基于改进海鸥算法的配电网分布式电源优化配置

Optimal Configuration of Distributed Generation in Distribution Network Based on Improved Seagull Optimization Algorithm

摘要:

为了提高含分布式电源（DG）配电网运行的经济性和稳定性，提出了一种基于改进海鸥算法（ISOA）的配电网DG优化配置方法。将配电网网损、系统电压偏差指标和DG投资成本组成多目标函数，采用层次分析法确定各子目标权重，将多目标函数转化为单目标函数，建立了以单目标函数最小的分布式电源优化配置模型。利用精英反向学习策略和莱维飞行策略对海鸥优化算法进行改进，以提高ISOA的全局搜索性能。采用ISOA对单目标函数进行优化，优化后所得配电网网损、DG投资成本和系统电压偏差指标均优于其他优化算法，验证了所提配电网DG配置方法的实用性和优越性。

Abstract:

In order to improve the economy and stability of distribution network operation with distributed generation (DG), an optimal configuration method for distribution network with DG based on the improved seagull optimization algorithm (ISOA) is proposed. A multi-objective function is composed of distribution network losses, system voltage deviation indicators and DG investment costs, and the analytic hierarchy process is used to determine the weights of each sub objective. Then the multi-objective function is transformed into a single objective function, and an optimal configuration model for DG with the smallest single objective function is established. Elite reverse learning strategy and Levy flight strategy are used to improve the seagull optimization algorithm so as to improve the global search performance of ISOA. The single objective function is optimized using ISOA, and the obtained distribution network losses, DG investment costs and system voltage deviation indicators after optimization are superior to other optimization algorithms, which verifies the practicality and superiority of the proposed DG configuration method.