Analysis of the islanded microgrid resilience under normal and extreme events using soft computing techniques

Abstract

Analysis of the Islanded Microgrid Resilience under Normal and Extreme Events using Soft Computing Techniques Smart operational strategies are considered cost-effective through the implementation of microgrids (MGs). Their implementation can provide a continuous power supply for critical loads during these extreme choice events. It is reliable for increasing distributed system resilience against extreme disruption events because of its operational flexibility, islanding capability, and consumer engagement when a system malfunction is detected. The electrical power distribution system resilience must be enhanced to ensure continuous power during natural disasters. Smart operational strategies and system hardening may be applied to achieve this. When the power transmission and distribution network is subjected to extreme disruptions, power system hardening measures are widely used to secure the network. However, hardening the entire network will increase the overall cost. Smart operational strategies are considered cost-effective through the implementation of microgrids. The maximum capacity load considered for normal load mode is 1000 kW rating, the medium-capacity load for energy conservation is 500 Kw, whereas the critical load for an emergency is 250 kW. Their implementation can provide a continuous power supply for critical loads during these extreme events. It is a reliable choice for increasing distributed system resilience against extreme disruption events because of its operational flexibility, islanding capability, and consumer engagement when a system malfunction is detected. In this study, a bidirectional “Fuzzy Logic Controller (FLC)” has been realized to deal with system resilience during islanded grid mode/operation in the event of a major disaster as well as in normal conditions. The system involves the utilization of solar, wind, battery, and load. We propose to develop a control algorithm for the system's current state. This algorithm allows effectively boosts the resilience and makes the optimal selection between the emergency, energy conservation, and normal modes. The designed fuzzy rule-based system takes appropriate action depending on the current state of solar power, wind power, battery state of charge (SOC), and wind-solar forecast. This research work has produced simulation results in MATLAB/Simulink to demonstrate the system’s resilience in normal and abnormal conditions. Moreover, a performance comparison between the presented strategy and “Proportional Integral Derivative (PID)” controllers has been carried out. The main aim is to compare the performance of a MG’s load modes for the normal situation as well as for disrupted events. For comparison, the developed system is tested for various scenarios. From the simulation results, it is evident that the proposed FLC effectively boosts