Research On The Reactive Power Optimization Based On Modified Particle Swarm Optimization Algorithm

With the development of power industry, the modern power system has become more tremendous, its framework and modes of operation get to be more complex in the extreme,and the security and stability of power system have become more tremendous. Reactive power optimization (RPO) in power system is one of the most important measurements to improve the voltage quality, reduce the net real loss and ensure power system securely and stably. As the establishment and improvement of electric power market of our country, the electric power enterprise must break the conventional electric power service construction integrated with generate electricity, power transmission and power distribution. So the study on RPO is quite imperative under the power market environment.In this paper, the mathematical models of Var optimization problem are fully studied as well as its algorithm, and all kinds of methods for solving the problem are summarized. What's more, the differences and features of these methods are given in the paper. Under the background of putting forward"separation of power plant from electric network, connection to the national network by price competition", and considering the secure and practical operation of power system, a mathematic model is designed in which the cost of active power loss and cost of reactive power are taken as objective function with its all kinds of constrains.In this paper, MPSO algorithm is applied to reactive power optimization model and its program is designed with VB6.0 language. Incorporation of non–stationary multi-stage assignment penalty function, which is set up to get the maximum economic benefits, can significantly improve the global convergence and the accuracy of MPSO algorithm. Test results from the simulation and calculation on IEEE30 system and Liaoyuan power grid demonstrate the accuracy, validity andapplicability of the proposed model and algorithm.The new research result is applicable to Liaoyuan power grid, and shows that this model not only overcomes the shortage of the present reactive optimization planning under the condition of electric power market, but also makes the cost of the active power loss and the cost of reactive power payed by electric network business minimum, which provides an promising approach for the practicing of reactive power optimation control in power market in the future.