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A Robust Optimization Model of Aggregated Resources Considering Serving Ratio for Providing Reserve Power in the Joint Electricity Market

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  • Seong-Hyeon Cha

    (Department of Electrical Engineering, Changwon National University (CWNU), 20 Changwondaehak-ro, Uichang-gu, Changwon-si 51140, Republic of Korea)

  • Sun-Hyeok Kwak

    (Department of Electrical Engineering, Changwon National University (CWNU), 20 Changwondaehak-ro, Uichang-gu, Changwon-si 51140, Republic of Korea)

  • Woong Ko

    (Department of Electrical Engineering, Changwon National University (CWNU), 20 Changwondaehak-ro, Uichang-gu, Changwon-si 51140, Republic of Korea)

Abstract

As the share of distributed generation increases, so do the opportunities for aggregators to participate in the electricity market. In particular, aggregators participating in both the day-ahead and real-time markets contribute to improving the reliability of the power system. In addition, aggregators seeking additional revenue can benefit from providing reserves in a joint electricity market environment. However, aggregated resources with uncertainty are limited because of the uncertain nature of both reserve provision and the amount of reserves they can provide. Therefore, this study proposes a robust optimization model for an aggregator to formulate a strategy for participation in the day-ahead markets and deploys energy control in the real-time operation. The serving ratio reflects the availability of the aggregator’s reserve participation. Both the deployed up/down power and renewable energy in the real-time operation are considered as uncertain parameters to reflect the uncertainty. In the case study, we analyze the profit-maximization strategy of an aggregator that owns renewable energy resources and energy-storage systems under the variation interval for uncertain parameters and the serving ratio. The bidding strategies vary by the variation interval and the serving ratio.

Suggested Citation

  • Seong-Hyeon Cha & Sun-Hyeok Kwak & Woong Ko, 2023. "A Robust Optimization Model of Aggregated Resources Considering Serving Ratio for Providing Reserve Power in the Joint Electricity Market," Energies, MDPI, vol. 16(20), pages 1-27, October.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:20:p:7061-:d:1258486
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    References listed on IDEAS

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    1. 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).
    2. Wang, Fei & Ge, Xinxin & Yang, Peng & Li, Kangping & Mi, Zengqiang & Siano, Pierluigi & Duić, Neven, 2020. "Day-ahead optimal bidding and scheduling strategies for DER aggregator considering responsive uncertainty under real-time pricing," Energy, Elsevier, vol. 213(C).
    3. Castagneto Gissey, Giorgio & Subkhankulova, Dina & Dodds, Paul E. & Barrett, Mark, 2019. "Value of energy storage aggregation to the electricity system," Energy Policy, Elsevier, vol. 128(C), pages 685-696.
    4. 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).
    5. Zhang, Rufeng & Sun, Haihang & Li, Guoqing & Jiang, Tao & Li, Xue & Chen, Houhe & Zou, He, 2023. "Reserve provision of combined-cycle unit in joint day-ahead energy and reserve markets," Applied Energy, Elsevier, vol. 336(C).
    6. Kuttner, Leopold, 2022. "Integrated scheduling and bidding of power and reserve of energy resource aggregators with storage plants," Applied Energy, Elsevier, vol. 321(C).
    7. Joseph Nyangon & John Byrne, 2023. "Estimating the impacts of natural gas power generation growth on solar electricity development: PJM's evolving resource mix and ramping capability," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 12(1), January.
    8. Sun, Guoqiang & Shen, Sichen & Chen, Sheng & Zhou, Yizhou & Wei, Zhinong, 2022. "Bidding strategy for a prosumer aggregator with stochastic renewable energy production in energy and reserve markets," Renewable Energy, Elsevier, vol. 191(C), pages 278-290.
    9. Zengqiang Mi & Yulong Jia & Junjie Wang & Xiaoming Zheng, 2018. "Optimal Scheduling Strategies of Distributed Energy Storage Aggregator in Energy and Reserve Markets Considering Wind Power Uncertainties," Energies, MDPI, vol. 11(5), pages 1-17, May.
    10. Iria, José & Soares, Filipe, 2019. "Real-time provision of multiple electricity market products by an aggregator of prosumers," Applied Energy, Elsevier, vol. 255(C).
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