Table 1 Overview of the employed techniques in enhancing HRES.
Refs. | Year | Location | Microgrid System | Techniques/Tool | Objective Function | Strength | Weakness |
|---|---|---|---|---|---|---|---|
2020 | Aljouf, Saudi Arabia | PV/WT/BESU/DG PV/BESU/DG WT/Battery/DG | SSO, GWO, HHO, MVO, WOA and ALO | COE | A clear and detailed research with several results | This study has limited constraints, and the suggested SSO could be explored more | |
2020 | Yobe State, Nigeria | PV/WT/BESU/DG | PSO, CSA, GOA MOGOA | COE COE/DPSP | Application of single-objective and multi-objective methods (GOA and MOGOA) | The proposed study doesn't analyze different architectures, and it doesn't compare MOGOA to other algorithms | |
2021 | Dakhla, Morocco | PV/WT/BESU/DG | EO, HHO, GWO, AEFA, and STOA | NPC | Apply a novel meta-heuristic optimization algorithm with many constraints | There weren't many different architectures or configurations analyzed | |
2021 | Sousse, Tunisia | PV/WT/BESU/DG | RG | TNPC/EC | Real weather data are considered | Algorithm comparison is needed to make sure that the RG algorithm can give the best results | |
2022 | Yalova, Turkey | PV/WT/BESU/DG | HS, HOMER, ACO and Jaya | ACS | Simple and clear research | The sensitivity analysis is not included | |
2023 | Sønderborg, Denmark | PV/WT/BESU/DG | MOMFO, NSGA-II, MOPSO, and MOSEO | LCOE/LPSP | The Taguchi method is employed to establish the upper limits of the model's decision variables, while a fuzzy decision-making approach is utilized to acquire the optimal Pareto front | In the proposed scenarios, areas with varying topography can be included in order to improve the accuracy of the decision-maker's analysis, particularly when solar radiation and wind speed are low | |
2023 | Jiuduansha, China | PV/WT/BESU/DG PV/BESU/DG WT/BESU/DG PV/WT/BESU | HPSODE-FAM, ABC, GA, PSO, and DE | LCOE/LPSP/HDI | A tri-objective function, which incorporates LCOE, LPSP, and HDI, and two strategies for managing energy are implemented | The REF is not considered in the constraints | |
2022 | Djelfa, Algeria | PV/WT/BESU/DG | MOSSA, MOGOA, MODA, and MOALO | COE/LPSP | Application of a new meta-heuristic optimization algorithm | The MOSSA could be further explored with different configurations of HMS | |
2023 | Tunisia | PV/WT/BESU/Hydraulic | NSGA-II | LPSP/COST | Multi-objective optimization using an evolutionary algorithm in a remote location | The results obtained are not compared to any other algorithms | |
2023 | Khartoum, Sudan | PV/WT/BESU/DG | MILP (Gurobi, Python) | NPC/LPSP | Integration Three different solar tracking systems were utilized with a fixed system of PV panels to gain maximum power | The algorithm's application is unclear, and it needs to be compared with other algorithms to get the best results | |
2023 | Ramnicu Valcea, Romania | PV/WT/BESU/DG PV/WT/BESU/FC PV/WT/BESU | HOMER, iHOGA | COE/NPC | HOMER and iHOGA simulate hybrid system performance. Both programs examine the economic and environmental outlook | The results obtained by applying HOMER and iHOGA are not compared to the meta-heuristic algorithms | |
2023 | Basra, Iraq | PV/WT/Biomass/BESU/DG | GWCSO, PSO, GA, GWO, CSO, and ALO | ANC/LCOE | Applied a new hybrid meta-heuristic optimization algorithm named GWCSO | This research does not account for reliability, which might decrease the design system's credibility |
