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

Fang, Ruiming; Popole, Zouthi

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

2020

Fang, Ruiming | Popole, Zouthi

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.

Показать больше [+]