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[Display omitted] • A new multi-criteria decision-making approach is proposed. • Fixed panel-based off-grid hybrid energy systems is the right choice. • The optimal hybrid system is sustainable during flood event without any damage. • The optimal hybrid system is cost-effective and beneficial for future load demand. • Sensitivity analysis proved the effectiveness of the proposed approach. The unique geographical features of wetlands pose challenges to the conventional energy infrastructure. To address these challenges, this study proposes the establishment of off-grid hybrid energy systems (HES) that integrate photovoltaic (PV), wind turbine (WT), diesel generator (DG), and hydrokinetic turbine (HKT) units, along with batteries for energy storage. Initially, a list of criteria was determined for analysis. The Hybrid Optimization of Multiple Energy Resources (HOMER) tool was utilized for techno-economic optimization and to identify optimal off-grid HES designs for powering three villages in the wetland (Haor) region of Bangladesh. Subsequently, the Linear Bounded Weighted Average (LBWA) method was used to calculate the weights of the criteria. Then, a wins in league (WIL) theory-based Multi-Criteria Decision Making (MCDM) method, known as the Combined Compromise Solution (CoCoSo), was introduced to rank the identified optimal off-grid HES alternatives. The results favor an integrated system comprising 388 kW PV, 39 kW WT, 150 kW DG, 160 kW HKT, and 893 kWh Li-Ion BT for optimal load demand fulfillment, providing benefits to nearby communities. This study underscores that a fixed panel-based optimal hybrid system consumes 5 %, 8 %, and 9 % less fuel, emits minimal CO 2 , requires fewer water resources, and creates more job opportunities than other tracking technologies. Compared with a DG-only system, the optimal off-grid HES proved to be 59 % more cost-effective and reduced CO 2 emissions by 96 %. In contrast, compared with a stand-alone PV system, the optimal off-grid HES is 35.5 % more cost-effective and reduces excess energy by 62 %. The proposed off-grid HES is highlighted as cost-effective, and environmentally sustainable, without any damage to the PV system during flood. Furthermore, the optimal hybrid system can reduce energy costs and excess energy by 2 % and 9 %, respectively, in future load demand scenarios while also generating 6 % more employment. The effectiveness of the analysis and the proposed approach was demonstrated through sensitivity analyses. The proposed WIL-CoCoSo approach effectively addresses the problem of rank reversal in decision making. The findings of this study also provide a foundational model for designing flood-resilient and sustainable off-grid HES in wetland areas of developing countries. [ABSTRACT FROM AUTHOR]

[Display omitted] • Optimum configuration of hybrid energy systems are presented for a building. • The combination of photovoltaic, wind, diesel generator, and battery is the optimum. • The costs of the hybrid energy system are sensitive to changes in fuel prices. • 1 kWh Li-Ion battery is the right choice for the hybrid energy system. • Excess energy can be utilized to charge electric vehicles and create new jobs. Stand-alone hybrid energy systems (HES) have the potential to significantly reduce pollutant emissions and alleviate strain on the national grid. The selection and sizing of stand-alone HES for buildings can serve as a methodological approach toward establishing a resilient and clean electrical energy system in urban areas of developing countries. To explore this further, a case study was conducted using Hybrid Optimization of Multiple Energy Resources (HOMER) to assess the feasibility of implementing a HES at Uttara University in Dhaka, Bangladesh. This study examined the technical, economic, environmental, social, and reliability aspects of a stand-alone HES. The findings of this study suggested that the PV-WT-DG-BT is the most cost-effective solution for the University when compared to other hybrid configurations. Additionally, this HES benefits the surrounding communities by creating employment opportunities and contributing to human development. The sensitivity analysis showed that the COE and NPC of the optimal HES are sensitive to fuel price changes. A PV slope angle of 23.88° was cost-effective, and a 20-meter wind turbine hub height was optimal. It was observed that increased solar radiation decreases COE. Further, sensitivity analysis showed that fuel costs, CO2 emissions, and NPC will decrease if average daily load demand declines. It was also found that 1 kWh of Li-Ion-based HES performed the best compared to other batteries. Finally, the results of the genetic algorithm (GA), and grey wolf optimizer (GWO) showed that they provide the same optimum configuration as HOMER but with the lowest NPC. The findings of this study can serve as a foundational model for designing HESs in other large educational buildings located in low and middle-income countries with environmental conditions and socio-economic characteristics similar to Bangladesh. [ABSTRACT FROM AUTHOR]