基于粒子群算法的配网优化运行建模与仿真

Modeling and simulation of optimal operation of distribution network based on Particle Swarm Optimization

为了提升配网调度效率,针对分布式电源接入电网后的调度控制优化方法进行了研究。在主流分布式发电装置数学模型的基础上对于典型的配网调度场景进行了运行特性和约束性分析,并将配电网优化调度抽象为一个非线性变化的优化问题。以配电网节点流入功率和流出功率平衡为约束条件进行问题的数学建模,并使用粒子群算法对该问题进行优化。通过引入粒子群进化状态的评估算子,根据算法的迭代程度对惯性权重进行调节。最终构建一个包含33个节点的配网网络,仿真结果表明,在进行配电网调度优化时,改进后的算法相较于基本的粒子群算法的收敛速度可以提升约3倍。

In order to improve the dispatching efficiency of the distribution network,the dispatching control optimization method after the distributed generation is connected to the power grid.Based on the mathematical model of mainstream distributed generation devices,the operation characteristics and constraints of typical distribution network scheduling scenarios are analyzed,and the distribution network optimal scheduling is abstracted as a nonlinear optimization problem.The mathematical model of the problem is established based on the balance of inflow power and outflow power of distribution network nodes,and the Particle Swarm Optimization is used to optimize the problem.By introducing the evaluation operator of evolution state of Particle Swarm Optimization,the inertia weight is adjusted according to the iteration degree of the algorithm.Finally,a distribution network with 33 nodes is constructed.The simulation results show that the convergence speed of the improved algorithm can be improved about 3times compared with the basic particle swarm optimization algorithm.