基于多目标混沌粒子群算法的矿区电网无功优化

Reactive Power Optimization of Mining Area Power Grid Based on Multi-Objective Chaotic Particle Swarm Algorithm

为了提高矿区电网电能质量,降低电网线路有功网损,在无功优化基本数学模型的基础上,综合系统电压的静态稳定性,建立了多目标无功优化数学模型。针对粒子群优化算法在进化中易出现早熟收敛等问题,引入混沌粒子群优化算法。以IEEE30节点系统为算例,验证了多目标混沌粒子群算法的可行性。将该算法应用于矿区电网无功优化中,仿真结果进一步验证了该算法的有效性。

In order to improve the electrical energy quality of mining area power grid and reduce active power loss of power grid line, on the basis of basic model of reactive power optimization, combining the static stability of system voltage, a multi-objective reactive power optimization mathematical model was established. Aiming at the problems that the particle swarm optimization algorithm in evolution is easy to occur premature convergence, the chaotic particle swarm optimization algorithm was introduced. An IEEE 30 node system was taken as an example to verify the multi-objective chaotic particle swarm algorithm＇ s feasibility. The algorithm was applied to the reactive power optimization of mining power grid, and the simulation results verified the algorithm＇ s effectiveness.