ABSTRACT
This chapter examines the Predator-prey Coevolution multi-objective optimization algorithm based on crowding distance to optimize the static voltage stability and power factor of micro grid operation. The optimization results show that the micro grid has good voltage stability, a small network loss and high power factor effect. The algorithm is a new optimization method of micro grid restraining multi-objective optimization. The Predator-prey Coevolution algorithm is applied to micro grid energy management optimization system. Micro grid, as an organic component of the smart grid, is based on the distributed generation and fused energy storage device, control device Integrated unit and protection device. The algorithm uses the Predator bodies as external population to achieve elitist strategy, and puts forward the concept of Predatorbody activity according to the crowding distance of none dominated. According to the proportion of clones the crowding distance activity of Predatorbody, recombination and mutation operation, in order to strengthen the front end when Pareto- is sparse region search.
