A multi-objective scheduling of renewable energy sources in a smart grid system
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Keywords:
RESs, MG, PV, WT, MOPSOAbstract
The demand for electricity is increasing as our global population grows. The shift towards renewable
energy sources (RESs) is unavoidable.
RESs have cost benefits and are also eco-friendly. However, effectively regulating the energy cost presents
a notable challenge when incorporating RESs into microgrids (MG). To tackle this issue, this work presents
a novel approach utilizing a cost-effective multi-objective particle swarm optimization (MOPSO) to
optimize electricity distribution among different generation units within the MG system. The proposed
MOPSO algorithm will optimally allocate the power produced from various sources in the MG, aiming to
minimize operational costs, carbon emissions, and LOLE (Loss of Load Expectation). MOPSO utilizes the
heuristic technique to produce a wide range of non-dominated solutions. The simulation results depict the
efficiency of our proposed model in reducing the cost, emissions, and LOLE in MG under two distinct
scenarios.
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