Step-constrained water allocation of hydropower stations based on optimal scheduling of particle swarm optimization

Shi Yuhui; Hu Fangqiang

doi:10.1117/12.2652857

20 October 2022 Step-constrained water allocation of hydropower stations based on optimal scheduling of particle swarm optimization

Shi Yuhui, Hu Fangqiang

Author Affiliations +

Proceedings Volume 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022); 1235004 (2022) https://doi.org/10.1117/12.2652857
Event: 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 2022, Qingdao, China

Abstract

Due to the unreasonable use of surface water and groundwater for a long time, the shortage of water resources has become an important factor restricting the northern country's social and economic development. As a demonstration area for Shaanxi, Shanxi and Henan to undertake industrial transfer while accelerating economic development, it also inevitably faces the realistic problem of the increasingly deteriorating contradiction between the supply and demand of hydropower stations. Considering that the traditional hydropower station configuration method will lead to deviation in results, this paper constructs a comprehensive evaluation function aiming at social benefit, economic benefit and ecological benefit based on ensuring the balance of supply and demand and establishing a more targeted hydropower station optimal configuration model, and analyzed the rationality of the configuration results through the configuration goals. The results show that the optimal allocation model conforms to the characteristics and changing trends of the multi-objective optimization model, can scientifically adjust the regional water supply structure, allocate water resources reasonably and effectively, improve the utilization level of hydropower stations, and provide support for the sustainable development of society and economy.

Citation Download Citation

Shi Yuhui and Hu Fangqiang "Step-constrained water allocation of hydropower stations based on optimal scheduling of particle swarm optimization", Proc. SPIE 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 1235004 (20 October 2022); https://doi.org/10.1117/12.2652857

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