The results revealed that at low LPSP values (0% to 5%), the PV-hydrogen system with weather forecasting led to an optimal solution. When the LPSP value was set to 10%, the hybrid system resulted in being cost efficient. In [9], the authors calculated the optimum system configuration and achieved the desired LPSP with a minimum TAC. [PERSON] et al. [10] proposed an iterative method that followed the LPSP concept to minimize the TAC values for a PV-WT-battery hybrid system. In [11], the authors used an iterative method as a benchmark along with other meta-heuristic approaches to find the optimal size of PV modules, charge controllers, inverters, and batteries via applying the LPSP concept. [PERSON] et al. [12] used a genetic algorithm (GA) that controlled the REs uncertainties using a chance constrained model, which was applied to a case, located in the western part of China. Further, for this study, terms like algorithms, methods, and schemes were synonymously used. In the literature, several research studies have reported the feasibility analysis of HRESs in rural and peri-urban areas [13; 14; 15]. [PERSON] et al. [13] evaluated the performance of a PV-WT-diesel-battery system on an hourly basis for a varying climate, located in Adrar, Algeria. The results revealed that 69% of FFs can be saved when HRESs are used instead of diesel generators. In [14], [PERSON] et al. reported the feasibility of using a PV-WT-hydro system for an off-grid application in two locations of Nepal. The results showed that HRESs were environmentally friendly and sustainable. [PERSON] et al. [15] investigated the feasibility of a PV-biomass-battery system for a laboratory complex, located in the Republic of Congo. The results indicated 98% electric stability when HRESs and ESS were adequately dimensioned. Meta-heuristic algorithms with hybridized schemes and other optimization methodologies are widely adopted for energy management [16; 17; 18; 19] and the unit sizing problem [20; 21; 22; 23; 24; 25; 26; 27; 28; 29]. The Jaya optimization scheme was used for the optimal sizing of HRESs to minimize TAC [20; 21]. In [22], [PERSON] et al. used a hybrid approach by combining the features of the GA with particle swarm optimization (PSO) for the optimal sizing of the PV-WT-battery system of a house in an SA environment, located in Tehran, Iran. The objective was to reduce the TAC and to increase the system's reliability. The results obtained by the hybrid approach were also compared to the results obtained by a software based tool known as a hybrid optimization model for electric renewables (HOMER). The PV-WT-battery system achieved the best results in terms of TAC as compared to PV-battery and WT-battery systems. The authors in [23] used an evolutionary multi-objective, non-dominated sorting GA (NSGA-II) to find an optimum sizing of the PV-WT-battery system for a remote area, located in Tunisia. Similarly, NSGA-II with re-ranking based GA operators was proposed for a PV-WT-diesel-battery system [24]. In [25], the authors used a GA to optimize the TAC value for an SA WT-PV-tidal-battery hybrid system, located in Brittany, France. [PERSON] et al. [26] used the HOMER software tool for the optimal sizing of a biomass-biogas system to supply electricity to a commercial agricultural farm, located in Odisha, India. Similarly, [PERSON] et al. [27] used the HOMER tool for techno-economic analysis of HRESs for a large community, located in Beijing, China, using both SA and grid-connected environments. In [28], the authors used the HOMER tool for unit sizing of PV-WT and hybrid storage systems, including the fuel cell and supercapacitor for Cape Town weather conditions. [PERSON] et al. [29] proposed various evolutionary algorithms with the LPSP constraint for TAC minimization of a PV-WT-battery system. The results produced by artificial bee swarm optimization were more promising than other schemes. Considering the aforementioned studies, the common objectives considered by researchers are the minimization of TAC values based on the LPSP concept.