Analysis Of Reactive Power Optimization In Power System

Reactive power optimization is a traditional subject in power system operation and control. It is not only an effective means to ensure power system operates securely and economically, but also one of the most important measures to reduce the transmission loss and improve the voltage quality. The study of reactive power optimization in power system is of great significance.Reactive power optimization is a large-scale nonlinear optimization problem with a large number of variables and uncertain parameters, the operating variables include continuous and discrete variables, the optimization becomes very complex. According to the characteristics of reactive power optimization, lots of algorithms are proposed. At present commonly used methods are non linear programming, linear programming, mixed-integer programming and intelligence algorithm. In these methods, primal-dual interior point method has the prominent merits. This method's advantages are that counting time has little relation with the size of problem and counting time doesn't follow the increase of the size of problem to rise distinct. So primal-dual interior point method is used widely in reactive power optimization. Reactive power optimization is a multi-object problem. Only adopting real power loss as the objective in reactive power optimization not only overlooks the voltage quality but also results the system running on limit state and significantly reduces the system's security and stability.The mathematical model of multi-objective planning has been established in this paper. The objectives consist of real power loss and voltage quality. This paper uses weighting objective function to make the multi-objective problems to transform as the simple target problem and uses primal-dual interior point method to solve the problem. In view of the fixed method of weighting's shortcoming, this paper carries on the sector analysis to system each node, according to node sensitivity coefficient different selection different weight factor, thus obtains a more appropriate optimized result.The computing results based on these systems prove that the mathematical model of multi-objective planning and the algorithm this paper uses can reduce the system real power loss and effectively, raise the systemic voltage quality level. The algorithm has a good ability of the global research and the high convergence rate and insensitive to the system scale. This paper has proved that the reactive power optimization model is correct and effective.