Researches Of Paralleled Reactive Power Optimization Algorithm Based On Subarea Division Of The Power Systems

The appearance of hierarchic voltage control greatly improves the security and economic efficiency of power system. As significant section of hierarchic voltage control existing reactive power optimization algorithm is facing the new challenge. How to improve the real-time effect of reactive power optimization algorithm already becomes a significant subject that is necessary to be solved timely.Actual power system mostly adopt partition balancing of reactive power/voltage. Through solving distributed feature of the power system, this dissertation brings forward the paralleled reactive power optimization algorithm based on subarea division of the power systems from the parallel computation angle. This algorithm realizes the distributed parallel reactive power optimization in coarse particle size, and greatly improves the degree of parallelism.How to ensure the independence of parallel computation Among all subareas is a significant problem. Therefore this dissertation applies auxiliary problem principle and constitutes auxiliary problem to avoid appearing cross-product between varied variable. Consequently augmented quadratic term of augmented Lagrangian function no more impact on the division of the power system. In this way the power system could be divided into several completely independent areas. But the parallel computation of the power system could bring multi-balance bus problem. So ?-variable idea is introduced to solve this problem. Here, every bus voltage phase is regarded as a ?-variable which can be coordinated through intermediate variable. In this way all bus voltage phase realize uniform. The amendment iteration formula of parallel reactive power optimization is acquired Through deduction.Optimization of each subarea is completely independent, so the optimization algorithm of each subarea may be different. Here, the direct nonlinear primal-dual interior point algorithm is adopted in each subarea. This algorithm has many merits. But it is not good at handling discrete variables and appears infeasible solution constantly. So the dissertation improves this algorithm for its shortcomings. At first, discrete variables are handled through using quadratic penalty function. And then soft constraints are handled through fuzzy membership functions. These methods could availably avoid appearing infeasible solution and improve convergence reliability of the algorithm.Finally this algorithm is tested by IEEE 118-bus system. Through analyzing the result of optimization , it is proved that this algorithm is feasible and practical.