摘要快速合理地确定黑启动路径对电力系统恢复控制具有重要的现实意义。当前对黑启动路径优化的研究多采用随机初始化的智能算法，求解速度大幅度提高却容易陷入局部最优。

本文以遗传算法为例，首先结合具体算例从初始种群的规模、多样性和连通性三个方面分析了初始种群对黑启动路径智能优化方法的影响；然后借鉴正交实验设计思想引入一种适用于黑启动路径智能优化的初始种群生成方法，提高初始种群多样性，有效避免智能算法收敛于局部最优解；此外，本文针对大规模系统的寻优效率问题对方法进行了改进，大幅度缩减了初始种群的规模，提高了算法的寻优效率；最后，通过对IEEE系统的仿真对比分析，验证了本文所提初始种群设定方法的有效性。82936

毕业论文关键词   电力系统黑启动   黑启动路径优化    初始种群设定    正交实验设计   遗传算法 

毕业设计说明书外文摘要

Title   Intelligent Optimization Method of Black Start Path Considering   the Influence of Initial Population                         

Abstract Determining the black start path fast and reasonably has an important and practical significance for power system to recover control。 Current research on black start path optimization usually use Intelligent Algorithm with random initialization。 This algorithm improves the speed of problem solving greatly, but it is easy to fall into local optimal solution 

In order to analyze the influence of initial population on intelligent optimization method better, this paper applies Genetic Algorithm as an example。 Firstly, this paper tells the influence of initial population on intelligent optimization method of black start path from three aspects: size, persity and connectivity。 Secondly, this paper introduces a method of population initialization based on orthogonal experimental design。 This method increases the persity of initial population, which avoids the Intelligent Algorithm converging to local optimal solution effectively。 In addition, this paper improves the method from the aspect of optimization efficiency for large-size system。 It reduces the initial population size greatly, and improves the optimization efficiency。 Finally, this paper verifies the effectiveness of the method proposed above to set initial population with simulation of IEEE systems。

Keywords  Power system black start   Black start path optimization   Initial population set   Orthogonal experiment design   Genetic Algorithm

目   次

1  绪论 1

1。1  研究背景与意义 1

1。2  国内外研究现状 1

1。3  本文主要研究内容 5

2  初始种群对智能寻优结果的影响分析 7

2。1  遗传算法概述 7

2。2  应用于黑启动路径优化的传统遗传算法构建 7

2。3  初始种群设定对寻优结果的重要性分析 8

2。4  初始种群设定对黑启动路径优化的影响分析 9

2。5  本章小结 16

3  基于正交实验设计的初始种群生成方法 17

3。1  正交实验设计 17