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A multi-area intra-day dispatch strategy for power systems under high share of renewable energy with power support capacity assessment

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  • Ye, Lin
  • Jin, Yifei
  • Wang, Kaifeng
  • Chen, Wei
  • Wang, Fei
  • Dai, Binhua

Abstract

Long-distance power support through High-voltage Direct Current (HVDC) has provided feasible solutions for power dispatch and control problems in multi-area power systems under high share of renewable energy. In this paper, an advanced multi-area intra-day dispatch strategy for power systems with high penetration of renewable energy considering power support capacity is established to increase the accommodation of wind power and enhance the stability of the power system. At first, a novel assessment method of regional active power support capacity is carried out in this paper, which can sufficiently quantify the regional power margin (RPM), the DC dispatchable power (DCDP), and the regional power support distance (RPSD) of a power system. Subsequently, a multi-area intra-day dispatch strategy based on power support capacity analysis is proposed, where constraints on conventional units, wind farms, transmission lines, and RPSD are developed. Finally, to enable the development of the dispatch model, a model predictive control (MPC) scheme is used to update the power support capacity indicators dynamically and improve model reliability. The effectiveness and superiority of the proposed strategy are verified by case studies. Numerical results show a 7.02% cost reduction and overload risk reduction by using the proposed strategy compared to conventional global optimization methods.

Suggested Citation

  • Ye, Lin & Jin, Yifei & Wang, Kaifeng & Chen, Wei & Wang, Fei & Dai, Binhua, 2023. "A multi-area intra-day dispatch strategy for power systems under high share of renewable energy with power support capacity assessment," Applied Energy, Elsevier, vol. 351(C).
    • Handle: RePEc:eee:appene:v:351:y:2023:i:c:s0306261923012308
    DOI: 10.1016/j.apenergy.2023.121866
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    References listed on IDEAS

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    1. Zhang, Heng & Hu, Xiao & Cheng, Haozhong & Zhang, Shenxi & Hong, Shaoyun & Gu, Qingfa, 2021. "Coordinated scheduling of generators and tie lines in multi-area power systems under wind energy uncertainty," Energy, Elsevier, vol. 222(C).
    2. Pengfei Li & Tong Zhang & Yantao Jin, 2023. "A Spatio-Temporal Graph Convolutional Network for Air Quality Prediction," Sustainability, MDPI, vol. 15(9), pages 1-13, May.
    3. Liu, Fan & Bie, Zhaohong & Liu, Shiyu & Ding, Tao, 2017. "Day-ahead optimal dispatch for wind integrated power system considering zonal reserve requirements," Applied Energy, Elsevier, vol. 188(C), pages 399-408.
    4. Zhang, Mingze & Li, Weidong & Yu, Samson Shenglong & Wen, Kerui & Muyeen, S.M., 2023. "Day-ahead optimization dispatch strategy for large-scale battery energy storage considering multiple regulation and prediction failures," Energy, Elsevier, vol. 270(C).
    5. Zhao, Baining & Qian, Tong & Tang, Wenhu & Liang, Qiheng, 2022. "A data-enhanced distributionally robust optimization method for economic dispatch of integrated electricity and natural gas systems with wind uncertainty," Energy, Elsevier, vol. 243(C).
    6. Kumar Jadoun, Vinay & Rahul Prashanth, G & Suhas Joshi, Siddharth & Narayanan, K. & Malik, Hasmat & García Márquez, Fausto Pedro, 2022. "Optimal fuzzy based economic emission dispatch of combined heat and power units using dynamically controlled Whale Optimization Algorithm," Applied Energy, Elsevier, vol. 315(C).
    7. Yang, Hongming & Liang, Rui & Yuan, Yuan & Chen, Bowen & Xiang, Sheng & Liu, Junpeng & Zhao, Huan & Ackom, Emmanuel, 2022. "Distributionally robust optimal dispatch in the power system with high penetration of wind power based on net load fluctuation data," Applied Energy, Elsevier, vol. 313(C).
    8. Sun, Lingling & Qiu, Jing & Han, Xiao & Yin, Xia & Dong, Zhao Yang, 2020. "Capacity and energy sharing platform with hybrid energy storage system: An example of hospitality industry," Applied Energy, Elsevier, vol. 280(C).
    9. Bai, Yuyang & Chen, Siyuan & Zhang, Jun & Xu, Jian & Gao, Tianlu & Wang, Xiaohui & Wenzhong Gao, David, 2023. "An adaptive active power rolling dispatch strategy for high proportion of renewable energy based on distributed deep reinforcement learning," Applied Energy, Elsevier, vol. 330(PA).
    10. Li, Jiawen & Yu, Tao & Zhang, Xiaoshun, 2022. "Coordinated load frequency control of multi-area integrated energy system using multi-agent deep reinforcement learning," Applied Energy, Elsevier, vol. 306(PA).
    11. Zhou, Xiaoqian & Ai, Qian & Yousif, Muhammad, 2019. "Two kinds of decentralized robust economic dispatch framework combined distribution network and multi-microgrids," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    12. Wang, Kaifeng & Ye, Lin & Yang, Shihui & Deng, Zhanfeng & Song, Jieying & Li, Zhuo & Zhao, Yongning, 2023. "A hierarchical dispatch strategy of hybrid energy storage system in internet data center with model predictive control," Applied Energy, Elsevier, vol. 331(C).
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    1. Shi, Jiantao & Guo, Ye & Wu, Wenchuan & Sun, Hongbin, 2024. "Scenario-oriented multi-area joint market clearing of energy and reserve under uncertainty," Applied Energy, Elsevier, vol. 361(C).

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