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Strategic active and reactive power scheduling of integrated community energy systems in day-ahead distribution electricity market

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  • Jiang, Tao
  • Dong, Xinru
  • Zhang, Rufeng
  • Li, Xue

Abstract

The increasing penetration of distributed energy resources (DERs) enable integrated community energy systems (ICESs) as emerging techno-economic energy entities at the end-user side. In the deregulated electricity market, the ICESs can actively participate in the distribution electricity market (DEM) to provide active and reactive power dispatched by ICES operator (ICESO). In this context, a strategic active and reactive power scheduling model for ICESs in the day-ahead DEM is proposed in this paper. A novel trading mechanism designed for ICESO and distribution system operator (DSO)’s interaction toward both active and reactive power is represented in the day-ahead DEM, where distribution locational marginal prices (DLMPs) for both active and reactive power are introduced as the market settlements. Then, the trading process is formulated as a bi-level programming problem. The upper level describes the combined cooling, heating, and power (CCHP)-dominated ICESO’s strategic active and reactive power dispatch, in which the DLMPs for active and reactive power, internal flexibility services, and optimal dispatch for inverter-based distributed generators are considered. The lower level performs a DEM clearing for both active and reactive power. Further, Karush–Kuhn–Tucker (KKT) conditions, Big-M approach, and duality theory are used to convert the bi-level model from a Mathematical Programing with Equilibrium Constraints (MPEC) model to a single-level mixed-integer second-order cone programming (MISOCP) model for efficient calculation. Finally, case studies on modified IEEE 33-node and IEEE 123-node distribution systems are adopted to evaluate the performance of the proposed scheduling method. The results show that the proposed scheduling approach can contribute to the renewable energy share and energy efficiency, reduce CCHP-dominated ICESs’ operation costs by 38.13% and 13.21% compared to the case where ICESO only acts as a price-taking consumer, and 6.64% and 3.44% compared to the case where ICESO does not consider reactive power bids/offers, respectively.

Suggested Citation

  • Jiang, Tao & Dong, Xinru & Zhang, Rufeng & Li, Xue, 2023. "Strategic active and reactive power scheduling of integrated community energy systems in day-ahead distribution electricity market," Applied Energy, Elsevier, vol. 336(C).
    • Handle: RePEc:eee:appene:v:336:y:2023:i:c:s0306261922018153
    DOI: 10.1016/j.apenergy.2022.120558
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    1. Sheikhahmadi, P. & Bahramara, S. & Moshtagh, J. & Yazdani Damavandi, M., 2018. "A risk-based approach for modeling the strategic behavior of a distribution company in wholesale energy market," Applied Energy, Elsevier, vol. 214(C), pages 24-38.
    2. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Zhai, Zhiqiang (John), 2011. "Performance comparison of combined cooling heating and power system in different operation modes," Applied Energy, Elsevier, vol. 88(12), pages 4621-4631.
    3. Sun, Qingkai & Wang, Xiaojun & Liu, Zhao & Mirsaeidi, Sohrab & He, Jinghan & Pei, Wei, 2022. "Multi-agent energy management optimization for integrated energy systems under the energy and carbon co-trading market," Applied Energy, Elsevier, vol. 324(C).
    4. Chen, Houhe & Wang, Di & Zhang, Rufeng & Jiang, Tao & Li, Xue, 2022. "Optimal participation of ADN in energy and reserve markets considering TSO-DSO interface and DERs uncertainties," Applied Energy, Elsevier, vol. 308(C).
    5. 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.
    6. Jiang, Qian & Mu, Yunfei & Jia, Hongjie & Cao, Yan & Wang, Zibo & Wei, Wei & Hou, Kai & Yu, Xiaodan, 2022. "A Stackelberg Game-based planning approach for integrated community energy system considering multiple participants," Energy, Elsevier, vol. 258(C).
    7. Liu, Mingxi & Shi, Yang & Fang, Fang, 2012. "A new operation strategy for CCHP systems with hybrid chillers," Applied Energy, Elsevier, vol. 95(C), pages 164-173.
    8. Li, Nan & Zhao, Xunwen & Shi, Xunpeng & Pei, Zhenwei & Mu, Hailin & Taghizadeh-Hesary, Farhad, 2021. "Integrated energy systems with CCHP and hydrogen supply: A new outlet for curtailed wind power," Applied Energy, Elsevier, vol. 303(C).
    9. Huiru Zhao & Hao Lu & Xuejie Wang & Bingkang Li & Yuwei Wang & Pei Liu & Zhao Ma, 2020. "Research on Comprehensive Value of Electrical Energy Storage in CCHP Microgrid with Renewable Energy Based on Robust Optimization," Energies, MDPI, vol. 13(24), pages 1-22, December.
    10. Rajabi Hamedani, Sara & Villarini, Mauro & Marcantonio, Vera & di Matteo, Umberto & Monarca, Danilo & Colantoni, Andrea, 2023. "Comparative energy and environmental analysis of different small-scale biomass-fueled CCHP systems," Energy, Elsevier, vol. 263(PD).
    11. Wang, Lang & Lu, Jianfeng & Wang, Weilong & Ding, Jing, 2016. "Energy, environmental and economic evaluation of the CCHP systems for a remote island in south of China," Applied Energy, Elsevier, vol. 183(C), pages 874-883.
    12. Bayat, A. & Bagheri, A., 2019. "Optimal active and reactive power allocation in distribution networks using a novel heuristic approach," Applied Energy, Elsevier, vol. 233, pages 71-85.
    13. Zhou, Yizhou & Wei, Zhinong & Sun, Guoqiang & Cheung, Kwok W. & Zang, Haixiang & Chen, Sheng, 2018. "A robust optimization approach for integrated community energy system in energy and ancillary service markets," Energy, Elsevier, vol. 148(C), pages 1-15.
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