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Effect of the quality of streamflow forecasts on the operation of cascade hydropower stations using stochastic optimization models

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  • Liu, Yuan
  • Ji, Changming
  • Wang, Yi
  • Zhang, Yanke
  • Jiang, Zhiqiang
  • Ma, Qiumei
  • Hou, Xiaoning

Abstract

Determining the economic value of streamflow forecasts is essential to judging the operation of cascade hydropower systems and investing in improved forecasting systems. Previous analyses of the streamflow forecast value are mainly based on deterministic optimization strategies. This paper investigates the impact of long-term (10-day-ahead) streamflow forecasts on the operation of a cascade hydropower system using stochastic dynamic programming (SDP) and Bayesian stochastic dynamic programming (BSDP). Synthetic streamflow forecasts with different bias, variance, and precision are generated by the generalized maintenance of variance extension approach. A case study is performed to evaluate the performance of these strategies in terms of cumulative annual power revenue (CAPR) and system reliability (SR). The results show that, even when using the forecast with the largest uncertainty and bias, the stochastic optimization strategies increase at least 6.63 × 108 CNY in CAPR and 33.89% in SR compared with a reference strategy that uses no forecast information. The SDP performs best with forecast systems that have a negative bias and high accuracy. Compared with the SDP, BSDP increases at least 1.80 CNY in CAPR and 0.28% in SR and is better able to handle forecast uncertainty, and is insensitive to forecast bias.

Suggested Citation

  • Liu, Yuan & Ji, Changming & Wang, Yi & Zhang, Yanke & Jiang, Zhiqiang & Ma, Qiumei & Hou, Xiaoning, 2023. "Effect of the quality of streamflow forecasts on the operation of cascade hydropower stations using stochastic optimization models," Energy, Elsevier, vol. 273(C).
  • Handle: RePEc:eee:energy:v:273:y:2023:i:c:s0360544223006928
    DOI: 10.1016/j.energy.2023.127298
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    References listed on IDEAS

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    1. He, Zhongzheng & Zhou, Jianzhong & Qin, Hui & Jia, Benjun & He, Feifei & Liu, Guangbiao & Feng, Kuaile, 2020. "A fast water level optimal control method based on two stage analysis for long term power generation scheduling of hydropower station," Energy, Elsevier, vol. 210(C).
    2. Gong, Yu & Liu, Pan & Ming, Bo & Li, Dingfang, 2021. "Identifying the effect of forecast uncertainties on hybrid power system operation: A case study of Longyangxia hydro–photovoltaic plant in China," Renewable Energy, Elsevier, vol. 178(C), pages 1303-1321.
    3. Cheng, Chuntian & Su, Chengguo & Wang, Peilin & Shen, Jianjian & Lu, Jianyu & Wu, Xinyu, 2018. "An MILP-based model for short-term peak shaving operation of pumped-storage hydropower plants serving multiple power grids," Energy, Elsevier, vol. 163(C), pages 722-733.
    4. Jiang, Zhiqiang & Li, Rongbo & Li, Anqiang & Ji, Changming, 2018. "Runoff forecast uncertainty considered load adjustment model of cascade hydropower stations and its application," Energy, Elsevier, vol. 158(C), pages 693-708.
    5. Qiao-feng Tan & Guo-hua Fang & Xin Wen & Xiao-hui Lei & Xu Wang & Chao Wang & Yi Ji, 2020. "Bayesian Stochastic Dynamic Programming for Hydropower Generation Operation Based on Copula Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(5), pages 1589-1607, March.
    6. Jiang, Zhiqiang & Ji, Changming & Qin, Hui & Feng, Zhongkai, 2018. "Multi-stage progressive optimality algorithm and its application in energy storage operation chart optimization of cascade reservoirs," Energy, Elsevier, vol. 148(C), pages 309-323.
    7. Ene, Seval & Küçükoğlu, İlker & Aksoy, Aslı & Öztürk, Nursel, 2016. "A genetic algorithm for minimizing energy consumption in warehouses," Energy, Elsevier, vol. 114(C), pages 973-980.
    8. P. Mujumdar & B. Nirmala, 2007. "A Bayesian Stochastic Optimization Model for a Multi-Reservoir Hydropower System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(9), pages 1465-1485, September.
    9. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2017. "Multi-objective quantum-behaved particle swarm optimization for economic environmental hydrothermal energy system scheduling," Energy, Elsevier, vol. 131(C), pages 165-178.
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    2. Shu, Xingsheng & Ding, Wei & Peng, Yong & Wang, Ziru, 2024. "Value of long-term inflow forecast for hydropower operation: A case study in a low forecast precision region," Energy, Elsevier, vol. 298(C).
    3. Zhou, Shuai & Wang, Yimin & Su, Hui & Chang, Jianxia & Huang, Qiang & Li, Ziyan, 2024. "Dynamic quantitative assessment of multiple uncertainty sources in future hydropower generation prediction of cascade reservoirs with hydrological variations," Energy, Elsevier, vol. 299(C).

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