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The lack of clean water and access to energy are two major obstacles to global sustainable systems. The development of solar photovoltaic (PV) technology gained the attention of water desalination projects due to its cost decline, carbon-free emission, and the on-site energy production. However, studies on in-depth analysis of the performance of these systems remain rare. This study performs a comprehensive a design optimization and seven-factor analysis (energy, exergy, economic, environmental, energoeconomic, exergoeconomic, enviroeconomic - 7E) of a grid-tied PV system powering a large-scale seawater reverse osmosis (SWRO) plant. First, an optimal design model is developed based on real hourly measured data for the SWRO load demand and renewable resources, while considering net energy metering mechanism. The objective function is delineated to diminish the energy cost of the system, concomitant with the imposition of operational constraints. Second, an analytical model is established to perform exergetic calculations for the optimal design. Third, a sensitivity analysis is conducted to show how the model parameters affect the system design and costs. The results show that the optimal system relies on a 4.25 MW solar PV array and a 3.125 MW grid-tied inverter. This configuration reduces the levelized cost of energy by 48.3 % and carbon emissions by 50 % compared to a grid-only system. The implementation of net-metering has also maximized the designed system's revenues to 263,834 $/year. Further, the optimally designed system achieves a lower levelized cost of water (0.2217 $/m3), minimal capacity shortage, and negligible unmet load ratios (0.048 %) despite grid outages. From the exergetic assessment, the proposed system has a high exergy efficiency (9.3 %) which can be achieved despite the high value of the exergy loss. Moreover, the energoeconomic and exergoeconomic indicators have recorded tiny values (3.35E-5 kWh/$ and 0.0311 kWh/$, respectively), which are considered a desired outcome. Notably, a profit of 4285.4$ is achieved through the sale of carbon emissions reduction. The sensitivity analysis revealed an increase in the system's total cost of 4.91 % and 9.36 % and the system's energy cost of 4.91 % and 8.7 % if the energy purchase price raised by 10 % and 20 %, respectively. Also, it indicates that a fall in the electricity sellback rate of 10 % would remarkably raise the system's energy cost by 47.3 %. Finally, reducing the PV-Inverter costs by 15 % would drop the system's net present and energy costs by 51.4 % and 60 %, respectively. Overall, the insights from this study have the potential to expedite the realization of sustainable development goals 6, 7, and 13, particularly in developing nations abundant in solar energy resources. • A design optimization model for a grid-tied solar PV-powered SWRO systems is proposed. • An energetic calculations model for a comprehensive 7E analysis is developed. • Proposed system reduced energy cost to 0.0393$/kWh and water cost to 0.2217$/m3. • Achieved high exergy efficiency (9.3 %) and favorable energy economic and indicators • Sensitivity analysis reveals that lower PV-inverter costs cut energy cost by 60 %. [ABSTRACT FROM AUTHOR]

The superior access to renewable sources in modern power systems increases the fluctuations in system voltage and power. Additionally, the central dilemmas in using renewable energy sources (RESs) are the intermittent nature of and dependence on wind speed and solar irradiance for wind and photovoltaic (PV) systems, respectively. Therefore, utilizing a vigorous and effective energy storage system (ESS) with RESs is crucial to overcoming such challenges and dilemmas. This paper describes the impacts of using a battery storage system (BSS) and superconducting magnetic energy storage (SMES) system on a DC bus microgrid-integrated hybrid solar–wind system. The proposed method employs a combination of BSS and SMES to improve the microgrid stability during different events, such as wind variation, shadow, wind turbine (WT) connection, and sudden PV outage events. Distinct control approaches are proposed to control the system's different components in order to increase overall system stability and power exchange. Both the PV and wind systems are further equipped with unique maximum power point tracking (MPPT) controllers. Additionally, each of the ESSs is controlled using a proposed control method to supervise the interchange of the active power within the system and to keep the DC bus voltage constant during the different examined instabilities. Furthermore, to maintain the load voltage /frequency constant, the prime inverter is controlled using the proposed inverter control unit. The simulation results performed with Matlab/Simulink show that the hybrid BSS + SMES system successfully achieves the main targets, i.e., DC voltage, interchange power, and load voltage/frequency are improved and smoothed out. Moreover, a comparison among three case studies is presented, namely without using ESSs, using the BSS only, and once more using both BSS and SMES systems. The findings prove the efficacy of the proposed control method based on the hybrid BSS + SMES approach over BSS only in preserving the modern power system's stability and reliability during the variable events. [ABSTRACT FROM AUTHOR]

