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5 October 2020 Study on Generation Scheduling of Cascade Hydropower Stations Based on SAPSO
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Abstract

Yi, M.; Mo, L., and Shen, Q., 2020. Study on generation scheduling of cascade hydropower stations based on SAPSO. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 371–378. Coconut Creek (Florida), ISSN 0749-0208.

With the reduction of energy and the reform of China's electric power system, it is of great help to develop clean energy such as hydropower to ease the lack of energy. Many methods are studied to solve the reservoir optimal scheduling problem, such as particle swarm optimization (PSO). In order to solve the premature problem and slow convergence of traditional PSO, simulated annealing particle swarm optimization (SAPSO) is proposed in this paper. The algorithm is improved by adding shrinkage factor and combining with simulated annealing algorithm. Establishing the maximum generation model, and SAPSO algorithm is used to optimize the power generation scheduling of four and ten hydropower stations. The case study shows that the application of SAPSO to solve the short-term optimal scheduling problem of cascade hydropower stations has achieved satisfactory results in effect and rationality. It provides a reliable method for the optimal operation of cascade hydropower stations.

©Coastal Education and Research Foundation, Inc. 2020
Min Yi, Li Mo, and Qin Shen "Study on Generation Scheduling of Cascade Hydropower Stations Based on SAPSO," Journal of Coastal Research 104(sp1), 371-378, (5 October 2020). https://doi.org/10.2112/JCR-SI104-066.1
Received: 10 February 2020; Accepted: 22 July 2020; Published: 5 October 2020
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