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A stochastic game-theoretic optimization approach for managing local electricity markets with electric vehicles and renewable sources

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  • Hosseini Dolatabadi, Sayed Hamid
  • Bhuiyan, Tanveer Hossain
  • Chen, Yang
  • Morales, Jose Luis

Abstract

In response to the growing need for sustainable and environmentally friendly energy ecosystems as well as the rapid adoption of electric vehicles (EVs) and renewable energy sources (RESs), local electricity markets (LEMs) offer a distinct potential to improve grid stability, promote clean energy, and reduce costs. However, harnessing the full potential of LEMs requires addressing multifaceted challenges associated with market dynamics, and the integration of EVs and RESs. Our study presents a stochastic bi-level model for managing LEMs, where the local transaction center (LTC) and other market participants (agents)—load aggregator (LA), charging station (CS), and their lower-level prosumers—aim to maximize their profits in a competitive game-theoretic structure. To ensure grid stability and profitability, LTC as the leader seeks to design a robust dynamic pricing strategy under uncertainty, whereas LA and CS, as followers, decide on the energy transaction amounts under uncertainty in their generation and consumption. We address several novel aspects of LEMs, such as heterogeneous behaviors of entities, uncertainties in renewable generation and load profiles, and the consumption profile of the EV fleet. We propose a centralized solution approach based on Karush–Kuhn–Tucker optimization and a decentralized approach based on a hybrid Genetic algorithm for solving the LEM management problem. The centralized approach provides optimal solutions whereas the decentralized approach provides near-optimal solutions much faster while maintaining the privacy of market participants (agents). Numerical results based on a realistic case study demonstrate that increasing the capacity of LTC’s energy storage and its initial state of charge increases LTC’s profit by 255%. Results also demonstrate that modeling the LEM under uncertainty as a two-stage stochastic program provides a robust pricing decision resulting in a 433% higher profit compared to the deterministic modeling that ignores the uncertainties in the key parameters.

