基于改进粒子群算法的配电网无功优化的研究

针对电力系统无功优化问题多变量、不连续、非线性的特点,本文建立了以系统年运行费用最小为目标函数、以有功功率和无功功率为约束条件的数学模型,并应用改进的粒子群算法对无功优化问题进行求解.该算法在权重系数和不活动粒子两方面进行改进,有效地解决了进化过程中陷入局部最优和搜索精度差的特点.最后,通过对IEEE30节点系统进行无功优化算例分析,仿真结果验证了该算法解决电力系统无功优化问题的有效性和可行性.

Research of Reactive Power Optimization Based on Improved Particle Swarm

In view of the characteristics of too many variables,discontinuousness and nonlinearity of the reactive power optimization,this paper established a mathematical model system whose objective function is the minimum annual operating cost and whose constraint conditions are active power and reactive power.The model applied improved the particle swarm algorithm to solve the problem of reactive power optimization.The algorithm improved the weight coefficients and inactive particles to solve the disadvantages of the local optimum and the poor search accuracy in the evolutionary process.Finally,by analyzing IEEE30 nodal systems with the examples of reactive power optimization,the results of simulation proved the effectiveness and feasibility of the algorithm to solve reactive power optimization.