CHAOS enhanced Flower Pollination Algorithm for Optimal Scheduling of Distributed Energy Resources in Smart Grid

This research paper has proposed a novel meta-heuristic optimization algorithm entitled CHAOS-Flower Pollination Algorithm (CHAOS-FPA) for optimally scheduling distributed energy sources in a smart grid. The basic FPA was modified by Gauss map chaotic equations. They are used to enhance the initialized population of particles, modify step size of Levy flight and reset the position of particles beyond the constraint surface. The objective was to maximize the profit of an aggregator. The proposed method has been tested on 33-bus distribution system consisting of sixty-six distributed sources, ten external energy suppliers, 1 large wind unit, 15 storage units, 1800 gridable electric vehicles and 32 demand response loads. It has been compared with the basic FPA, Cuckoo Search Algorithm (CSA) and Differential Search Algorithm (DSA). The simulation results showed that it gave better results than other methods.