基于遗传算法的电力系统无功优化.docx

基于遗传算法的电力系统无功优化 目录 中文摘要1 英文摘要2 1 绪论3 1.1 问题的提出及研究意义3 1.2 国内外研究现状3 1.3 本文的主要工作4 2 电力系统无功优化模型6 2.1无功优化的模型6 2.2无功优化的目标函数6 2.3无功优化的约束条件7 3 遗传算法的原理及其解题过程9 3.1 生物进化与遗传算法9 3.2 遗传算法的特点及其优化原理9 3.3 遗传算法的解题过程11 4 算例分析14 4.1 参数设置14 4.2 结果分析16 5 总结展望19 参考文献20 附录21 PAGE \* MERGEFORMAT3 摘要：随着现代工业的发展，电能质量越来越重要。无功优化是通过对可调变压器分接头、发电机端电压和无功补偿设备的综合调节，使系统满足电网安全约束，在稳定电压的同时可以降低系统的网络损耗。由于可投切并联电容器组的无功出力和可调变压器的分接头位置是非连续变化的，因此电力系统无功优化问题是一个复杂的非线性混合整数规划问题、其控制变量既有连续变量又有离散变量，优化过程十分复杂。针对无功优化问题，人们提出了众多的求解方法，目前常用的、比较成熟的方法主要有非线性规划法、线性规划法、混合整数规划法、人工智能法等。线性规划法、非线性规划法均为单路径搜索方法，有可能会得到局部最优解。为克服这一弊端，可以采用遗传算法，它从多个初始点出发进行搜索，同一次迭代中各个点的信息互相交换，遗传算法允许所求解的问题是非线性不连续的，并能从整个可行域空间寻找最优解。同时由于其搜索最优解的过程是具有指导性进行的，从而避免了维数灾难问题。基于以上优点本文采用了遗传算法对电力系统进行无功优化，在matlab上编写程序对算例进行优化，优化结果表明算法的可行性。 关键字：电力系统；无功优化；非线性规划；遗传算法 Abstract: With the development of modern industry, power quality is becoming more and more important. Reactive power optimization is based on the adjustable transformer tap, generator terminal voltage and reactive power compensation equipment comprehensive regulation which can meet the grid security constraints, and can reduce the system network loss while stabilizing the voltage. Because of the reactive power output of the shunt capacitor bank and the position of the tap of the adjustable transformer is discontinuous the reactive power optimization problem of power system is a complex nonlinear mixed integer programming problem. Its control variables include continuous and discrete, and the optimization process is very complicated. For the problem of reactive power optimization, many methods have been put forward. The commonly used methods are nonlinear programming method, linear programming method, mixed integer programming method, artificial intelligence method, etc. The linear programming method and the nonlinear programming method are all single path search methods, and it will obtain the local optima. In order to overcome the disadvantages of them we can use the genetic algorithm. It starts from man