Elephant Clan Optimization for Scenario‐Based Fuel‐Constrained Heat and Power Scheduling for Remote Microgrid

This manuscript proposes elephant clan optimization (ECO) to address heat and electric power scheduling in remote microgrids (MGs) under three distinct scenarios, considering fuel constraints. ECO is a population‐based approach influenced by the behavior and social structure of elephants. The MG consists of wind turbine generators (WTGs), biomass‐fuel‐fired micro‐cogeneration (BMC) units, diesel generators (DGs), battery energy storage systems (BESS), solar micro‐cogeneration (SMC) units, and plug‐in electric vehicles (PEVs). BMC units and SMC units are alternately integrated into the MG. Numerical results of a standard system are contrasted with those derived from a hierarchical particle swarm optimizer with time‐varying acceleration coefficients (HPSO‐TVAC), as well as gray wolf optimization (GWO). The analysis demonstrates that ECO offers an improved solution.