基于多种群改进差分进化算法的环境／经济电力调度优化

应用多种群改进差分进化算法求解环境/经济电力调度(Environmental/Economic Dispatch,EED)这一多目标优化问题。将多种群策略引入差分进化算法,有助于保持群体多样性,有效避免经典差分进化算法的早熟收敛问题。采用自适应变异因子及交叉因子,使算法在搜索初期保持全局搜索能力,在搜索后期增强局部搜索能力,加快收敛速度。将该算法应用到IEEE 30节点-6机组系统的环境/经济调度优化,仿真计算结果以及与其他算法的对比分析验证了该算法的有效性。

Environmental/Economic Power Dispatch Optimization Using Multi-Tribe Modified Differential Evolution Algorithm

A multi-tribe modified differential evolution algorithm is presented for solving environmental /economic dispatch(EED)multi-objective optimization problem.The multi-tribe strategy is introduced into differential evolution algorithm , to maintain the diversity of the group , and effectively avoid the premature convergence problem in classical differential evolution algorithm .The adaptive mutation and crossover factors are used to keep the global searching ability in the early stage , and to enhance the local searching ability in the late stage to accelerate convergence .The algorithm is applied to obtain environmental/economic power dispatch optimization solutions for the IEEE 30-bus system and 6-unit system.The results obtained are compared with other algorithms to verify the effectiveness of the proposed algorithm .