电力系统电压稳定与无功控制的研究
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摘要
电力系统电压稳定与无功控制的研究是电力系统规划和运行分析中的重要课题。电力系统实施无功电压控制是提高系统的电压稳定性和经济性,保证系统的供电质量,防止系统发生电压崩溃的必要措施。本文对电力系统电压稳定和电压无功控制的研究进行了系统的阐述,并着重对无功电压控制分区和无功源优化配置进行较为深入的研究。
     在对电力系统电压稳定和电压无功控制研究现状系统阐述的基础上,仿真分析了发电机励磁调节参数对电力系统动态电压稳定的影响。分级电压控制是解决现代复杂电力系统的电压控制问题较有效的方案,其首要问题是对系统进行电压控制区域划分。在最临近电压稳定临界状态点附近对系统进行分区,综合考虑了有功功率和无功功率对节点电压的影响,以欧氏空间距离定义电气距离,最后由改进的动态分区方法进行分区计算。
     无功源最佳配置是包括确定无功源配置地点、台数和补偿容量的问题。在无功电压控制分区的基础上,以无功补偿主导节点为无功源的配置地点,同时对粒子群优化算法的粒子初始化进行改进,并将遗传算法的变异算子引入到粒子群算法,再由改进粒子群算法来确定各无功源配置点的补偿容量。系统分区后再求解无功源配置问题,可以减少粒子群算法寻求解的维数,提高计算速度,有利于找到全局最优解。算例分析证实了该方法的可行性和有效性。
Research of voltage stability and reactive power control in power system is an important issue in power system dispatching and planning. Reactive voltage control is a necessary measure to improve power system voltage stability and its economy, to ensure power quality and prevent voltage collapse. The text expatiate the content of power system voltage stability and reactive voltage control, laying stress on study of voltage control partition and reactive sources allocation.
     Based on the content of power system voltage stability and reactive voltage control, Using PSAT to analyse the exciter parameters of the generator influence on the dynamic voltage stability in power system. Voltage hierarchical control is a great formula to solve the problem of the modern complex power system, and its primary concern is to partition power system into several control areas. This text proposes a new method: partition the system at voltage stability critical point, define electric distance with euclidean distance, comprehensive consider influence of active and reactive power on the node voltage, and last use the improved dynamic partitioning method to solve the problem.
     Reactive sources allocation problem includes allocation site, number and capacity of reactive sources. An optimal allocation of reactive power sources using reactive compensation pilot buses approach on the basis of system partition. The author suggest a method to improve particle swarm optimization by introducing mutation operator of genetic algorithm and changing its particle initialization. And then to calculate compensation capacity of each allocation site with the improved particle swarm optimization. System partition reduces solution dimensions and promotes computing speed of the improved particle swarm optimization method. It is convenient to tackle the problem of reactive allocation and easy to find the global optimal solution. The example verifies the feasibility and effectiveness of the method.
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