基于遗传算法的无功优化与控制【精品毕业设计】(完整版)Word文档格式.docx

1、班专201 年 月班所在院（系）:完成日期:摘要电力系统无功功率的有效优化与合理控制既能提高电力系统运行时的电压质量，也能有效减少网损，节约能源，是保证电力系统安全经济运行的重要措施, 对电网调度和规划具有重要的指导意义。无功优化的核心问题主要集中在数学模型和优化算法两方面，其中数学模型问题是根据解决问题的重点不同来选取不同的目标函数；而优化算法的研究则大量集中在提高计算速度、改善收敛性能上。本文选取有功网损最小作为数学模型的目标函数，数学模型的约束条件有各节点的注入有功、无功功率的等式约束和各节点电压、发电机输出无功功率、可调变压器变比、并联补偿电容量、发电机机端电压均在各自的上下限之内的不

2、等式约束，优化方法采用遗传算法。设计和编制了牛顿拉夫逊直角坐标matlab潮流计算程序以及遗传算法无功优化的matlab潮流计算程序。通过 IEEE30节点系统的算例分析，得出基于遗传算法的无功优化能有效降低系统网损、提高电压水平，验证了该算法在解决多变量、非线性、不连续、多约束问题时的独特优势，并指出了该算法的不足之处以及如何改善。关键词：牛顿拉夫逊法，无功优化，遗传算法REACTIVE POWER OPTIMIZATION BASED ON GENETIC ALGORITHMABSTRACTReactive power with reasonable optimization and co

3、ntrol of Power system can not onlyimprove the stability ofpower system, but also effectively reduce network losses and saveenergy. It ensures the safety and economic operation of power systems and improve thevoltage quality. It is important for planning departments on grid reactive power scheduling.

4、Reactive power optimization focuses on mathematical models and optimization algorithms.The mathematical model is selected depending on the focus of problem-solving. Optimizationalgorithm is concentrated in improving the calculationspeed and improve theconvergenceperformance. This paper selects the a

5、ctive power loss minimum objective function as amathematical model, the constraints of mathematical model are each node of the injectedactive and reactive power equality constraint and the node voltage and reactive power ofgeneratoroutput, adjustabletransformer ratio,parallelcapacitancecompensation,

6、thegenerator terminal voltage within the respective upper and lower limits of the inequalityconstraints, optimizationmethod usinggenetic algorithms.Design Cartesian coordinateNewton Raphson power flow calculation method and genetic algorithm matlab calculate thereactive power optimization procedures

7、. Through a numerical example of the IEEE 14 nodesystem, we can draw reactive power optimization based on genetic algorithm can effectivelyreduce system loss and improve voltageleveland verify the algorithmhave uniqueadvantages to solve multivariable, nonlinear, discontinuous, multi-constraint probl

8、em.Key words: Newton Raphson method; reactive power optimization; genetic algorithm目录1 绪论.1.1.1 背景与意义.1.1.2 现状和发展趋势.1.2 电力系统潮流计算问题及其方程求解方法.3.2.1 电力网络方程.3.2.2 节点导纳矩阵.4.2.2.1 形成节点导纳矩阵.4.2.2.2 节点导纳矩阵的修改.5.2.3 功率方程及其迭代解法.7.2.3.1 功率方程.7.2.3.2 变量的分类.8.2.3.3 节点的分类.1.0.2.4 牛顿-拉夫逊法潮流计算方法112.4.1 牛顿-拉夫逊法112.4.2 牛顿-拉夫逊法潮流计算过程.1.2.2.4.3 潮流计算的基本流程.1.5.2.5 牛顿拉夫逊法潮流计算程序源代码.1.6.3 电力系统无功优化问题及其遗传算法优化求解.1.7.3.1 无功优化问题描述及其模型.1.7.3.2 遗传算法的理论基础.1.8.3.3 遗传算法基本原理及操作过程.1.9.3.3.1 适应度函数定标.1.9.3.3.2 初始解的形成.