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Multi-Objective Optimal Long-Term Operation of Cascade Hydropower for Multi-Market Portfolio and Energy Stored at End of Year

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  • Haojianxiong Yu

    (Institute of Hydropower & Hydro informatics, Dalian University of Technology, Dalian 116024, China)

  • Jianjian Shen

    (Institute of Hydropower & Hydro informatics, Dalian University of Technology, Dalian 116024, China)

  • Chuntian Cheng

    (Institute of Hydropower & Hydro informatics, Dalian University of Technology, Dalian 116024, China)

  • Jia Lu

    (China Yangtze Power Co., Ltd., Yichang 443133, China)

  • Huaxiang Cai

    (Kunming Power Exchange Center, Kunming 650011, China)

Abstract

Taking into account both market benefits and power grid demand is one of the main challenges for cascade hydropower stations trading on electricity markets and secluding operation plan. This study develops a multi-objective optimal operation model for the long-term operation of cascade hydropower in different markets. Two objectives were formulated for economics benefits and carryover energy storage. One was to maximize the market utility value based on portfolio theory, for which conditional value at risk (CVaR) was applied to measure the risk of multi-markets. Another was the maximization of energy storage at the end of a year. The model was solved efficiently through a multi-objective particle swarm optimization (MOPSO). Under the framework of the MOPSO, the chaotic mutation search mechanism and elite individual retention mechanism were introduced to diversify and accelerate the non-inferior solution sets. Lastly, a dynamic updating of archives was established to collect the non-inferior solution. The proposed model was implemented on the hydropower plants on the Lancang River, which traded on the Yunnan Electricity Market (YEM). The results demonstrated non-inferior solution sets in wet, normal and dry years. A comparison in solution sets revealed an imbalanced mutual restriction between objectives, such that a 2.65 billion CNY increase in market utility costs a 13.96 billion kWh decrease in energy storage. In addition, the non-inferior solution provided various schemes for actual demands based on other evaluating indexes such as the minimum output, power generation and spillage.

Suggested Citation

  • Haojianxiong Yu & Jianjian Shen & Chuntian Cheng & Jia Lu & Huaxiang Cai, 2023. "Multi-Objective Optimal Long-Term Operation of Cascade Hydropower for Multi-Market Portfolio and Energy Stored at End of Year," Energies, MDPI, vol. 16(2), pages 1-21, January.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:2:p:604-:d:1024976
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    References listed on IDEAS

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    1. Zhang, Yuanyuan & Zhao, Huiru & Li, Bingkang & Zhao, Yihang & Qi, Ze, 2022. "Research on credit rating and risk measurement of electricity retailers based on Bayesian Best Worst Method-Cloud Model and improved Credit Metrics model in China's power market," Energy, Elsevier, vol. 252(C).
    2. White, Halbert & Kim, Tae-Hwan & Manganelli, Simone, 2015. "VAR for VaR: Measuring tail dependence using multivariate regression quantiles," Journal of Econometrics, Elsevier, vol. 187(1), pages 169-188.
    3. Cheng, Chun-Tian & Shen, Jian-Jian & Wu, Xin-Yu & Chau, Kwok-wing, 2012. "Operation challenges for fast-growing China's hydropower systems and respondence to energy saving and emission reduction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2386-2393.
    4. Shen, Jianjian & Cheng, Chuntian & Wang, Sen & Yuan, Xiaoye & Sun, Lifei & Zhang, Jun, 2020. "Multiobjective optimal operations for an interprovincial hydropower system considering peak-shaving demands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    5. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    6. Markowitz, Harry M, 1991. "Foundations of Portfolio Theory," Journal of Finance, American Finance Association, vol. 46(2), pages 469-477, June.
    7. Bin Luo & Shumin Miao & Chuntian Cheng & Yi Lei & Gang Chen & Lang Gao, 2019. "Long-Term Generation Scheduling for Cascade Hydropower Plants Considering Price Correlation between Multiple Markets," Energies, MDPI, vol. 12(12), pages 1-17, June.
    8. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    9. M. Reddy & D. Kumar, 2006. "Optimal Reservoir Operation Using Multi-Objective Evolutionary Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(6), pages 861-878, December.
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