基于粒子群算法的受端电网紧急切负荷优化

针对多直流馈入受端电网的直流闭锁故障提出一种紧急切负荷优化模型和求解方法。模型兼顾安全性与经济性,以切负荷总量最小为优化目标,计及暂态频率、电压偏移、线路过载、节点切负荷量限制等约束条件,优化各节点切负荷量。针对模型非线性强导致难以直接求解的问题,基于粒子群优化算法和并行计算技术,提出粒子演化的自适应参数调整方法,提高优化算法的全局寻优能力和优化速度。以山东电网模型为例,验证算法在严重直流闭锁故障下的紧急切负荷控制有效性。

Optimization of emergency load shedding of receiving-end power grid based on Particle Swarm Optimization

An optimization model and solving method of emergency load shedding were proposed to solve the high voltage direct current (HVDC) blocking of multi-infeed HVDC receiving-end power grid. The model was established to minimize the total amount of shed loads and was constrained by transient frequency variations, voltage variations, line overloading and load capacity of each node to maintain power system stability. The optimal variable of the model was the amount of load shedding of each node. Considering that the model was nonlinear, an adaptive parameter adjustment method based on particle swarm optimization (PSO) algorithm and parallel computing was established. The method improved the global optimization and the speed of the algorithm. Shandong Power Grid model was taken as an example to verify the validity of the algorithm for emergency load shedding following HVDC blocking.