The growth of load or depreciation resulting from load shifting and peak shifting are two major phenomena observed when an epidemic or pandemic strike. Robust and reliable power and energy management system becomes the need of the hour to meet the load variation. Hence, in this work, a power and energy management system for an isolated microgrid using fuzzy based controller considering a real-time load growth scenario is illustrated. The microgrid consists of renewable energy technologies (RETs) utilizing the locally available resources (solar and wind) and lead-acid battery as storage and diesel generator as backup. The selection and sizing of the microgrid’s various elements are carried based on the load determined and predicted before the pandemic. An intelligent fuzzy-based controller (IFBC) is designed to manage the power flow between the microgrid elements efficiently. IFBC can deal with the system’s uncertainties through an IF-THEN rule-based approach, reducing mathematical modeling requirements. Further, it is robust to the load variations and operates without boundary conditions. The modeled IFBC has three input variables and two outputs. The input variables of the IFBC are total available power from RETs, total existing load demand, and the difference between power from generation and connected load. Fuzzy logic controller (FLC) output is power, fed to the load and battery energy storage system (BESS) for compensating the gap between power demand and supply and meeting the demand to keep the batteries at minimum SOC of 20%. The analysis presented in this work is based on the actual load data collected from a remote village in India before and during the pandemic, demonstrating the proposed controller’s effectiveness.
Keywords Microgrid, renewable energy, COVID 19 impact, pandemic