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

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  • Basu, Mousumi

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.

Suggested Citation

  • Basu, Mousumi, 2023. "Scenario-based fuel-constrained heat and power scheduling of a remote microgrid," Energy, Elsevier, vol. 277(C).
    • Handle: RePEc:eee:energy:v:277:y:2023:i:c:s0360544223011167
    DOI: 10.1016/j.energy.2023.127722
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    1. Wu, Thomas & Hu, Ruifeng & Zhu, Hongyu & Jiang, Meihui & Lv, Kunye & Dong, Yunxuan & Zhang, Dongdong, 2024. "Combined IXGBoost-KELM short-term photovoltaic power prediction model based on multidimensional similar day clustering and dual decomposition," Energy, Elsevier, vol. 288(C).

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