This article offers a cohesive design optimization and control framework of a large-scale grid-connected battery and battery-less hybrid solar/wind system. Primarily, a techno-enviro-socio-economic design optimization and feasibility analysis were performed for eight distinct energy alternatives. Secondly, a finite-set model predictive current control (FS-MPCC) was proposed to improve both stability and dynamic behavior of the optimal energy alternative under various climatic circumstances. Moreover, finite-set model predictive control is furtherly employed to exploit the maximum permissible power from both solar and wind energies. The proposed framework is verified over a new case-study in Sokhna Industrial Zone in Suez, Egypt. The studied load demand combines both industrial and residential load sectors with a daily consumption of 40,500 kWh and of 4-MW peak. The design optimization results revealed that the grid-connected photovoltaic/wind turbines/converter system has superior sustainable and economic performances with the least net present cost ($17,371,980) and energy cost (0.0782 $/kWh). These values were less than those of the base-case system (grid-only) by 17 % and 22 %, respectively. Moreover, the reliability analysis found a tiny and tolerable daily capacity shortage of 5835-kWh despite the five annual grid outages. Besides, around 52 % of the total energy production was acquired from both solar and wind generation systems, which interpreted in a maximum saving in carbon dioxide emissions by 45.8 % compared to the base-case system and offered substantial social benefits in terms of creating nearly 10 jobs. The FS-MPCC results proved a reinforced dynamic behavior for the maximum power tracking profiles of solar and wind systems as well as in the DC-bus voltage profile regarding the over- and undershoot and the steady-state response. Compared to PI controller, the proposed FS-MPCC creates dq-axis voltages and currents with less disturbances and ripples which inject current/voltage to the grid with fewer harmonics and thus increases the generator's lifetime. To sum up, the proposed method features an integrative and compelling case to be used as an efficient tool to implement large-scale renewable energy projects. It could act as a blueprint for energy developers, researchers, investors, and authorities to achieve affordable and sustainable energy access. • On-grid solar/wind energy system is optimized to meet industrial and residential loads. • PI. FS-MPCC technique is developed and compared with PI for optimal system control. • Optimal design has the least net present and energy costs and maximum carbon savings. • FS-MPCC prove a strengthened dynamic performance under different climatic conditions. [ABSTRACT FROM AUTHOR]

Water and energy sustainability are major concerns of the world's nations at present. This research introduces a geographical decision-making model for strategically selecting optimal locations for seawater reverse-osmosis desalination plants (SWRODPs). Furthermore, it assesses the best electrification approach, considering onshore wind turbine (WT) or solar photovoltaic (PV) power plants. A representative case-study of the Egyptian Red Sea Coast Region (ERSCR) is considered to validate the proposed model. The study delineates nineteen assessment criteria for building an informed selection of SWRODPs' potential locations. Seven experts with at least ten years of expertise in desalination and renewable technologies were selected to obtain accurate assessment criteria that imitate the real-life selection process. The group best-worth method (GBWM) was employed to ascertain optimal weights for the geospatial model criteria. The findings indicate that a mere 6.11 % of the total land area is deemed suitable, with the remaining 93.89 % classified as restricted. The suitable area is divided into different suitability classes in which about 65.85 % of the suitable area is found good for establishing the SWRODPs, while about 23.65 % of suitable land is found of moderate suitability. Besides, about 9.21 % and 0.03 % of suitable lands are considered very good and excellent suitability for implementing SWRODPs' projects. Moreover, the analysis pinpointed 8 % of the ERSCR (∼12,810 km2) as a highly suitable area for PV installation, predominantly within Qusir, Ras Sidr, Hurghada, and Ataqa districts. Concurrently, a scant 0.15 % (∼244 km2) is optimal for WT in the Qusir district. Further, the results offer proposals to the authorities and energy investors with about 50,200 km2 and 39,858 km2 of the ERSCR suitable for establishing SWRODPs powered by PV and WT, respectively. Overall, the research findings are anticipated to bolster the UN's sustainable development goals 6 and 7 and align with Egypt's Vision 2030. [Display omitted] [ABSTRACT FROM AUTHOR]

