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

• Published in: Energy (Oxford) Vol. 277; p. 127722
• Main Author: Basu, Mousumi
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.08.2023
• Subjects: algorithms; batteries; Biomass-fuel-fired micro-cogeneration unit; Diesel generators; electric power; fuels; heat; Microgrid; Small hydro power plant; Solar micro-cogeneration unit; thermal energy; water power; Wind turbine generators; wind turbines; wolves; Diesel generators; Biomass-fuel-fired micro-cogeneration unit; Microgrid; Wind turbine generators; Solar micro-cogeneration unit; Small hydro power plant
• ISSN: 0360-5442
• DOI: 10.1016/j.energy.2023.127722

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. •Heat and power scheduling of remote microgrid for different scenarios is presented.•Fuel constraints of diesel generators are taken into consideration.•Solar micro-cogeneration and biomass micro-cogeneration units are incorporated alternately.•Elephant clan optimization algorithm has been used for solving the problem.•am the sole author of this article.