基于改进遗传算法的主动配电网经济优化调度

Economic Optimal Dispatch of Active Distribution Network Based on Improved Genetic Algorithm

随着风能、太阳能等可再生能源的大规模开发,可再生能源并网给电力系统安全性和稳定性造成了一定威胁,也给配电网经济调度带来了巨大挑战。针对含多种能源和储能系统的主动配电网(ActiveDistributionNetworks,ADN)经济调度问题,综合考虑ADN运行过程中产生的购电成本、运行维护成本、折旧成本、损耗成本、售电收益等各项成本及约束条件,建立以ADN总成本最小为目标函数的ADN经济优化调度模型。为了提高ADN经济优化调度模型的计算精度,对遗传算法的交叉概率和突变概率进行改进,形成改进遗传算法,利用改进遗传算法对ADN经济优化调度模型进行求解,结果表明,改进遗传算法能够明显加快目标函数收敛,提高ADN经济优化调度的经济性。

With the large⁃scale development of renewable energy such as wind energy and solar energy,the grid connection of renewable energy has posed a certain threat to the security and stability of power system,and also brought great challenges to the economic dispatch of distribution network.Considering the cost of power purchase,operation and maintenance,depreciation cost,loss cost,sales revenue and other costs and constraints during the operation of active distribution network,an ADN economic optimal dispatch model of active distribution network with multiple energy sources and energy storage systems was established,which took the minimum total cost of active distribution network as the objective function.In order to improve the calculation accuracy of ADN economic optimal dispatch model,the crossover probability and mutation probability of genetic algorithm were improved to form an improved genetic algorithm.The economic optimal dispatch model of active distribution network was solved by using the improved genetic algorithm.The results show that the improved genetic algorithm can significantly accelerate the convergence of the objective function and improve the economy of economic optimal dispatch of active distribution network.