基于改进二进制粒子群与动态微增率逐次逼近法混合优化算法的水电站机组组合优化

Hydroelectric unit commitment optimization based on improved BPSO algorithm combined dynamic successive approximation method

针对水电站机组组合问题具有高维、非凸、离散、非线性等特点,提出了一种适用于求解大容量、多机组巨型水电站机组组合问题的改进二进制粒子群优化算法,改进了粒子概率变换和位置更新方程,使其具有更强的全局寻优能力和更快的收敛速度。通过将改进二进制粒子群算法与动态微增率逐次逼近法混合嵌套,分别对水电站外层机组组合和内层机组间负荷分配进行交替迭代优化来求解水电站机组组合问题。同时引入启发式机组最短开停机时间修补策略和基于机组启停优先顺序表的系统备用容量修补技术,有效处理了多重约束条件,提高了算法的收敛速度和寻优能力。以三峡水电站为工程应用背景进行了实例研究,并与DP和BPSO算法以及实际耗水量进行了比较分析,结果表明所提算法简单快速,优化效果较好,具有较强的工程实用价值。

For the unit commitment problem of hydroelectric plant that has the characteristics of high-dimension, non-convex, discretization and non-linearity,an improved binary particle swarm optimization algorithm is presented,which is suitable for solving unit commitment problem of large-capacity and multi-unit giant hydroelectric plant.This method has better global optimization ability and faster convergence speed for using a new probability of transformation equation and particle position update equation.The proposed method takes the improved binary PSO for the outer unit combination and the dynamic successive approximation of increment rate for inner economic load dispatch.The economic operation of hydroelectric plant is solved by the two internal and external sub-problems alternating iterative updates.Meanwhile,heuristic unit minimum up/down time repair strategy and system reserve capacity repair technique based on priority of unit commitment is used to deal with constraints that effectively improve the convergence speed and optimization capability.The proposed method is applied to solve the unit commitment of the Three Gorges Hydroelectric plant.Compared with DP,original BPSO and actual water consumption,the results show that this method is easier and faster and has better global optimization ability with a strong practical engineering value.