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Optimal dispatching strategy and real-time pricing for multi-regional integrated energy systems based on demand response

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  • Yuan, Guanxiu
  • Gao, Yan
  • Ye, Bei

Abstract

With the penetration of multiple distributed energy sources, demand side management (DSM) of the regional integrated energy system (RIES) becomes more complicated in the energy market. Real-time pricing (RTP) is an effective method for DSM, which can flexibly guide the supply and demand sides to adjust their behavior to participate in demand response (DR). In this paper, a hierarchical energy system is studied including multiple RIESs with multiple energy dispatch and supplement. To maximize the social welfare, a bilevel programming model is developed, in which the upper level aims at maximizing the profits of the supplier, and the lower level aims at maximizing the RIESs' welfare. Then, the proposed bilevel model is transformed into a mixed integer quadratic programming model using duality theory and Karush-Kuhn-Tucker conditions. Furthermore, the RTP strategy is obtained, and the optimal energy scheme of RIES is given in the solution. Compared simulations in different scenarios, the total social welfare is increased by about 14.12%, the peak-to-valley difference of power load and carbon emissions are reduced by 16.99% and 5.7% respectively after DR. The results show that the proposed bilevel model under the RTP is conducive to social economy and environment.

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  • Yuan, Guanxiu & Gao, Yan & Ye, Bei, 2021. "Optimal dispatching strategy and real-time pricing for multi-regional integrated energy systems based on demand response," Renewable Energy, Elsevier, vol. 179(C), pages 1424-1446.
    • Handle: RePEc:eee:renene:v:179:y:2021:i:c:p:1424-1446
    DOI: 10.1016/j.renene.2021.07.036
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    References listed on IDEAS

