基于自适应遗传算法的分布式电源多目标功率优化与模糊决策

Multi-objective Optimization of Distributed Generation Based on Self-adaptive Genetic Algorithm and Fuzzy Decision

主要研究了自适应遗传算法及模糊决策在微电网中分布式能源功率优化分配中的应用,以减小节点电压偏移、线路损耗、运行成本、安装成本和充分利用可再生能源等为目标函数优化了分布式发电功率,并采取了模糊决策作为筛选最终解的方法。算法中对变种群规模,变异概率、选择、标定等都采用了自适应机制,有效提高了算法的性能。结果表明,该算法能够找到功率优化解,确实提升了微电网运行的各项性能,在微电网的能量管理系统中有一定的应用价值。

This essay mainly researched the application of self-adaptive genetic algorithm and fuzzy decision in multi-objective optimization of distributed generation in microgrid. Five objective functions are taken into account：voltage offset,transmission loss,running cost,installation cost and maximum the advantages of renewable energy,and fuzzy decision is used to decide the final solution. In the algorithm,self-adaptation in population size,mutation probability,selection and standardization of objective functions are developed to enhance the speed and efficiency of the algorithm. The result shows this algorithm can find the optimal solution effectively and improves the operation of microgrid in deed,so that some application potential can be seen in microgrid energy management system.