: 10.1016/j.egyr.2024.06.011_bib27 article-title: Modified shapley value-based profit allocation method for wind power accommodation and deep peak regulation of thermal power publication-title: IEEE Trans. Ind. Appl. doi: 10.1109/TIA.2022.3208866 – volume: 33 start-page: 2030 issue: 2 year: 2017 ident: 10.1016/j.egyr.2024.06.011_bib24 article-title: Cost allocation and net load variability publication-title: IEEE Trans. Power Syst. doi: 10.1109/TPWRS.2017.2732921 |
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SubjectTerms | Cost allocation Equal-kWh following load Peak-load regulation Renewable energy generation Shapley allocation method |
Title | Research on deep peaking cost allocation mechanism considering peaking demand subject and thermal power unit |
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