A particle swarm optimization algorithm based collaborative optimal scheduling for multi-level water basin in non-flood season

Rong Li, Lijun Cheng, Wei Wang, Yongsheng Ding
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引用次数: 2

Abstract

Water resource optimization has become an important issue due to water shortage in recent years. In the paper, we build a collaborative model for optimal water scheduling. It considers many real factors in scheduling reasonably, including domestic water, ecological water, production water, agricultural water and their backwater et al. In the model, all the factors determine the minimum required water and control section flow in river. When a water control system monitors the fact that water flow in control section is lower than the minimum required water flow. The multi-reservoirs water dispatching which based on collaborative particle swarm optimization is activated to solve the contradiction among different water demanding, especially in the peak of agricultural water in non-flood. The experiment result shows that the model in practice is reliable.
基于粒子群算法的非汛期多级流域协同优化调度
近年来,由于水资源短缺,水资源优化已成为一个重要问题。在本文中,我们建立了一个最优用水调度的协同模型。合理调度考虑了生活用水、生态用水、生产用水、农业用水及其回水等诸多现实因素。在该模型中,各因素确定了河流的最小需水量和控制断面流量。当水控制系统监测到控制段的流量低于所需的最小流量时。激活了基于协同粒子群优化的多水库水资源调度,解决了不同用水需求之间的矛盾,特别是在非汛期农业用水高峰期。实验结果表明,该模型在实际应用中是可靠的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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