Operation control, energy management, and power quality enhancement for a cluster of isolated microgrids

Several isolated microgrids (MGs) may exist in remote areas because of the geographical and/or utility investment limitations. The isolated MG has its challenges depending on its configuration, energy sources, and nature of loads resulting in power quality issues. Clustering these MGs based on their relative locations to form several clusters and interconnecting them may provide additional benefits such as improved reliability, stability, and cost-effective operation. This entails the capability of energy sharing between the energy sources through distributive MGs and the power exchange within MGs through designing an effective energy management system (EMS). In this work, a proposed EMS built on the marine predator algorithm (MPA) is presented, with its design based on a hierarchical decentralized strategy for a cluster of interconnected MGs. The criterion of the proposed EMS design encompasses two key steps. First, developing an MG central controller (MGCC) in each MG to optimally handle the use of power with large-scale hybrid distributed energy resources as well as the resolution of power quality issues. Second, the MG operator (MGO) assists in the power exchange among the cluster MGs to surmount any probable unbalance between generations and demand in the cluster's entire coverage area. To enhance the complete MG's dynamic performance, an adaptive dynamic voltage restorer (ADVR) with a proportional-inte gral-derivative (PID) controller based on MPA is employed as a supervisory controller. Different cases are studied using the MATLAB/Simulink environment. Finally, two comparative performance assessment of various optimization strategies and with other controller like fractional order PID (FOPID) are presented in order to achieve the effectiveness and robustness of the presented ADVR.(c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/ by-nc-nd/4.0/).

Automated summary

This study proposes an energy management system based on the marine predator algorithm for clustering interconnected microgrids. The system improves the reliability, stability, and cost-effectiveness of the grid through energy sharing and power exchange. Case studies and performance assessments demonstrate the effectiveness and robustness of the system.