Reactive Power Planning Based On Improved Genetic Algorithm For The Regional Power Grid Optimization

With the fast development of national economy, demand for electricity has been increasing rapidly as well. Consequently, it is very important to ensure security and economy of power system operation under such a demanding situation. However, in possession of enough power supply capacity, reasonable reactive power distribution is one of the basic conditions, which ensure electric power system to operate safely and economically. The purpose of reactive power planning optimization (RPPO) is to fix the project of reactive compensating, and it is very important for RPO to ensure the security and economy of power system operation and the quality of supply power.Genetic Algorithms (GAs) are search algorithms based on of natural evolution processing including selection, mutation and crossover operations on the genes of individuals or potential solutions. GAs are stochastic optimization algorithms and can be carried out through parallel computing. GAs do not require the optimization problem to be convex and differentiable as required by other traditional optimization techniques to find the global optimal solution. GAs has been widely applied to solving many power engineering problems over the past decades including power system planning, economic dispatch, unit commitment and fault analysis etc.Detailed analysis of RPPO problem is given in this thesis based on research content, methods, RPPO modeling and RPPO objective function used. Combined with engineering practice, this paper describes an idea about optimal reactive power planning that the amount of investment is fixed. The fundamental and advanced techniques in GAs are given in the background chapters of the thesis. An improved GA is used for RPPO problem in the thesis. According to the characteristics of reactive power planning optimization, a fully scheme of refined GA was proposed in this thesis. The main research topics of the thesis have been followed:Firstly, the mathematic model of RPPO was improved, including the establishment of objective function and the selection of constrains. This paper introduces an idea about optimal reactive power planning that the amount of investment is fixed.