Document Type

Article

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

Electrical and electronic engineering

Abstract

The actual energetic situation has several challenges such as pollution, the rarefaction of fossil fuel and the dangers of nuclear. Renewable sources are proposed as a solution and suggested, such as a cost-effectiveness system. The paper deals with the problem of feeding a domestic load with electricity which should respect the ecologies factors, so this work is a design problem of the hybrid renewable energy systems; PV/biomass, PV/diesel/battery, PV/wind/diesel/battery, and wind/diesel/battery to choose the best one of them which feed the load with the lowest cost. The study’s goal is to design a microgrid system by the minimization of the total investment cost with respect to the required technical factor, the minimum allowed renewable energy fraction, and the minimum allowed availability factor. The methodology flowed utilizes frameworks based on a recent algorithm called Movable damped wave algorithm (MDVP). The proposed optimization algorithm is compared with other algorithms to prove its efficacy which are; the artificial electric field algorithm (AEFA), harris hawks optimization (HHO), and the grey wolf optimizer (GWO). The project case study is investigated in Al-Majmaah, Saudi Arabia. The contribution of this work is implementing a recent algorithm that proves its efficacy and finding the best microgrid configuration following many investigations and comparisons. The results confirm that the MDVP is better compared to the other algorithms, its computational time is fast, and its convergence is good; otherwise, the PV/biomass is considered the best configuration in the area of study with a size of 237.698 m2 from PV panel and 954.097 t/year of biomass, which obtained the best Net Present Cost (NPC) of $299504, and a cost of energy (LCOE) assumed as $0.228/kW. A sensitivity analysis is applied to prove the effect of size variation on project factors. The simple observation, by the way, is that any change in the PV size affects the output factors.

DOI

https://doi.org/10.1016/j.egyr.2022.08.278

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