Research On The Algorithm For The Dynamic Reactive Power Optimization Based On The PSO

The dynamic reactive-power optimization model is the reactive power optimization objective function , which the constraints of allowable operation times of the control variables are restored to economic costs which are used to construct with the cost for energy loss at the current time interval, and generally divides the load levels forecast in a day into some certain time intervals, the constrains of allowable operation times of control devices should be led into, to avoid the frequent operation of control devices. It is the extremely complicated nonlinear problem, and the optimization is rather difficult.The paper studies the mathematical model of the dynamic reactive optimization and the particle swarm optimization (PSO). For the high dimension and difficult optimization of the dynamic reactive optimization, the modified PSO is proposed by combining PSO with different evolution and death penalty to solve constrained optimization problems. It reduces the risk of being trapped into local minimums resulting from single heuristic mechanism, overcomes fault of method dealing with complicated boundary constraint by adopting a new method to cope with boundary constraint condition. The dynamic reactive optimization is be modified in some parts according to the modified PSO. The fourteen nodes power supply network of one city is used to validate the proposed algorithm. And the effect of different constraints of operation times on dynamic reactive power optimization results is analyzed respectively in detail. The result based on the proposed method is compared with that based on the static optimization and other algorithms on the same system, great success in the constraints of operation times and the total of profit, and this comparison has shown correctness and effectiveness of the proposed method.