Scenario-based fuel-constrained heat and power scheduling of a remote microgrid

Abstract

This manuscript suggests elephant clan optimization (ECO) algorithm to solve heat and electric power scheduling of a remote microgrid (MG) for three different scenarios considering fuel constraints. ECO algorithm is a populace-based method motivated by the elephants’ behaviour and their societal organization. MG comprises diesel generators (DGs), small hydro power plants (SHPPs), wind turbine generators (WTGs), solar micro-cogeneration (SMC) unit, biomass-fuel-fired micro-cogeneration (BMC) unit, battery energy storage system (BESS), plug-in electrical vehicles (PEVs) and thermal energy storage system (TESS). BMC units and SMC units are incorporated alternately into the MG. Numerical results of a typical system are compared with those obtained from self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients (HPSO-TVAC) and grey wolf optimization (GWO). It is seen from the evaluation that ECO offers superior solution.