    as
    1. Gu, Haifei & Li, Yang & Yu, Jie & Wu, Chen & Song, Tianli & Xu, Jinzhou, 2020. "Bi-level optimal low-carbon economic dispatch for an industrial park with consideration of multi-energy price incentives," Applied Energy, Elsevier, vol. 262(C).
    2. Li, Guoqing & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Bai, Linquan & Cui, Hantao & Li, Xiaojing, 2017. "Optimal dispatch strategy for integrated energy systems with CCHP and wind power," Applied Energy, Elsevier, vol. 192(C), pages 408-419.
    3. Collins, Seán & Deane, John Paul & Poncelet, Kris & Panos, Evangelos & Pietzcker, Robert C. & Delarue, Erik & Ó Gallachóir, Brian Pádraig, 2017. "Integrating short term variations of the power system into integrated energy system models: A methodological review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 839-856.
    4. Salehimaleh, Mohammad & Akbarimajd, Adel & Valipour, Khalil & Dejamkhooy, Abdolmajid, 2018. "Generalized modeling and optimal management of energy hub based electricity, heat and cooling demands," Energy, Elsevier, vol. 159(C), pages 669-685.
    5. Di Somma, M. & Graditi, G. & Heydarian-Forushani, E. & Shafie-khah, M. & Siano, P., 2018. "Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects," Renewable Energy, Elsevier, vol. 116(PA), pages 272-287.
    6. Ordoudis, Christos & Delikaraoglou, Stefanos & Kazempour, Jalal & Pinson, Pierre, 2020. "Market-based coordination of integrated electricity and natural gas systems under uncertain supply," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1105-1119.
    7. Li, Yuanyuan & Li, Junxiang & He, Jianjia & Zhang, Shuyuan, 2021. "The real-time pricing optimization model of smart grid based on the utility function of the logistic function," Energy, Elsevier, vol. 224(C).
    8. Dai, Yeming & Zhao, Pei, 2020. "A hybrid load forecasting model based on support vector machine with intelligent methods for feature selection and parameter optimization," Applied Energy, Elsevier, vol. 279(C).
    9. Bornapour, Mosayeb & Hooshmand, Rahmat-Allah & Parastegari, Moein, 2019. "An efficient scenario-based stochastic programming method for optimal scheduling of CHP-PEMFC, WT, PV and hydrogen storage units in micro grids," Renewable Energy, Elsevier, vol. 130(C), pages 1049-1066.
    10. Martine Labbé & Alessia Violin, 2016. "Bilevel programming and price setting problems," Annals of Operations Research, Springer, vol. 240(1), pages 141-169, May.
    11. Chaudhary, Priyanka & Rizwan, M., 2018. "Energy management supporting high penetration of solar photovoltaic generation for smart grid using solar forecasts and pumped hydro storage system," Renewable Energy, Elsevier, vol. 118(C), pages 928-946.
    12. Tabar, Vahid Sohrabi & Ghassemzadeh, Saeid & Tohidi, Sajjad, 2019. "Energy management in hybrid microgrid with considering multiple power market and real time demand response," Energy, Elsevier, vol. 174(C), pages 10-23.
    13. Kaygusuz, Asim, 2019. "Closed loop elastic demand control by dynamic energy pricing in smart grids," Energy, Elsevier, vol. 176(C), pages 596-603.
    14. Xu, Weiwei & Zhou, Dan & Huang, Xiaoming & Lou, Boliang & Liu, Dong, 2020. "Optimal allocation of power supply systems in industrial parks considering multi-energy complementarity and demand response," Applied Energy, Elsevier, vol. 275(C).
    15. Benoît Colson & Patrice Marcotte & Gilles Savard, 2007. "An overview of bilevel optimization," Annals of Operations Research, Springer, vol. 153(1), pages 235-256, September.
    16. Mansouri, Seyed Amir & Ahmarinejad, Amir & Javadi, Mohammad Sadegh & Catalão, João P.S., 2020. "Two-stage stochastic framework for energy hubs planning considering demand response programs," Energy, Elsevier, vol. 206(C).
    17. Wu, Xiaomin & Cao, Weihua & Wang, Dianhong & Ding, Min & Yu, Liangjun & Nakanishi, Yosuke, 2021. "Demand response model based on improved Pareto optimum considering seasonal electricity prices for Dongfushan Island," Renewable Energy, Elsevier, vol. 164(C), pages 926-936.
    18. Li, Guoqing & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Bai, Linquan & Li, Xiaojing, 2017. "Security-constrained bi-level economic dispatch model for integrated natural gas and electricity systems considering wind power and power-to-gas process," Applied Energy, Elsevier, vol. 194(C), pages 696-704.
    19. Wu, Chuanshen & Gao, Shan & Liu, Yu & Song, Tiancheng E. & Han, Haiteng, 2021. "A model predictive control approach in microgrid considering multi-uncertainty of electric vehicles," Renewable Energy, Elsevier, vol. 163(C), pages 1385-1396.
