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Sizing of Hybrid PV/Battery/Wind/Diesel Microgrid System Using an Improved Decomposition Multi-Objective Evolutionary Algorithm Considering Uncertainties and Battery Degradation

Houssem R. E. H. Bouchekara, Yusuf A. Sha’aban, Mohammad Shoaib Shahriar, Saad Mohammad Abdullah, Makbul A.M. Ramli

2023Sustainability27 citationsDOIOpen Access PDF

Abstract

In this paper, a small-scale PV/Wind/Diesel Hybrid Microgrid System (HMS) for the city of Yanbu, Saudi Arabia is optimally designed, considering the uncertainties of renewable energy resources and battery degradation. The optimization problem is formulated as a multi-objective one with two objective functions: the Loss of Power Supply Probability (LPSP) and the Cost of Electricity (COE). An Improved Decomposition Multi-Objective Evolutionary Algorithm (IMOEAD) is proposed and applied to solve this problem. In this approach, different decomposition schemes are combined effectively to achieve better results than the classical MOEA/D approach. Twelve case studies are investigated based on different scenarios and different numbers of houses (5 and 10 houses). Each time, the suggested approach produced a set of solutions that formed a Pareto front (PF). Considering a variety of parameters, the optimal compromise option can be selected by the designer from the PF.

Topics & Concepts

Multi-objective optimizationMicrogridBattery (electricity)Evolutionary algorithmMathematical optimizationDecompositionSizingWind powerRenewable energyComputer scienceAutomotive engineeringPower (physics)EngineeringMathematicsElectrical engineeringVisual artsBiologyQuantum mechanicsEcologyPhysicsArtHybrid Renewable Energy SystemsEnergy and Environment ImpactsElectric Vehicles and Infrastructure
Sizing of Hybrid PV/Battery/Wind/Diesel Microgrid System Using an Improved Decomposition Multi-Objective Evolutionary Algorithm Considering Uncertainties and Battery Degradation | Litcius