Water and energy sustainability are major concerns of the world's nations at present. This research introduces a geographical decision-making model for strategically selecting optimal locations for seawater reverse-osmosis desalination plants (SWRODPs). Furthermore, it assesses the best electrification approach, considering onshore wind turbine (WT) or solar photovoltaic (PV) power plants. A representative case-study of the Egyptian Red Sea Coast Region (ERSCR) is considered to validate the proposed model. The study delineates nineteen assessment criteria for building an informed selection of SWRODPs' potential locations. Seven experts with at least ten years of expertise in desalination and renewable technologies were selected to obtain accurate assessment criteria that imitate the real-life selection process. The group best-worth method (GBWM) was employed to ascertain optimal weights for the geospatial model criteria. The findings indicate that a mere 6.11 % of the total land area is deemed suitable, with the remaining 93.89 % classified as restricted. The suitable area is divided into different suitability classes in which about 65.85 % of the suitable area is found good for establishing the SWRODPs, while about 23.65 % of suitable land is found of moderate suitability. Besides, about 9.21 % and 0.03 % of suitable lands are considered very good and excellent suitability for implementing SWRODPs' projects. Moreover, the analysis pinpointed 8 % of the ERSCR (∼12,810 km2) as a highly suitable area for PV installation, predominantly within Qusir, Ras Sidr, Hurghada, and Ataqa districts. Concurrently, a scant 0.15 % (∼244 km2) is optimal for WT in the Qusir district. Further, the results offer proposals to the authorities and energy investors with about 50,200 km2 and 39,858 km2 of the ERSCR suitable for establishing SWRODPs powered by PV and WT, respectively. Overall, the research findings are anticipated to bolster the UN's sustainable development goals 6 and 7 and align with Egypt's Vision 2030. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper investigates the potential and feasibility of an integrating hybrid renewable power generation system with a large-scale reverse osmosis desalination plant to provide electricity, heat, and water for the New Capital International Airport, Egypt. The proposed energy system contains photovoltaic panels, wind turbine, combined heat-power microturbine generator, diesel generator, batteries, converter, thermal load controller, and a boiler. A comprehensive energy-economic-environmental optimization analysis was performed to optimize energy systems in which 16-feasible solutions were evaluated and compared. The results revealed that the optimal system has the least net present and energy costs by 1.54 M$ and 0.089 $/kWh, respectively, and needs only 1.12 years to recover the invested money. Moreover, the proposed system produces emissions of 59.5% less than the base-case. The optimal system has a negligible unmet load ratio since it has a negligible loss of power supply possibility of 0.0993%. The thermal load controller has a significant impact on reducing the net present cost, cost of energy, emissions, and needed batteries by 52%, 56.4%, 36.5%, and 90%, respectively compared to the base-case. The obtained results are expected to attract large investments in clean energy and water desalination because of the government's challenges in such fields. • Energy-economic-environmental optimization is performed for an airport in the new capital of Egypt. • Prominence is set to provide the airport with the daily need for electricity, heat, and water. • The effect of renewables, TLC, and batteries on the optimal system performance is discussed. • The cost of energy of the optimal system is reached to 0.08 $/kWh with a payback period of 1.2 years. • The proposed system generates 59.5% of CO 2 emission less than the traditional diesel. [ABSTRACT FROM AUTHOR]

• Solar-wind-diesel hybrid system is proposed for a large-scale reverse osmosis desalination plant. • A 3E fuzzy decision-making optimization model is developed for ten distinct energy systems. • Performance of flow batteries and pumped hydro storage technologies are investigated and compared. • Hybrid system with battery option results in better energy, economic, and ecological benefits. • Sensitivity analysis on storage cost show more savings in NPC and COE with pumped hydro than the battery. This paper aims to propose a conceptual design model for sustainable hybrid renewable stand-alone energy system (HRSES) to meet the electricity demand of a large-scale reverse osmosis desalination plant in Baltim, Egypt. The model investigates the feasibility of different HRSES alternatives and develop a fuzzy-based multicriteria decision-making model for meticulously selecting the optimal energy solution. Both zinc-bromine flow battery and turbine-pumped hydro energy storage technologies are integrated independently with wind, solar, and diesel power sources. Firstly, the proposed model uses HOMER software to execute an energy-economic-ecological optimization analysis for studying the practicability and components sizing of nine HRSES alternatives. Second, an integration between Fuzzy-AHP and Fuzzy-VIKOR decision-making methods is executed to choose the best design considering ten performance criteria. In the second stage, the fuzzy environment is engaged to expedite decision-makers to express their ratings in linguistic terms and to achieve more sensible and accurate results. Among ten feasible alternatives, the results reveal that the optimal system consists of 5 × 20-kW wind turbines, 328-kW photovoltaic array, 100-kW diesel generator, 112 batteries and 235-kW converter. This system has the best economic performance among all alternatives with least NPC, COE, and payback-period of $1,048,046, 0.101$/kWh and 1.1 yr, respectively. Besides, it has a treasured share of renewable of 95.55%; hence, it produces a realistic CO 2 of 25,426.46 kg/year. Lastly, the sensitivity analysis illuminates that the future load growth and low-interest rate hurt upcoming investments while the projected reduction in the cost of energy storages has an encouraging influence on financing decisions. [ABSTRACT FROM AUTHOR]

