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A hierarchy model to use local resources by DSO and TSO in the balancing market

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  • Khojasteh, Meysam
  • Faria, Pedro
  • Lezama, Fernando
  • Vale, Zita

Abstract

Due to the increasing penetration level of local generating resources at the distribution network, the transmission system operator (TSO) and distribution system operators (DSOs) need to coordinate their operations to use these resources and provide the required energy and regulation for the power system. This work proposes a hierarchy model for scheduling the local flexible resources at the distribution and transmission levels. In the first stage, the optimal bidding strategy of balance service providers (BSPs) and the distribution balancing market-clearing problem are formulated by a bi-level optimization problem, respectively. At this stage, the lower-level sub-problem is replaced by the Karush–Kuhn–Tucker (KKT) conditions, and the bi-level problem is formulated as a mathematical programming with equilibrium constraints (MPEC) problem. Results of the first stage are considered as fixed parameters for the second stage problem, which specifies the feasible bids of local resources that the TSO can dispatch. At the second stage, DSO checks the feasibility of remaining bids, which are not dispatched in the distribution balancing market, and determines the maximum regulation capability of the local resources that the TSO can use. Simulation results indicate that in the IEEE 33-bus distribution test system with the total imbalance energy of 4.672 MWh, 32.36% and 67.64% of the required power are compensated by transmission balancing market and local resources, which results in a reduction of 24.32% in balancing costs.

Suggested Citation

  • Khojasteh, Meysam & Faria, Pedro & Lezama, Fernando & Vale, Zita, 2023. "A hierarchy model to use local resources by DSO and TSO in the balancing market," Energy, Elsevier, vol. 267(C).
    • Handle: RePEc:eee:energy:v:267:y:2023:i:c:s0360544222033473
    DOI: 10.1016/j.energy.2022.126461
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    References listed on IDEAS

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    1. Dimitriadis, Christos N. & Tsimopoulos, Evangelos G. & Georgiadis, Michael C., 2022. "Strategic bidding of an energy storage agent in a joint energy and reserve market under stochastic generation," Energy, Elsevier, vol. 242(C).
    2. Liu, Jia & Zeng, Peter Pingliang & Xing, Hao & Li, Yalou & Wu, Qiuwei, 2020. "Hierarchical duality-based planning of transmission networks coordinating active distribution network operation," Energy, Elsevier, vol. 213(C).
    3. Kara, Güray & Pisciella, Paolo & Tomasgard, Asgeir & Farahmand, Hossein & Crespo del Granado, Pedro, 2022. "Stochastic local flexibility market design, bidding, and dispatch for distribution grid operations," Energy, Elsevier, vol. 253(C).
    4. Yan, Rujing & Wang, Jiangjiang & Huo, Shuojie & Qin, Yanbo & Zhang, Jing & Tang, Saiqiu & Wang, Yuwei & Liu, Yan & Zhou, Lin, 2023. "Flexibility improvement and stochastic multi-scenario hybrid optimization for an integrated energy system with high-proportion renewable energy," Energy, Elsevier, vol. 263(PB).
    5. van der Veen, Reinier A.C. & Abbasy, Alireza & Hakvoort, Rudi A., 2012. "Agent-based analysis of the impact of the imbalance pricing mechanism on market behavior in electricity balancing markets," Energy Economics, Elsevier, vol. 34(4), pages 874-881.
    6. Azim, M. Imran & Tushar, Wayes & Saha, Tapan K. & Yuen, Chau & Smith, David, 2022. "Peer-to-peer kilowatt and negawatt trading: A review of challenges and recent advances in distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    7. 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).
    8. Wang, Shouxiang & Wang, Kai & Teng, Fei & Strbac, Goran & Wu, Lei, 2018. "An affine arithmetic-based multi-objective optimization method for energy storage systems operating in active distribution networks with uncertainties," Applied Energy, Elsevier, vol. 223(C), pages 215-228.
    9. Chen, Houhe & Lin, Chuqiao & Fu, Linbo & Zhang, Rufeng, 2021. "Collaborative optimal operation of transmission system with integrated active distribution system and district heating system based on semi-definite programming relaxation method," Energy, Elsevier, vol. 227(C).
    10. Le Cadre, Hélène & Mezghani, Ilyès & Papavasiliou, Anthony, 2019. "A game-theoretic analysis of transmission-distribution system operator coordination," European Journal of Operational Research, Elsevier, vol. 274(1), pages 317-339.
    11. Silva, Ana R. & Pousinho, H.M.I. & Estanqueiro, Ana, 2022. "A multistage stochastic approach for the optimal bidding of variable renewable energy in the day-ahead, intraday and balancing markets," Energy, Elsevier, vol. 258(C).
    12. Qin, Zhijun & Mo, Yuhong & Liu, Hui & Zhang, Yihui, 2021. "Operational flexibility enhancements using mobile energy storage in day-ahead electricity market by game-theoretic approach," Energy, Elsevier, vol. 232(C).
    13. Khojasteh, Meysam & Faria, Pedro & Vale, Zita, 2022. "A robust model for aggregated bidding of energy storages and wind resources in the joint energy and reserve markets," Energy, Elsevier, vol. 238(PB).
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    Cited by:

    1. Di Foggia, Giacomo & Beccarello, Massimo, 2024. "Designing New Energy Markets to Promote Renewables," MPRA Paper 121783, University Library of Munich, Germany.
    2. Aouss Gabash, 2023. "Energy Market Transition and Climate Change: A Review of TSOs-DSOs C+++ Framework from 1800 to Present," Energies, MDPI, vol. 16(17), pages 1-24, August.
    3. Vijay, Rohit & Mathuria, Parul, 2024. "Common TSO-DSO market framework with no upfront priority to utilize DER flexibility," Energy, Elsevier, vol. 299(C).

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