Reactive Power Optimization In Power System Based On Ecology Evolutionary Algorithm Of Food Chain

With the rapid development of increasingly high demand on the grid. Power system reactive power sources and the rational distribution of the balance of reactive power is to ensure the quality and reducing the power loss voltage precondition for economic operation of the power system and security play a decisive role. Therefore, reactive power optimization problem for both theoretical significance, but also has real value.Reactive power optimization is a multi-variable, multi-constraint mixed nonlinear programming problem. This article describes the various optimization algorithms in the field of application of reactive power optimization, commonly used at home and abroad reactive control principle, the principle of compensation and compensation. Use the minimum power loss throughout the system as the optimization objective function, the node voltage cross-border and cross-border generator reactive power into the objective function as a penalty term. Ecological food chain using evolutionary algorithms (Ecology Evolutionary Algorithm of Food Chain) search for the optimal planning, drawing on simulated annealing search process fix individual fitness values. Ecological food chain evolutionary algorithm based on population size fitness values into high, medium and low three populations, each population’s genetic evolution using an independent way, different levels between populations through mode adjustment is completed the exchange of information and exchange between populations, global search excellent combined with local optimization, optimal preservation strategy to prevent the last individual get the best individual in later iterations disappear. In this paper, language optimization program, using the node IEEE14node system and IEEE30node system for authentication. The results prove that ecological food chain evolutionary algorithm has excellent global search ability and high accuracy.