【作者】 张强；

【导师】 杨晓萍；

【作者基本信息】 西安理工大学 ， 电力系统及其自动化， 2009， 硕士

【摘要】 电力系统无功的合理分布是保证电压质量和降低网损的前提条件,电力系统中无功的优化调整,将对电力系统的安全经济运行产生重要作用。因此对电网进行无功优化,是一个既直接影响系统电压质量,又关系到电网经济运行的重要问题。在以往的无功优化计算中,对于无功功率不足和系统电压偏低的情况一直是人们关注的问题。随着对电力系统电压稳定研究的深入,研究人员认识到电压稳定与无功功率的分布有着非常紧密的联系。因此,国内外众多学者提出对传统的无功优化方法进行改进,将电压稳定问题引入无功优化,以期在改善无功潮流分布的同时提高系统的静态电压稳定性。本文采用了基于广义Tellegen定理的静态电压稳定判据,建立了考虑静态电压稳定性的无功优化数学模型。对无功优化问题的求解本文采用遗传算法。针对遗传算法容易出现早熟、局部寻优能力较差和收敛速度缓慢的问题,本文用模拟退火思想对适应度函数改进,用自适应算法对遗传算法的交叉、变异策略进行改进,采用精英保留策略,变异操作使用尾部占优原则,并把电压稳定裕度最大作为无功优化的目标函数之一,以改善电力系统的静态电压稳定性。本文采用C语言编制了实用的程序,用IEEE30节点系统进行验算,将优化结果与简单遗传算法、改进粒子群算法和协同进化算法进行比较,结果表明本文算法优化结果更优,相对于简单遗传算法有更好地收敛性,加速了算法的收敛速度,在降低网损的同时能够有效提高负荷节点的电压稳定裕度,本文还用改进遗传算法对IEEE57节点系统和胜利油田电网进行了无功优化,进一步验证了本文算法的实用性和可靠性。更多还原

【Abstract】 Rational distribution of reactive power in power system is the prior condition which can ensure voltage quality and reduce the loss. Optimization adjustment of reactive power can act on secure and economical operation of power system. So reactive power optimization of power network is an important problem which directly influences voltage quality of the system as well as which relates to economical operation of power network. During the previous calculation of reactive power and voltage in the power network, reactive power insufficiency and system under-voltage are always concerned.With the deeply study on power system voltage stability, researcher recognize that voltage stability have tight connection with the distribution of reactive power. So many home and abroad scholars proposed improving the traditional reactive power optimization algorithm. In order to enhance the static voltage stability of system while improve the distribution of reactive power flow take the voltage stability problem into reactive power optimization. In this dissertation take the static voltage stability criterion based on the generalized Tellegen’s theorem, established the reactive power optimization mathematical model which considered static voltage stability.In this paper, genetic algorithm is applied to the problem of reactive power optimization. The genetic algorithm has three disadvantages, early maturity, poor ability of local optimization, and convergence rate is slow. According to these problems this paper used simulated annealing theory modified fitness function, used adaptive algorithm to improved genetic algorithm crossover and mutation strategy, adopted the tactics of elites to keep, mutation operation used tail-prevailing principle, and taken the maximization of voltage stability margin as one of objective functions of reactive power optimization to improve the static voltage stability of power system. In this paper used C language made practical program, checked calculation on IEEE 30-bus system, compared the optimization results with simple genetic algorithm, improved partical swarm algorithm and cooperative coevolutionary approach the results showed that this paper algorithm optimization results is better, relative to simple genetic algorithm had better convergence, accelerated the algorithm convergence speed, can effectively improve the voltage stability margin of load buses while reducing the power loss, this paper used modified genetic algorithm to the IEEE 57-bus system and victory oilfield power system for reactive power optimizztion, verified the practicability and reliability of this algorithm.更多还原