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

机译：基于改进粒子群优化算法的水电储层多目标优化调度模型

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摘要

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.
机译：为了使水电站的发展与生态保护和谐，水电站满足生态保护需求的优化运行。首先，河流课程的生态保护功能根据最低生态径流和合适的生态径流定义。然后，提出了一种能够最大化生态保护和生成能力的储层多目标最佳运行模型。最后，提出了一种改进的多目标粒子群优化算法（MOPSO），其可以构造每个粒子的邻域并通过采用自组织映射（SOM）方法来选择邻域最佳解决方案，以解决模型。该模型适用于中国岷江水电站。结果表明，该模型可以通过平衡思考生态效益和发电效益来获得最佳时间表，这对水库的经济效益产生了很大的影响，同时实现了生态环境的目标。研究结果可以为储层运作提供理论基础和具体方案参考。

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