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EV-observing distribution system management considering strategic VPPs and active & reactive power markets

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  • Ebrahimi, Mahoor
  • Ebrahimi, Mahan
  • Shafie-khah, Miadreza
  • Laaksonen, Hannu

Abstract

The growing deployment of new flexible resources, renewable energy resources (RES), and Electric Vehicles (EV) in the distribution system necessitates new methods to manage the distribution system operation optimally. In this regard, our paper, by deploying the concept of Virtual Power Plants (VPPs) as the aggregation of multiple agents and local power markets that are known as important tools for future power systems presents a management framework for the distribution systems with high penetration of EVs. To this end, the interaction of the DSO and VPPs is studied based on their strategic behaviour through the local active and reactive power markets. This way, a bilevel optimization approach is proposed where the DSO aims to minimize its operational cost by setting the operation point of its own facilities and determining the hourly active and reactive power prices for VPPs considering the distribution system congestion in the upper level. At the lower level, VPPs try to minimize their cost by scheduling their assets based on the local active and reactive power prices set by the DSO. The results show how nodal pricing in local markets could improve the distribution system operation. In addition, it is indicated that Reactive Power Support (RPS) from VPP-owned EVPLs can decrease the VPPs’ cost by gaining profit in the reactive power market and facilitating their participation in the active power market.

Suggested Citation

  • Ebrahimi, Mahoor & Ebrahimi, Mahan & Shafie-khah, Miadreza & Laaksonen, Hannu, 2024. "EV-observing distribution system management considering strategic VPPs and active & reactive power markets," Applied Energy, Elsevier, vol. 364(C).
  • Handle: RePEc:eee:appene:v:364:y:2024:i:c:s030626192400535x
    DOI: 10.1016/j.apenergy.2024.123152
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    References listed on IDEAS

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    1. Rawat, Tanuj & Niazi, K.R. & Gupta, Nikhil & Sharma, Sachin, 2022. "A linearized multi-objective Bi-level approach for operation of smart distribution systems encompassing demand response," Energy, Elsevier, vol. 238(PC).
    2. Li, Qiang & Wei, Fanchao & Zhou, Yongcheng & Li, Jiajia & Zhou, Guowen & Wang, Zhonghao & Liu, Jinfu & Yan, Peigang & Yu, Daren, 2023. "A scheduling framework for VPP considering multiple uncertainties and flexible resources," Energy, Elsevier, vol. 282(C).
    3. Zhao, Jinli & Zhang, Mengzhen & Yu, Hao & Ji, Haoran & Song, Guanyu & Li, Peng & Wang, Chengshan & Wu, Jianzhong, 2019. "An islanding partition method of active distribution networks based on chance-constrained programming," Applied Energy, Elsevier, vol. 242(C), pages 78-91.
    4. Lu, Yu & Xiang, Yue & Huang, Yuan & Yu, Bin & Weng, Liguo & Liu, Junyong, 2023. "Deep reinforcement learning based optimal scheduling of active distribution system considering distributed generation, energy storage and flexible load," Energy, Elsevier, vol. 271(C).
    5. Zhang, Tianhan & Qiu, Weiqiang & Zhang, Zhi & Lin, Zhenzhi & Ding, Yi & Wang, Yiting & Wang, Lianfang & Yang, Li, 2023. "Optimal bidding strategy and profit allocation method for shared energy storage-assisted VPP in joint energy and regulation markets," Applied Energy, Elsevier, vol. 329(C).
    6. Khaledi, Arian & Saifoddin, Amirali, 2023. "Three-stage resilience-oriented active distribution systems operation after natural disasters," Energy, Elsevier, vol. 282(C).
    7. Wooyoung Jeon & Sangmin Cho & Seungmoon Lee, 2020. "Estimating the Impact of Electric Vehicle Demand Response Programs in a Grid with Varying Levels of Renewable Energy Sources: Time-of-Use Tariff versus Smart Charging," Energies, MDPI, vol. 13(17), pages 1-22, August.
    8. Bhuiyan, Erphan A. & Hossain, Md. Zahid & Muyeen, S.M. & Fahim, Shahriar Rahman & Sarker, Subrata K. & Das, Sajal K., 2021. "Towards next generation virtual power plant: Technology review and frameworks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    9. Jayachandran, M. & Rao, K. Prasada & Gatla, Ranjith Kumar & Kalaivani, C. & Kalaiarasy, C. & Logasabarirajan, C., 2022. "Operational concerns and solutions in smart electricity distribution systems," Utilities Policy, Elsevier, vol. 74(C).
    10. Lei, Xiang & Yu, Hang & Shao, Ziyun & Jian, Linni, 2023. "Optimal bidding and coordinating strategy for maximal marginal revenue due to V2G operation: Distribution system operator as a key player in China's uncertain electricity markets," Energy, Elsevier, vol. 283(C).
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