Co-ordination Among Multiple Hybrid AC/DC Microgrids for Optimal Power Sharing and Power Management Based on Multi Objective Particle Swarm Optimization

Distributed power generation inside a single microgrid system (MGS) which is composed of renewable energy resources (RERs) like PV and Wind, and distributed generators (DGs) based on natural resources like gas and diesel engine is inevitable for many drawbacks. Since power generation inside a single MGS is increasing day by day with increased load demand, which is causing high penetration of distributed energy resources (DEGs). This increased penetration of DERs inside a single MGS causes 1) control and technical issues, 2) less utilization of individual DER, and 3) need to use a large number of electrical storage system (ESS) for emergency backup, especially in PV and Wind based MGS, which results in high-cost power generation. A solution to these above-mentioned issues is to have geographically closed interconnected multiple microgrid system (IMMGS). This IMMGS will make possible power-sharing among multiple microgrids (MMGs). One of the main issues of this IMMGS is to make the power-sharing process among MMGs optimal and economical. So, this study is about an IMMGS for optimal power sharing among geographically closed multiple microgrids. This paper presents an energy management system (EMS) and optimal power-sharing concept based on multi-objective particle swarm optimization (MOPSO) among multiple microgrids, including AC/DC hybrid microgrids both in islanded and grid connected modes of operation. This study will ensure 1) the optimal power-sharing among IMMGS, 2) minimization of load curtailment inside individual microgrids, 3) maximum utilization of DERs/RERs for economical power generation, and 4) minimum use of ESS for low-cost power generation. For multiple microgrids interconnection mesh topology has been selected because of the highest reliability and flexibility. The simulation and coding part has been done in MATLAB. Simulation results at the end of this paper showed that whenever any microgrid is in underload condition other microgrids with excess power generation will support that microgrid, but which microgrid is able to support will depend on the selection of MOPSO based on the three objective functions. In each case MOPSO selected the best microgrid for optimal power sharing.