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Consideration of Multi-Objective Stochastic Optimization in Inter-Annual Optimization Scheduling of Cascade Hydropower Stations

Author

Listed:
  • Jun Jia

    (College of Transportation Engineering, Nanjing Tech University, Nanjing 211899, China)

  • Guangming Zhang

    (College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211899, China)

  • Xiaoxiong Zhou

    (College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211899, China)

  • Mingxiang Zhu

    (Taizhou College, Nanjing Normal University, Taizhou 225300, China)

  • Zhihan Shi

    (College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211899, China)

  • Xiaodong Lv

    (College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211899, China)

Abstract

There exists a temporal and spatial coupling effect among the hydropower units in cascade hydropower stations which constitutes a complex planning problem. Researching the multi-objective optimization scheduling of cascade hydropower stations under various spatiotemporal inflow impacts is of significant importance. Previous studies have typically only focused on the economic dispatch issues of cascade hydropower stations, with little attention given to their coupling mechanism models and the uncertainty impacts of inflows. Firstly, this paper establishes a coupled optimization scheduling model for cascade hydropower stations and elaborates on the operational mechanism of cascade hydropower stations. Secondly, according to the needs of actual scenarios, two types of optimization objectives are set, considering both the supply adequacy and peak-shaving capacity as indicators, with the total residual load and the peak-valley difference of the residual load as comprehensive optimization objectives. Subsequently, considering the uncertainty impact of the inflow side, a stochastic optimization model for inflow is established based on a normal distribution probability. Finally, case study analyses demonstrate that the proposed model not only effectively achieves supply stability but also reduces the peak-valley difference in load, and can achieve optimized scheduling under the uncertain environment of inflow.

Suggested Citation

  • Jun Jia & Guangming Zhang & Xiaoxiong Zhou & Mingxiang Zhu & Zhihan Shi & Xiaodong Lv, 2024. "Consideration of Multi-Objective Stochastic Optimization in Inter-Annual Optimization Scheduling of Cascade Hydropower Stations," Energies, MDPI, vol. 17(4), pages 1-18, February.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:4:p:772-:d:1334270
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    References listed on IDEAS

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