• Large-scale reverse osmosis desalination powered by hybrid renewable energy source. • The optimal off-grid power system was photovoltaics/wind/diesel/battery/convertor. • The emitted carbon dioxide of the optimal system outperformed diesel system by 81.5%. • Energy storage systems are required to meet the energy demand during night times. Seawater desalination is a viable source of potable water, particularly for the coastal and remote areas. However, their sustainability is limited by the intensive energy demand of the present methods. Renewable energy is an inexhaustible source of energy, accompanied by cost reduction benefits and clean power generations. Seawater desalination powered with renewable energy sources is being attractive, mainly if the utility-grid is absent. This paper aims to design a renewable energy system, to meet the electrical load demand of large-scale reverse osmosis desalination plant (1500 m3/d), and to find the optimal sizing and techno-economic and environmental feasibility assessment of several off-grid power systems. Two off-grid scenarios with different combinations of hybrid power systems were proposed and compared with the base-case of diesel. The first scenario consists of a photovoltaic, wind turbine, diesel, and generator, while the second scenario is equipped with battery storage devices. A total of eleven hybrid renewable energy systems were modelled, analyzed, and compared with the aid of HOMER Pro software to identify the best performance and the optimal plan configuration. The optimization results show that the proposed photovoltaic/wind/diesel/battery/convertor system outperformed the other alternatives and exhibited reduction potential of 60.7%, 73.7%, 62% and 81.5% lower than the existing diesel with regards to the net present cost, renewable fraction, cost of energy, and carbon dioxide emission, respectively. The optimum case consists of 451 kW solar panels, 25 wind turbines, 250 kW diesel power, battery storage of 352 string, and 358 kW system converter. The results obtained by the optimal plan with low cost and environmental protection aspects would provide a new sight for real field applications of large scales reverse osmosis applications. [ABSTRACT FROM AUTHOR]

• A multi-objective optimization model for the optimal design of HMGESs is proposed. • The optimization model includes energy, economic and environmental aspects in the assessment. • SPV/WDG/DslG/Battery is the most economic, sustainable, and ecologically favorable option. • A power management strategy is applied efficiently on the optimized system to safeguard system power quality. Currently, the global gives a unique awareness of sustainable development by exploiting renewables to provide the people with affordable and clean energy and preserve the climate. This paper proposes a methodical and explicit framework of four phases, to design an autonomous hybrid renewable energy system in a community area in Egypt: preliminarily assessment, design optimization analysis, findings evaluation, and power-quality assessment. In the first three phases which performed by HOMER Pro® software, five hybridization scenarios are evaluated and compared regarding their life-cycle cost, carbon outflows, and reliability to distinguish the extraordinary scenario to supply the addressed community area. Contrary to the majority of studies that suffice only the first three phases, the fourth phase is proposed to perform a power-quality valuation based on a power management strategy (PMS). The results reveal that the optimal configuration consists of a photovoltaic generator, wind-driven generator, diesel-genset, battery-bank, and a power converter with the minimum net present cost of 351,223 $ and energy cost of 0.2262 $/kWh among all configurations. The optimal system has a negligible capacity shortage of 0.0955% and produces the least amount of emitted gases by 50.43 tones/year due to the high renewable fraction (57%). Moreover, the optimal proposed system can recover the invested money after only 3.4 years. The proposed PMS profitably harmonized the system's energy exchange, kept sufficient reserve energy at all times, and maintained the system stability under various meteorological and load disturbances. This can be verified from the superior stabilization of the dc-bus, load voltage and frequency during the examined disturbances. [ABSTRACT FROM AUTHOR]

