基于自适应遗传算法的分布式电源优化配置

Optimal Configuration of Distributed Generators Based on Adaptive Genetic Algorithm

摘要:

针对能源互联网背景下大量分布式电源接入配电网的优化配置问题,从经济性出发,建立了以投资成本、运行维护成本、网络损耗成本和购电成本之和最小为目标的分布式电源的选址定容优化模型。利用前推回推法计算配电网络潮流,采用了自适应遗传算法对所提模型进行求解。结合IEEE 33节点构造算例进行分析,结果表明该模型在保证经济性的同时,能有效减少网络损耗并提高电压质量。

Abstract:

Aiming at the optimal configuration problem of a large number of distributed generators connected to distribution network under the background of Energy Internet,starting from economy,an optimization model for the location and capacity of distributed power generation is established with the goal of minimizing the sum of investment cost,operation and maintenance cost,network loss cost and power purchase cost. The power flow of distribution network is calculated by using forward and backward method,and an adaptive genetic algorithm is adapted to solve the proposed model. Combining with the analysis of IEEE 33 node structure example,the results show that the proposed model can effectively reduce the network loss and improve the voltage quality while ensuring the economy.