基于混沌多目标遗传算法的微网系统容量优化

Optimization allocation of microgrid capacity based on chaotic multi-objective genetic algorithm

微网系统容量的优化配置直接影响能源的梯级综合利用效率、供电可靠性和电能质量,是微网发展所要面对的一个重要课题。在分析分布式电源功率特性的基础上,考虑微网系统中分布式电源、能源资源、储能和负载之间的复杂匹配关系,构建了经济成本、供电可靠性和环境效益的量化目标函数。将混沌优化算法与多目标遗传算法结合,提出了混沌多目标遗传算法对独立运行微网系统容量进行优化配置。算例分析验证了算法的有效性和实用性。优化后的微网系统保证了供电可靠性,节省了经济成本,降低了环境污染。

Microgrid optimization allocation directly mnuences energy comprehensive utilization efficiency supplu reliability and electrical energy quality, which is an important topic that microgrid development must face. Based on the power characteristic analysis of distributed generation, considering complex matching relations among distributed generation, energy resources, storage energy and load, the objective functions of systematic economic cost, power supply reliability and environment benefit are constructed. Chaotic multi-objective optimization genetic algorithm （CMGA） which integrates mutative chaotic optimization are multi-objective genetic algorithm is proposed to the optimization allocation of microgrid capacity. Example analysis demonstrates the efficiency and validity of CMGA. Optimized microgrid ensures power supply reliability, saves economic cost and reduces environmental pollution.