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Modeling the daily generation schedules in under-developed electricity markets with high-share renewables: A case study of Yunnan in China

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  • Liu, Shuangquan
  • Xie, Mengfei

Abstract

This paper presents a transition approach for markets with high-share renewables to connect the delivery of physical medium and long-term market contracts with daily system operation while ensuring safe and reliable grid operation given the under-developed electricity market environment in China. The proposed approach decomposes the market contracts into daily energy schedules with rolling updates of subsequent daily schedules to ensure fairness in contract delivery, then employs security-constrained economic dispatch to allocate the decomposed energy to each power plant to determine the day-ahead schedules. In the security check, a multi-section coordinating strategy is incorporated to maximize the utilization of transmission capacity and determine the optimal power flow. Results of the Yunnan case study demonstrate the feasibility and effectiveness of the proposed approach in modeling the day-ahead schedules and handling the multiple objectives and numerous constraints, and therefore provide a reference for similar hydro-dominated systems in transitioning to electricity spot markets. Finally, discussions and suggestions are proposed to promote electricity markets further.

Suggested Citation

  • Liu, Shuangquan & Xie, Mengfei, 2020. "Modeling the daily generation schedules in under-developed electricity markets with high-share renewables: A case study of Yunnan in China," Energy, Elsevier, vol. 201(C).
  • Handle: RePEc:eee:energy:v:201:y:2020:i:c:s0360544220307842
    DOI: 10.1016/j.energy.2020.117677
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    as
    1. Liu, Benxi & Liao, Shengli & Cheng, Chuntian & Chen, Fu & Li, Weidong, 2018. "Hydropower curtailment in Yunnan Province, southwestern China: Constraint analysis and suggestions," Renewable Energy, Elsevier, vol. 121(C), pages 700-711.
    2. Wang, Ke & Zhang, Xian & Wei, Yi-Ming & Yu, Shiwei, 2013. "Regional allocation of CO2 emissions allowance over provinces in China by 2020," Energy Policy, Elsevier, vol. 54(C), pages 214-229.
    3. Fang, Debin & Zhao, Chaoyang & Yu, Qian, 2018. "Government regulation of renewable energy generation and transmission in China’s electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 775-793.
    4. Yin, Yue & Liu, Tianqi & He, Chuan, 2019. "Day-ahead stochastic coordinated scheduling for thermal-hydro-wind-photovoltaic systems," Energy, Elsevier, vol. 187(C).
    5. Esmaeily, Ali & Ahmadi, Abdollah & Raeisi, Fatima & Ahmadi, Mohammad Reza & Esmaeel Nezhad, Ali & Janghorbani, Mohammadreza, 2017. "Evaluating the effectiveness of mixed-integer linear programming for day-ahead hydro-thermal self-scheduling considering price uncertainty and forced outage rate," Energy, Elsevier, vol. 122(C), pages 182-193.
    6. Hu, Jing & Harmsen, Robert & Crijns-Graus, Wina & Worrell, Ernst & van den Broek, Machteld, 2018. "Identifying barriers to large-scale integration of variable renewable electricity into the electricity market: A literature review of market design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2181-2195.
    7. Gugler, Klaus & Haxhimusa, Adhurim & Liebensteiner, Mario & Schindler, Nora, 2020. "Investment opportunities, uncertainty, and renewables in European electricity markets," Energy Economics, Elsevier, vol. 85(C).
    8. Khosravi, Abbas & Nahavandi, Saeid & Creighton, Doug, 2013. "Quantifying uncertainties of neural network-based electricity price forecasts," Applied Energy, Elsevier, vol. 112(C), pages 120-129.
    9. Valitov, Niyaz, 2019. "Risk premia in the German day-ahead electricity market revisited: The impact of negative prices," Energy Economics, Elsevier, vol. 82(C), pages 70-77.
    10. Gal, Nurit & Milstein, Irena & Tishler, Asher & Woo, C.K., 2017. "Fuel cost uncertainty, capacity investment and price in a competitive electricity market," Energy Economics, Elsevier, vol. 61(C), pages 233-240.
    11. Hogan, William W., 2015. "Electricity Markets and the Clean Power Plan," Working Paper Series 15-059, Harvard University, John F. Kennedy School of Government.
    12. Zhang, Long & Sovacool, Benjamin K. & Ren, Jingzheng & Ely, Adrian, 2017. "The Dragon awakens: Innovation, competition, and transition in the energy strategy of the People’s Republic of China, 1949–2017," Energy Policy, Elsevier, vol. 108(C), pages 634-644.
    13. Ayón, X. & Gruber, J.K. & Hayes, B.P. & Usaola, J. & Prodanović, M., 2017. "An optimal day-ahead load scheduling approach based on the flexibility of aggregate demands," Applied Energy, Elsevier, vol. 198(C), pages 1-11.
    14. Chen, J.J. & Zhao, Y.L. & Peng, K. & Wu, P.Z., 2017. "Optimal trade-off planning for wind-solar power day-ahead scheduling under uncertainties," Energy, Elsevier, vol. 141(C), pages 1969-1981.
    15. Philipsen, Rens & Morales-España, Germán & de Weerdt, Mathijs & de Vries, Laurens, 2019. "Trading power instead of energy in day-ahead electricity markets," Applied Energy, Elsevier, vol. 233, pages 802-815.
    16. Chen, J.J. & Qi, B.X. & Peng, K. & Li, Y. & Zhao, Y.L., 2020. "Conditional value-at-credibility for random fuzzy wind power in demand response integrated multi-period economic emission dispatch," Applied Energy, Elsevier, vol. 261(C).
    17. Zhang, Chi & Zhou, Kaile & Yang, Shanlin & Shao, Zhen, 2017. "On electricity consumption and economic growth in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 353-368.
    18. Zhang, Jingrui & Wu, Yihong & Guo, Yiran & Wang, Bo & Wang, Hengyue & Liu, Houde, 2016. "A hybrid harmony search algorithm with differential evolution for day-ahead scheduling problem of a microgrid with consideration of power flow constraints," Applied Energy, Elsevier, vol. 183(C), pages 791-804.
    19. Sun, Mucun & Feng, Cong & Zhang, Jie, 2020. "Multi-distribution ensemble probabilistic wind power forecasting," Renewable Energy, Elsevier, vol. 148(C), pages 135-149.
    20. Wang, Yongpei & Yan, Weilong & Zhuang, Shangwen & Zhang, Qian, 2019. "Competition or complementarity ? The hydropower and thermal power nexus in China," Renewable Energy, Elsevier, vol. 138(C), pages 531-541.
    21. Liu, Shuangquan & Yang, Qiang & Cai, Huaxiang & Yan, Minghui & Zhang, Maolin & Wu, Dianning & Xie, Mengfei, 2019. "Market reform of Yunnan electricity in southwestern China: Practice, challenges and implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
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