Research On Multi-Objective Reactive Power Optimization Based On Modified Particle Swarm Optimization Algorithm

The main propose of power system reactive power optimization was to decrease the active losses of system, to enhace the voltage quality and system stability by reasonably adjusting reactive power equipment. Reactive power optimization of power system is a nonlinear programming problem with a large number of variables, aims and constraint conditions. There are a conflict between some objects and the control variables are made of continuous and discrete variables, so reactive power optimization problem is complex and hard to solve with conventional methods. Weighting method, which was a method to turn mult-objective optimization of these kinds of problems, however, because of the different physical dimension, the value of weight factor was very hard to use in different target functions. In this paper, use the concept of Pareto records to calculate the mult-objective optimization.According to the above mentioned characteristics of reactive power optimization, Multi-Objective Particle Swarm Optimization (MOPSO) algorithm has been applied to solve the two aims that are losses of system and voltage quality of reactive power optimization. PSO algorithm is a kind of heuristic algorithm based on swarm intelligence which is easy to implement and has fast convergence performance. However, the convergence precision of the basic PSO algorithm is low, and the algorithm can easily fall into its local minimum value. Aiming at these shortcomings of PSO algorithm, the paper proposed the modified MOPSO algorithm that composed of Tabu Search Multi-Object Particle Swarm Optimization (TSMOPSO). And dynamically adjust the maximum speed, to avoid fall into local minimum. When applied to classic optimization function, the TSMOPSO algorithm proves superiority in global convergence and convergence precision compared to standard MOPSO.This TSMOPSO algorithm is applied to IEEE-6, IEEE-14and IEEE-30standard systems, considering all factors affecting reactive power flow such as generator terminal voltage, output of reactive power sources and transformer tap positions, taking the real power loss and voltage safety of system as optimization goals, meeting reactive power constraints, setting different parameters in different systems to meet the different demands.