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

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 uni...

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Bibliographic Details
Published in:Water resources management Vol. 35; no. 11; pp. 3771 - 3790
Main Authors: Yang, Kun, Yang, Kan
Format: Journal Article
Language:English
Published: Dordrecht Springer Netherlands 01.09.2021
Springer Nature B.V
Subjects:
administrative management
Algorithms
Atmospheric Sciences
Canyons
Civil Engineering
Distribution
Downtime
Earth and Environmental Science
Earth Sciences
Economics
Environment
Feasibility studies
Geotechnical Engineering & Applied Earth Sciences
Heuristic methods
Hydroelectric power
Hydroelectric power generation
Hydroelectric power stations
Hydrogeology
Hydrology/Water Resources
Inertia
Load distribution
Load distribution (forces)
Mutation
Optimization
Optimization algorithms
Perturbation
Reserve capacity
Scheduling
water
Water consumption
water power
Water resources
whales
Whale optimization algorithm
Perturbation mutation strategy
Optimal stable load distribution table
Adaptive inertia weight
Short-term hydropower generation scheduling
ISSN:0920-4741, 1573-1650
Online Access:Get full text
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Summary: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 m 3 , 892,524,696 m 3 , and 745,272,216 m 3 , 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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ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-021-02917-0