Worldwide, the emerging trend of hybrid renewable energy sources integration in modern power systems is increasing due to privileged prices and clean electricity supply. However, the optimal planning of rural hybrid systems is a challenging and complex task, especially when different alternatives and sustainability aspects are considered. This paper develops an integrated decision-making approach for the optimal planning of a 100% renewable energy supply system comprising solar, wind, hydro, and biomass sources in a rural area located in Pakistan. An hourly-based design optimization analysis of twelve on/off-grid electrification alternatives is performed. The optimization model simultaneously addresses five sustainability criteria related to economy, reliability, ecology, society, and topography aspects. Furthermore, a novel hybrid decision-making model has developed to identify the unique best configuration with on-grid and off-grid options. The proposed model combines fuzzy analytic hierarchy process, multi-objective optimization based on ratio analysis technique for order of preference by similarity to an ideal solution, and evaluation based on distance from average solution methods. The results reveal that the solar-hydro-biomass battery with a life cycle cost of 10.9 M$ is the top-ranking off-grid system. When the hybrid system is connected to the grid, the solar-hydro-battery has found the most appropriate design with a life cycle cost of 12.96 M$. Both scenarios have a negligible capacity shortage of 0.09%. Ecologically, the optimal off-grid system produces only 408.37 kg/yr of CO 2 due to the significant energy share of solar and hydro sources (99.3%). The optimal on-grid system produced the minimum CO 2 with 29,177.89 kg/yr compared to other alternatives. Also, employing the optimal on/off-grid designs require land area and jobs of 96.6 m2, 14 jobs, and 118 m2, 15 jobs, respectively. Overall, the developed approach with the presented case study offers a valuable benchmark and guidelines for investors and stakeholders to create realistic investment plans for the energy industry looking to push efficient inducements to encourage the high dissemination of renewables. [Display omitted] • 100% renewable energy system is established for on/off grid rural electrification. • Twelve distinctive solar/wind/hydro/biomass-based hybrid energy alternatives are optimized. • An integrated fuzzy-AHP/TOPSIS/EDAS/MOORA decision-making model is proposed. • Cost, reliability, emission, social, and topographical criteria are simultaneously considered. • Results prove the long-term sustainability of 100% renewable in rural Pakistan. [ABSTRACT FROM AUTHOR]

Owing to the stochastic behavior of renewable energy activity and the multiple design considerations, the advancement of hybrid renewable energy-based microgrid (HREMG) systems has become a complex task. This study proposes a design optimization algorithm for the long-term operation of an autonomous HREMG along with the optimal system capacities. The investigated energy system comprises photovoltaic panels, wind turbines, diesel generators, and batteries. It aims to energize a remote coastal community with a daily load demand of 400 kWh in Marsa Matruh, Egypt. Since most studies utilize commercial tools in the design optimization procedure, the African vultures optimization approach (AVOA) is developed to find the optimal energy alternative and determine the optimal component's capacity considering achieving the minimum energy cost and loss of power supply probability. Moreover, an adequate energy management strategy is suggested to coordinate the power flow within the energy system in which renewable energy sources are fully penetrated. To check the AVOA robustness and efficacy, its performance is compared with the HOMER Pro most popular commercial tool as well as with new metaheuristic algorithms, namely the grasshopper optimization algorithm (GOA) and Giza pyramid construction (GPC) under the same operating environment. The results revealed that the proposed AVOA achieved superior economic results toward the least net present cost ($346,614) and energy price (0.0947 $/kWh). Moreover, over 20 independent runs, the AVOA showed a better performance in terms of convergence and execution time compared to other tools/algorithms. The obtained findings could be a useful benchmark for researchers in the sizing problem of hybrid energy systems. [ABSTRACT FROM AUTHOR]

