Reactive Power Optimization In Distribution Networks Based On Improved Genetic Algorithm

Reactive power optimization in distribution networks is a multi-variable, multi-constrained, non-continuous, mixed nonlinear programming problem, its operating variables include continuous variables and discrete variables,so the optimization becomes very complex. Reactive power optimization mainly considers on-load tap changer, the optimal capacity of the capacitor and the voltage of generator under the steady load. Therefore, the study of the distribution network reactive power optimization is of great significance.Firstly, this paper outlines the objective and meaning of reactive power optimization in power systems, shows the basic model of reactive power optimization which including the target function, power equations constraints and variable constraint. This paper listes the existing method of distribution network power flow calculation and reactive optimization with the effective combination of economic indicators. Based on the simple genetic algorithm (SGA), this paper introduces the concept of niche biology, developes initial population generation methods to ensure the diversity of individual, and producs niche genetic algorithm method which can be used in the reactive power optimization. By calculating the affinity and fitness, this algorithm evaluates the individual and promotes or inhibits the production of individual, reduce the possibility of falling into the local optimal solution during iteration and further reduce the number of iterations.Finally, this algorithm is applied to the reactive power optimization of the typical regional distribution network in Huizhou, and the results validate the effectiveness and practicality of the mathematical model and algorithmin this paper.