改进粒子群算法在无功优化中的应用

Application of Reactive Power Optimization based on Improved Particle Swarm

针对电力系统无功优化的特点,本文提出以有功网损最小为目标函数,以负荷节点电压质量和PV发电机节点无功出力为罚函数,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缺点。最后,将改进后的粒子群算法应用于IEEE14节电力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。

According to the features of reactive power optimization in power system, this paper establishes 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 applies improved particle swarm algorithm to solve the problem of reactive power optimization. The algorithm improves 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 IEEEI4 nodal systems with the examples of reactive power optimization, the results of simulation proves the effectiveness and feasibility of the algorithm to solve reactive power optimization.