Reactive Power Optimization of Power System Based on the Quantum Genetic Algorithm
|School||Southwest Jiaotong University|
|Course||Proceedings of the|
|Keywords||power system reactive power optimization genetic algorithm (GA) quantum genetic algorithm (QGA)|
With the development of national economy, the demands of power supply quality from all kinds of industries are increased. Reactive power optimization is one of the most important control methods to ensure power system operation securely and economically, and an effective measure to improve the voltage profile and reduce the transmission loss. Study the problem of reactive power optimization has the great significance in theory and practical application.Reactive power optimization is a large-scale nonlinear optimization problem with a large number of objects, variables and uncertain parameters, the operating variables include continuous and discrete variables, so the optimization becomes very complex. This paper introduces the process of development and research actuality of reactive power optimization in power system, summarizes the methods of reactive power optimization; The methods mainly include two kinds: sutra and modern. The sutra method mainly refers to definitive searchable method, the modern method involve the manpower intelligence method (especially the genetic algorithm), the tabu searchable method and the simulated anneal etc.But the methods have some defects and limitations in certain degree, this paper discusses the characteristics of reactive power optimization thorough, establishes the basic mathematical model and the object function of model is based on active power loss, and puts forward a novel algorithm-quantum genetic algorithm (QGA) which is applied to the problem of reactive power optimization of power system. Quantum Genetic Algorithm is a new optimum method that combines quantum computation with Genetic Algorithms. It uses quantum bit as coding which is different from conventional binary coding completely. QGA makes full use of superposition of quantum states to keep diversity of population and avoid prematurity of population. So it has good characteristics of strong search capability, rapid convergence and no premature. It appears strong life-force and valuable for research. It can greatly improve the computation efficiency of GA and remedy shortcoming.QGA is applied to the problem of reactive power optimization of power system, the computing results against the IEEE-14 and IEEE-30 criterion testing system prove that method of reactive power optimization based on QGA proposed in this paper is effective. Compared with the traditional genetic algorithm, QGA has good characteristics of strong search capability, rapid convergence and no premature, is superior to conventional genetic algorithms in quality and efficiency.This paper incorporates the voltage stability view to reactive power dispatch and control problem, a model of multi-objective reactive power optimization is established, which takes into account of loss minimization, voltage stability margin maximization and high service quality. The simulations are carried out on IEEE-14 bus system, and the results show the validity of the proposed model and algorithm.