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Short-Term Hydro Generation Scheduling of the Three Gorges Hydropower Station Using Improver Binary-coded Whale Optimization Algorithm

Abstract

The short-term hydropower generation scheduling (STHGS) is a complicated problem in the utilization of hydropower and water resources. An improved binary-coded whale optimization algorithm (IBWOA) is proposed in this paper to solve the complex nonlinear problem. The STHGS problem is divided into unit combination (UC) subproblem and economic load distribution (ELD) subproblem. For the UC subproblem, we use the sigmoid function (SF) to generate a binary array representing the start/stop state of the unit. The whale algorithm's search mechanism is optimized, and the inertia weight and perturbation variation strategy are introduced to improve the algorithm's optimization ability. Each generation solution is optimized by repairing the minimum uptime/downtime constraint and the spinning reserve capacity constraint. For ELD subproblem, the optimal stable load distribution table (OSLDT) is used to distribute the load quickly. The Mutation mechanism and the Locally balanced dynamic search mechanism compensate for the non-convex problems caused by start-stop constraints and stable optimal table methods. Finally, the proposal is applied to solve the STHGS of the Three Gorges Hydropower Station. When the water head is 75 m,88 m, and 107 m, the minimum water consumption calculated by the IBWOA algorithm is 1,058,323,464 m3, 892,524,696 m3, and 745,272,216 m3, respectively. Compared with the traditional whale optimization algorithm, the water consumption of the IBOWA algorithm corresponding to 75 m, 88 m, and 107 m water heads is reduced by 0.76%, 0.26%, and 0.05%, respectively. The comparison between the IBWOA algorithm and other heuristic algorithms shows that the IBWOA has good feasibility and high optimization accuracy.

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Funding

The achievement is supported by the National Key Basic Research Program of China (973 Program) (2012CB417006) and the National Science Support Plan Project of China (2009BAC56B03).

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Conceptualization and material preparation: Kan Yang; Methodology, data collection, modeling process and analysis: Kun Yang.

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Correspondence to Kan Yang.

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Yang, K., Yang, K. Short-Term Hydro Generation Scheduling of the Three Gorges Hydropower Station Using Improver Binary-coded Whale Optimization Algorithm. Water Resour Manage 35, 3771–3790 (2021). https://doi.org/10.1007/s11269-021-02917-0

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Keywords

  • Short-term hydropower generation scheduling
  • Whale optimization algorithm
  • Adaptive inertia weight
  • Perturbation mutation strategy
  • Optimal stable load distribution table