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基于改进粒子群算法的水电水库多目标优化调度模型。

Multi-objective optimized scheduling model for hydropower reservoir based on improved particle swarm optimization algorithm.

机构信息

Department of Electrical Engineering, Huaqiao University, Xiamen, 362021, China.

出版信息

Environ Sci Pollut Res Int. 2020 Apr;27(12):12842-12850. doi: 10.1007/s11356-019-04434-5. Epub 2019 Feb 4.

Abstract

In order to make hydropower station's development and operation harmonious with ecological protection, the optimal operation of hydropower stations to meet the needs of ecological protection is studied. Firstly, the ecological protection function of river course is defined according to the minimum ecological runoff and suitable ecological runoff. Then, a multi-objective optimal running model of reservoir which can maximize the capacity of ecological protection and generation is proposed. Finally, an improved multi-objective particle swarm optimization algorithm (MOPSO), which can construct a neighborhood for each particle and choose the neighborhood optimal solution by adopting self-organizing mapping (SOM) method, is proposed to solve the model. The model is applied to the Shui-Kou Hydropower Station in Minjiang, China. The results show that the model can get the optimal schedule with balanced consideration of ecological benefits and power generation benefits, which has not a great impact on the economic benefits of reservoirs while achieving the goal of ecological environment. The research results can provide theoretical basis and concrete scheme reference for reservoir operation.

摘要

为了使水电站的开发和运行与生态保护相协调,研究了满足生态保护需求的水电站优化运行。首先,根据最小生态流量和适宜生态流量来定义河道的生态保护功能。然后,提出了一种能够最大限度地发挥生态保护和发电能力的水库多目标优化运行模型。最后,提出了一种改进的多目标粒子群优化算法(MOPSO),该算法可以为每个粒子构建一个邻域,并通过采用自组织映射(SOM)方法选择邻域最优解,来求解该模型。该模型应用于中国闽江的水口水电站。结果表明,该模型可以在兼顾生态效益和发电效益的基础上得到最优调度方案,在实现生态环境目标的同时,对水库的经济效益影响不大。研究结果可为水库运行提供理论依据和具体方案参考。

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