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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]

• An approach for modelling, simulation, and optimization of coastal MGs was developed. • Different DSM scenarios were implemented, evaluated, and compared. • Combined load shifting and load shaving techniques with hybrid MG attained the highest cost savings. • 100% renewable-based MG offered more sustainable design. • Sensitivity analysis proves the reliability and generalizability of the proposed approach. In the realm of sustainable power systems, the pivotal role of demand-side management (DSM) in Microgrids (MGs) design and planning is increasingly recognized. This study accentuates the significance of DSM in improving operational efficiency, economic viability, and environmental sustainability of MGs, focusing on a remote community in the Gulf Al-Aqaba, Sinai Peninsula, Egypt. An innovative four-level approach is proposed for the techno-enviro-economic modelling, simulation, and optimization-based DSM of MGs, addressing the challenges posed by renewable energy integration and fluctuating electricity demands. The research explores three demand scenarios: a base load without DSM (SC-1), load shifting-based DSM (SC-2), and a combined load shifting/peak shaving DSM (SC-3), to demonstrate the adaptability and robustness of MGs under different conditions. The findings reveal significant improvements in MG performance, with peak load reduction from 73.66 kW in SC-1 to 50.82 kW in SC-2 and 44.82 kW in SC-3, highlighting the effectiveness of the applied DSM strategies. These strategies also yield economic benefits, evident in an 8% and 23% decrease in the total life cycle cost for hybrid and 100% renewable MG configurations under SC-2 and SC-3, respectively, compared to SC-1. Particularly noteworthy is the reduction in required capacities of key MG components in the hybrid MG scenario under SC-3, with reductions of 10% for solar photovoltaic, 33% for microturbine generator, and 40% for battery energy storage, implying cost savings and a more efficient MG setup. Additionally, the environmental impact is profound, with an 80.3% decrease in emissions for the hybrid MG setup under SC-3 compared to a standalone 50 kW MTG system under SC-1. This outcome highlights the potential of DSM in contributing to environmental sustainability, particularly in MG configurations involving renewable energy sources. In conclusion, the study provides comprehensive insights into the synergy between DSM and MG optimization, underscoring its essential role in addressing climate change and transitioning to sustainable energy systems. [ABSTRACT FROM AUTHOR]

The refugee crisis forces various security, economic and natural weight on host nations. To house refugees, camps are considered a preferred option by humanitarian agencies and governments. The siting of refugee camps is an inherently complex and multidisciplinary task and can result in further displacement and long-term risks and distress to people of concern. This study proposes a geospatial decision-making approach combining geographic information systems (GIS) technology and fuzzy-analytical hierarchy process (F-AHP) method to assess land suitability and identify the optimal sites of refugee camps in Kenya. Four main factors and 19 evaluation criteria relevant to geographical, environmental, infrastructure, and social aspects are thoroughly investigated. The F-AHP is applied to determine the weights of the adopted criteria in consultation with three experts. The geospatial analysis is established using ArcGIS Pro software to derive the suitability map of refugee camps. The results concluded that Kenyan territory is classified into four ranks, low suitable represents 6.5% of the total surface area, 10.6% moderate suitable, 10.3% suitable, and 7.5% high suitable. Further, the analysis showed that the existing camps are located in unsuitable areas, whether north or east. Thus, the current study recommends moving these camps to areas far away from the flooded risk lands. In addition, eighteen new camps sites were suggested to host current and future refugees as well. The majority of these sites are located in Northeast, Northwest, and Northern Kenya, near the Kenyan borders with refugees' countries of origin. The findings revealed that the proposed new locations have superlative m2/refugee and approved the minimum area for a refugee (45 m2) defined by UNHCR. [Display omitted] [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]

• A two-stage multi-attribute analysis method for optimal design of sustainable energy system is proposed. • Different alternatives are optimized based on energy, environmental, economic, and social attributes. • Effect of uncertainty parameters on the designed system structure and cost is examined. • PV-WT-BAT-CONV mini-grid is the most sustainable alternative in El-Qsier urban city, Egypt. • Load growth and battery cost have high impacts on investment decision rather than RE resources. This paper proposes a two-stage multi-attribute analysis method in conceptualizing the feasible electrification strategy with optimal capacities for a mid-rise building situated in El-Qsier urban city, Egypt. The proposed model measures the implementation practicability of hybrid mini-grid against stand-alone diesel and the utility grid extension systems. The model takes into consideration, simultaneously, a total of 12 attributes covering technical, economic, environmental, and socio-political sustainability aspects. First, an accurate Energy-Enviro-Economic (3E) optimization analysis is performed to determine the set of feasible configurations using HOMER Pro software. Second, a Multi-Attribute Decision Making (MADM) model is established based on AHP, TOPSIS, VIKOR, CODAS, WASPAS methods to identify the unique best alternative. The results of the 3E optimization and decision making analyses confirm the non-viability of the reference site for grid extension against other off-grid systems. Also, the 100 % hybrid renewable mini-grid system is nominated as the most sustainable design, and it yielded optimal capacities of 196 kW, 72 kW, 587 kW h, and 75 kW for photovoltaic, wind turbine, converter, and battery. The system has total life-cycle and energy costs of 751,597$ and 0.2374$/kWh, respectively, with a zero-emission value and maximum social benefits equals 0.6089 jobs/year. Meanwhile, the sensitivity analysis elucidates that the load growth and battery cost have a high impact on investment decisions rather than solar irradiance and wind speed. [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]

• 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]