Suggested Citation

  • Hosseini Dolatabadi, Sayed Hamid & Bhuiyan, Tanveer Hossain & Chen, Yang & Morales, Jose Luis, 2024. "A stochastic game-theoretic optimization approach for managing local electricity markets with electric vehicles and renewable sources," Applied Energy, Elsevier, vol. 368(C).
    • Handle: RePEc:eee:appene:v:368:y:2024:i:c:s0306261924009012
    DOI: 10.1016/j.apenergy.2024.123518
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    as
    1. Chang, Weiguang & Dong, Wei & Yang, Qiang, 2023. "Day-ahead bidding strategy of cloud energy storage serving multiple heterogeneous microgrids in the electricity market," Applied Energy, Elsevier, vol. 336(C).
    2. 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).
    3. Tushar, Wayes & Yuen, Chau & Saha, Tapan K. & Morstyn, Thomas & Chapman, Archie C. & Alam, M. Jan E. & Hanif, Sarmad & Poor, H. Vincent, 2021. "Peer-to-peer energy systems for connected communities: A review of recent advances and emerging challenges," Applied Energy, Elsevier, vol. 282(PA).
    4. K.C., Bevin & Verma, Ashu, 2023. "Decentralized local electricity market model using Automated Market Maker," Applied Energy, Elsevier, vol. 334(C).
    5. Neuhoff, Karsten & Richstein, Jörn C. & Kröger, Mats, 2023. "Reacting to changing paradigms: How and why to reform electricity markets," Energy Policy, Elsevier, vol. 180(C).
    6. Hong, Qiuyi & Meng, Fanlin & Liu, Jian & Bo, Rui, 2023. "A bilevel game-theoretic decision-making framework for strategic retailers in both local and wholesale electricity markets," Applied Energy, Elsevier, vol. 330(PA).
    7. Wei, F. & Jing, Z.X. & Wu, Peter Z. & Wu, Q.H., 2017. "A Stackelberg game approach for multiple energies trading in integrated energy systems," Applied Energy, Elsevier, vol. 200(C), pages 315-329.
    8. Kröger, David & Peper, Jan & Rehtanz, Christian, 2023. "Electricity market modeling considering a high penetration of flexible heating systems and electric vehicles," Applied Energy, Elsevier, vol. 331(C).
    9. Mehdinejad, Mehdi & Shayanfar, Heidarali & Mohammadi-Ivatloo, Behnam, 2022. "Peer-to-peer decentralized energy trading framework for retailers and prosumers," Applied Energy, Elsevier, vol. 308(C).
    10. Wang, Yubin & Zheng, Yanchong & Yang, Qiang, 2023. "Optimal energy management of integrated energy systems for strategic participation in competitive electricity markets," Energy, Elsevier, vol. 278(PA).
    11. Zhang, Chenghua & Wu, Jianzhong & Zhou, Yue & Cheng, Meng & Long, Chao, 2018. "Peer-to-Peer energy trading in a Microgrid," Applied Energy, Elsevier, vol. 220(C), pages 1-12.
    12. Guo, Yi & Han, Xuejiao & Zhou, Xinyang & Hug, Gabriela, 2023. "Incorporate day-ahead robustness and real-time incentives for electricity market design," Applied Energy, Elsevier, vol. 332(C).
    13. Qiu, Dawei & Xue, Juxing & Zhang, Tingqi & Wang, Jianhong & Sun, Mingyang, 2023. "Federated reinforcement learning for smart building joint peer-to-peer energy and carbon allowance trading," Applied Energy, Elsevier, vol. 333(C).
    14. Karsten Neuhoff & Jörn C. Richstein & Mats Kröger, 2023. "Reacting to Changing Paradigms: How and Why to Reform Electricity Markets," DIW Berlin: Politikberatung kompakt, DIW Berlin, German Institute for Economic Research, volume 127, number pbk189.
    15. Soto, Esteban A. & Bosman, Lisa B. & Wollega, Ebisa & Leon-Salas, Walter D., 2021. "Peer-to-peer energy trading: A review of the literature," Applied Energy, Elsevier, vol. 283(C).
    16. García-Muñoz, Fernando & Dávila, Sebastián & Quezada, Franco, 2023. "A Benders decomposition approach for solving a two-stage local energy market problem under uncertainty," Applied Energy, Elsevier, vol. 329(C).
    17. Tushar, Wayes & Saha, Tapan Kumar & Yuen, Chau & Morstyn, Thomas & McCulloch, Malcolm D. & Poor, H. Vincent & Wood, Kristin L., 2019. "A motivational game-theoretic approach for peer-to-peer energy trading in the smart grid," Applied Energy, Elsevier, vol. 243(C), pages 10-20.
    18. Samende, Cephas & Cao, Jun & Fan, Zhong, 2022. "Multi-agent deep deterministic policy gradient algorithm for peer-to-peer energy trading considering distribution network constraints," Applied Energy, Elsevier, vol. 317(C).
    19. McKenna, Eoghan & Thomson, Murray, 2016. "High-resolution stochastic integrated thermal–electrical domestic demand model," Applied Energy, Elsevier, vol. 165(C), pages 445-461.
    20. Wang, Jun & Xu, Jian & Ke, Deping & Liao, Siyang & Sun, Yuanzhang & Wang, Jingjing & Yao, Liangzhong & Mao, Beiling & Wei, Congying, 2023. "A tri-level framework for distribution-level market clearing considering strategic participation of electrical vehicles and interactions with wholesale market," Applied Energy, Elsevier, vol. 329(C).
    21. Aguado, José A. & Paredes, Ángel, 2023. "Coordinated and decentralized trading of flexibility products in Inter-DSO Local Electricity Markets via ADMM," Applied Energy, Elsevier, vol. 337(C).
    22. Chen, Yang & Park, Byungkwon & Kou, Xiao & Hu, Mengqi & Dong, Jin & Li, Fangxing & Amasyali, Kadir & Olama, Mohammed, 2020. "A comparison study on trading behavior and profit distribution in local energy transaction games," Applied Energy, Elsevier, vol. 280(C).
    23. Acuña, Luceny Guzmán & Ríos, Diana Ramírez & Arboleda, Carlos Paternina & Ponzón, Esneyder González, 2018. "Cooperation model in the electricity energy market using bi-level optimization and Shapley value," Operations Research Perspectives, Elsevier, vol. 5(C), pages 161-168.
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