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论文编号:ZD1368 论文字数:9820,页数:25
论文题目：基于云遗传算法的变电站选址定容研究
摘 要
云遗传算法(CGA)是借鉴遗传算法的思想，利用云模型云滴的随机性和稳定倾向性的特点所形成的一种优化遗传算法，与传统遗传算法相比，其搜索速度更快、且不易陷入局部最优解。
变电站规划是电网规划的重要组成部分，变电站的选址是否合理，直接影响到电力企业的经济效益以及电网的可靠性和安全性，并且关系到未来网架规划的优劣。本文采用云遗传算法，结合变电站选址定容模型，编制了相应的计算机程序，其运算结果表明，本文基于云遗传算法的变电站选址定容方法具有较好的站址站容寻优能力和收敛性能, 可实现无待选站址的自动寻优，能满足实际电网中大规模变电站规划的需求。
关 键 词：遗传算法；云理论；变电站选址模型；无待选站址自动寻优
Title: RESEARCH ON SUBSTATION’S SITING AND CAPACITY DETERMINATION BASED ON CLOUD GENETIC ALGORITHM
ABSTRACT
Cloud genetic algorithm (CGA) uses the idea of genetic algorithms for reference; it is an optimization genetic algorithm, which uses randomicity and stable orientation of cloud model’s droplets. Compared with traditional genetic algorithms, CGA has a faster searching speed, and is not easy to fall into local optimal solution.
Substation planning is an important part of grid planning, rationality of substation’s siting has a direct effect on the economic benefits of electric power enterprises and grid’s reliability and security, as well as pros and cons of future grid’s planning. Together with model of substation’s siting and capacity determination, this paper uses genetic algorithms to programme correspondingly; its computing results indicate that the method of substation’s siting and capacity determination based on CGA has a good optimization ability to determine substation’s site and capacity, as well as convergence performance, also it can realize automatic optimization of unavailable sites that is to be elected, and is able to meet the demand for the planning of large-scale substations in the actual power grid.
KEY WORDS: GENETIC ALGORITHM; CLOUD THEORY; MODEL OF SUBSTATION’S SITING;AUTOMATIC OPTIMIZATION OF UNAVAILABLE SITES THAT IS TO BE ELECTED
TYPE OF THESIS: a
目 录
1 前言 1
1.1 立题意义 1
1.2国内外研究现状 1
1.2.1计算机技术的应用 2
1.2.2地理信息系统的应用 2
1.2.3各类优化算法的应用 2
1.3本文主要工作 2
2基于云理论的智能优化算法 3
2.1 遗传算法 3
2.2 云理论简介 3
2.3 基于云理论的智能优化算法 3
2.3.1基本概念 3
2.3.2基本云发生器 4
2.3.3Ｙ条件云发生器 4
2.3.4云遗传算法流程 5
3基于云优化算法的配电网络变电站选址定容 7
3.1 引言 7
3.2 变电站选址的准则 7
3.3 变电站定容的准则 8
3.4 变电站选址定容的数学模型 8
3.4.1数学模型 8
3.4.2组合优化问题求解 9
3.5 算法流程图 11
3.6 变电站选址定容算例分析 11
3.6.1算例一 11
3.6.2算例二 12
4结论 16
致 谢 17
参考文献 18