• A large-scale solar linear Fresnel system with thermal oil storage tank is experimentally studied. • The maximum instantaneous heat production was found to be 62.3 kW. • The proposed system achieved tank thermal oil temperatures up to 213.2 °C. • relevance vector machine (RVM) was employed to model the system operation. • Simulated annealing algorithm (SAA) was utilized to explore the optimal structure of RVM. • RVM-SSA had a unique accuracy in predicting the performance of the linear Fresnel system. The advancement of solar linear Fresnel reflector (LFR) systems as a viable technology for green heat and power generation has recently garnered significant attention from both researchers and authorities. Regrettably, this technology's lack of experimental performance data and operational parameters hinders its in-depth characterization, complicates modeling and design efforts, and constrains its practical applications. A large utility-scale solar LFR system with evacuated compound receiver is experimentally investigated and numerically modeled in this work. The site selection, technical design, and experimental implementation of the system are technically introduced. Moreover, the experimental performance of system is examined in the harsh outdoor conditions of Al-Khobar, Saudi Arabia and thoroughly assessed in terms of specific heating power per solar collection area, total heat power production, exit hot oil temperature, energy efficiency, and net exergy efficiency. More so, the long-term operation performance of the established LFR system, for the first time, is modeled and predicted using the relevance vector machine (RVM) modeling as a novel machine learning benchmark. Additionally, an innovative version of metaheuristic algorithms, namely simulated annealing algorithm (SAA) is incorporated with the original RVM to explore the optimum RVM hyperparameters towards maximizing the prediction accuracy. Moreover, using eight different statistical measures, the RVM-SAA model is compared with typical RVM and classical ANN. The experimental findings demonstrate the capability of the LFR system to generate approximately 62.30 kW of useful thermal power, with energy, thermohydraulic, and exergy efficiencies reaching up to 35.10 %, 25.95 % and 7.82 %, respectively. Furthermore, the operation of this new LFR system can lead to temperature levels up to 213.25 °C at a continuous thermal oil flow at a rate of 9.0 m3/h. Furthermore, the statistical analyses demonstrated the superiority of the RVM-SAA approach compared to other models investigated for predicting the system performance profiles. Specifically, RVM-SAA achieved the highest deterministic coefficient values of 0.9997 and 0.9988 and the lowest RMSE of 0.4090 and 2.5150 for predicting the system's thermal power production and the outlet oil temperature, respectively. [ABSTRACT FROM AUTHOR]

• Model for the design and control of an off-grid 100% renewable system is proposed. • Nine alternatives of solar/wind/different storages are modelled and optimized. • Evaluation criteria are cost, emission, and load voltage/frequency constancy. • Solar/wind/lead-acid battery shows the most economic and reliable alternative. • Lead-acid battery/supercapacitor is more efficient than battery only. The continuous rise of global electricity demand and significant dependency on fossil fuel-based centralised power plants are the main indicators of increasing greenhouse gas emissions, thus negatively affecting climate change and human health and increasing the earth temperatures. This alarming situation has demanded the transition to 100 % renewable energy to decarbonise energy use. However, the fluctuating weather resources, and high investment cost are the major challenges with renewable energy implementation. In this context, the combined integration of multiple sources with energy storage in a so-called hybrid renewable energy system was developed as a durable remedy for the previous issues. This paper proposes a joint and conceptual approach for techno-economic design and dynamic rule-based power control of an off-grid solar/wind hybrid renewable energy system integrated with a hybrid energy storage system that comprises a lithium-ion battery, lead-acid battery, and a supercapacitor. Such concurrent integration of 100 % renewable energy systems and hybrid energy storage systems is lacking in the existing literature. First, with the aid of HOMER software, the feasibility and optimisation analysis of nine different configurations was performed in 1 min resolution to find the optimal component sizes. Second, MATLAB/Simulink models were assembled for the winning design based on a dynamic rule-based strategy to investigate and analyse the system's dynamic response, power equilibrium, DC-bus voltage supervision and load voltage/frequency control against instantaneous and dynamic changes in the load or renewable energy resources. The proposed approach was promoted and validated on an actual case study for isolated residential community electrification in Saudi Arabia, in which a multi-tier framework was adopted to accurately simulate the stochastic energy consumption of the community's households. From the design results, the hybrid renewable energy system, which integrates solar, wind, lead-acid batteries, and converter with optimal capacities of 55 kW, 18 kW, 325 kWh and 42 kW converter, respectively, is the most cost-effective alternative with the minimum net present and energy costs of $232,423.3 and $0.3458/kWh, respectively. The system has the least unmet load with 13.5 kWh/years (0.02 %), thus ensuring maximum reliability and customer satisfaction. Meanwhile, the developed control strategy efficiently improved the dynamic response, the DC-bus voltage stability, and the load voltage/frequency during different climatological and load interruptions. Further, the use of lead-acid batteries and supercapacitors has effectively diminished the maximum overshoot of the DC-bus and load voltages by 50 % during all disturbances. In addition, the integration of supercapacitors proficiently saved 2.3–6 kW during wind speed change and 2–9 kW during simultaneous changes in the radiation and load. Overall, the presented method, together with the reported results, provides an improved understanding and highlights the extent to which the successful integration of hybrid renewable energy system and hybrid energy storage system can be used to develop reliable and sustainable energy access for off-grid areas. [ABSTRACT FROM AUTHOR]