    20. Yang, Xiaohui & Leng, Zhengyang & Xu, Shaoping & Yang, Chunsheng & Yang, Li & Liu, Kang & Song, Yaoren & Zhang, Liufang, 2021. "Multi-objective optimal scheduling for CCHP microgrids considering peak-load reduction by augmented ε-constraint method," Renewable Energy, Elsevier, vol. 172(C), pages 408-423.
    21. Gjorgievski, Vladimir Z. & Cundeva, Snezana & Georghiou, George E., 2021. "Social arrangements, technical designs and impacts of energy communities: A review," Renewable Energy, Elsevier, vol. 169(C), pages 1138-1156.
    22. Yanzhe (Murray) Lei & Stefanus Jasin, 2020. "Real-Time Dynamic Pricing for Revenue Management with Reusable Resources, Advance Reservation, and Deterministic Service Time Requirements," Operations Research, INFORMS, vol. 68(3), pages 676-685, May.
    23. Alipour, Manijeh & Zare, Kazem & Seyedi, Heresh, 2018. "A multi-follower bilevel stochastic programming approach for energy management of combined heat and power micro-grids," Energy, Elsevier, vol. 149(C), pages 135-146.
    24. Anand, Hithu & Ramasubbu, Rengaraj, 2018. "A real time pricing strategy for remote micro-grid with economic emission dispatch and stochastic renewable energy sources," Renewable Energy, Elsevier, vol. 127(C), pages 779-789.
    25. Li, Longxi & Cao, Xilin & Wang, Peng, 2021. "Optimal coordination strategy for multiple distributed energy systems considering supply, demand, and price uncertainties," Energy, Elsevier, vol. 227(C).
    26. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Hosseinzadeh, Mehdi & Yousefi, Hossein & Khorasani, Sasan Torabzadeh, 2018. "Optimal management of energy hubs and smart energy hubs – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 33-50.
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    3. Lyu, Xiangmei & Liu, Tianqi & Liu, Xuan & He, Chuan & Nan, Lu & Zeng, Hong, 2023. "Low-carbon robust economic dispatch of park-level integrated energy system considering price-based demand response and vehicle-to-grid," Energy, Elsevier, vol. 263(PB).
    4. Gejirifu De & Xinlei Wang & Xueqin Tian & Tong Xu & Zhongfu Tan, 2022. "A Collaborative Optimization Model for Integrated Energy System Considering Multi-Load Demand Response," Energies, MDPI, vol. 15(6), pages 1-26, March.
    5. Dai, Yeming & Sun, Xilian & Qi, Yao & Leng, Mingming, 2021. "A real-time, personalized consumption-based pricing scheme for the consumptions of traditional and renewable energies," Renewable Energy, Elsevier, vol. 180(C), pages 452-466.
    6. Meng, Anbo & Xu, Xuancong & Zhang, Zhan & Zeng, Cong & Liang, Ruduo & Zhang, Zheng & Wang, Xiaolin & Yan, Baiping & Yin, Hao & Luo, Jianqiang, 2022. "Solving high-dimensional multi-area economic dispatch problem by decoupled distributed crisscross optimization algorithm with population cross generation strategy," Energy, Elsevier, vol. 258(C).
    7. Han, Ouzhu & Ding, Tao & Zhang, Xiaosheng & Mu, Chenggang & He, Xinran & Zhang, Hongji & Jia, Wenhao & Ma, Zhoujun, 2023. "A shared energy storage business model for data center clusters considering renewable energy uncertainties," Renewable Energy, Elsevier, vol. 202(C), pages 1273-1290.
    8. Li, Ningning & Gao, Yan, 2023. "Real-time pricing based on convex hull method for smart grid with multiple generating units," Energy, Elsevier, vol. 285(C).
    9. Xia, Tangbin & Si, Guojin & Shi, Guo & Zhang, Kaigan & Xi, Lifeng, 2022. "Optimal selective maintenance scheduling for series–parallel systems based on energy efficiency optimization," Applied Energy, Elsevier, vol. 314(C).
    10. Bian, Yifan & Xie, Lirong & Ye, Jiahao & Ma, Lan, 2024. "A new shared energy storage business model for data center clusters considering energy storage degradation," Renewable Energy, Elsevier, vol. 225(C).
    11. Jieran Feng & Junpei Nan & Chao Wang & Ke Sun & Xu Deng & Hao Zhou, 2022. "Source-Load Coordinated Low-Carbon Economic Dispatch of Electric-Gas Integrated Energy System Based on Carbon Emission Flow Theory," Energies, MDPI, vol. 15(10), pages 1-24, May.
    12. Dong, Haiyan & Fu, Yanbo & Jia, Qingquan & Zhang, Tie & Meng, Dequn, 2023. "Low carbon optimization of integrated energy microgrid based on life cycle analysis method and multi time scale energy storage," Renewable Energy, Elsevier, vol. 206(C), pages 60-71.
    13. Dai, Yeming & Yang, Xinyu & Leng, Mingming, 2022. "Forecasting power load: A hybrid forecasting method with intelligent data processing and optimized artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    14. Wang, Yudong & Hu, Junjie, 2023. "Two-stage energy management method of integrated energy system considering pre-transaction behavior of energy service provider and users," Energy, Elsevier, vol. 271(C).

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