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The current study proposes a model of an autonomous HRFS installed on different sites in 20 Saudi cities powered by renewable clean energy sources. The station is fully powered by photovoltaic (PV) panels and wind turbines involving an electrolyzer and hydrogen tank for producing and storing hydrogen. Three scenarios are investigated to propose an optimized model, namely Scenario 1 containing (PV-Wind-Battery) system, Scenario 2 with (Wind-Battery) technologies, and Scenario 3 with (PV-Battery) components. The HRFS is expected to feed the load hydrogen demand of 25 hydrogen cars with a storage tank capacity of 5 kg. The simulation is carried out using the well-known HOMER software and the description of the technical parameters of the renewable plant together with a detailed economic feasibility for the investigated cities are also performed. Furthermore, the optimization process executed demonstrates a competitive levelized cost of energy (LCOE) and levelized cost of hydrogen (LCOH) especially for the third scenario with a LCOH varying within $12–15.9/kg and LCOE in range $ 0.332–0.414/kWh, for all 20 cities. For instance, encouraging lowest values of net present cost (NPC) and LCOE are obtained for the futuristic NEOM mega city relatively to the first and third scenarios with values (NPC = $1,576,000, LCOE = $ 0.627/kWh) and (NPC = $830,494, LCOE = $ 0.332/kWh), respectively. On another hand, thorough analysis of PV/Wind hydrogen technoeconomic operation is provided including improvements recommendations, scenarios comparison and environmental impact discussion. [ABSTRACT FROM AUTHOR]

Tamil Nadu, a state in India, has many households with loads between 1 kW and 2.5 kW and a single-phase power supply of 230V, 50Hz. The bi-monthly energy consumption of these categories of houses crosses the band of 500 units, which leads to the excess payment of energy consumption costs. To utilize the plenty of renewable energy available in this state, we conducted a feasibility analysis to develop the optimal solar PV system for these types of households using HOMER software. Over the years from 2016 to 2018, real-time data from 500 residences in Tirumangalam, Madurai District, Tamil Nadu, were gathered and utilized to design an optimal solar PV system for these households. On completion of the sensitivity analysis, the lowest Cost of Energy (COE), Net Present Cost (NPC), and Annual Operating and Maintenance Costs are $0.104, $158.36, and $4,389.76, respectively. An optimal 2kW on-grid Internet of Things (IoT)-based solar PV system is installed in 2019 for a residential building employed in the HOMER results, and the outcomes are compared to those without solar PV systems. It is been proven that adding a 2kW solar PV system leads to an average annual savings of $79.02 for the study period of 2019 to 2022. [ABSTRACT FROM AUTHOR]

The developing environmental consequences of excessive dependence on fossil fuels have pushed many countries to invest in clean and renewable energy sources. Mexico is a country that, due to its geographic and climatic diversity, can take advantage of this potential in renewable energy generation and reduce its dependence on fossil fuels while developing strategies to improve its energy system. This study investigated the feasibility of the autonomous use of two hybrid renewable energy systems and a photovoltaic system to power homes in a remote location. With the help of HOMER Pro Version 3.14.5 software, a model was made to evaluate the operation of three systems for one year, and the demand was predicted according to a given scenario. In addition, the optimal configuration of the components of each system was determined. The results showed that the simultaneous use of solar systems with a converter and a backup system consisting of a diesel generator and batteries would be the most viable and reliable option for generating renewable energy at the selected location, offering electricity with a renewable fraction of more than 80%.

The developing environmental consequences of excessive dependence on fossil fuels have pushed many countries to invest in clean and renewable energy sources. Mexico is a country that, due to its geographic and climatic diversity, can take advantage of this potential in renewable energy generation and reduce its dependence on fossil fuels while developing strategies to improve its energy system. This study investigated the feasibility of the autonomous use of two hybrid renewable energy systems and a photovoltaic system to power homes in a remote location. With the help of HOMER Pro Version 3.14.5 software, a model was made to evaluate the operation of three systems for one year, and the demand was predicted according to a given scenario. In addition, the optimal configuration of the components of each system was determined. The results showed that the simultaneous use of solar systems with a converter and a backup system consisting of a diesel generator and batteries would be the most viable and reliable option for generating renewable energy at the selected location, offering electricity with a renewable fraction of more than 80%. [ABSTRACT FROM AUTHOR]

This paper compares the design feasibility and economic advantage of photovoltaic (PV)-diesel generator (DG)-battery, PV-wind-battery, and PV-biogas (BG)-battery hybrid systems. The objective of this study is to investigate the performance of the three hybrid renewable energy systems (HRES) for sustainable electricity supply in remote areas of Afghanistan. Hybrid optimization model for multiple energy resources (HOMER) software was utilized to perform modeling, optimization, economic, sensitivity, and multi-year analysis of the hybrid systems. The findings indicates that the PV-biomass-battery hybrid system with $175,938 net present cost (NPC) and $0.29/kWh cost of energy (COE) is the most appropriate approach than the PV-DG-battery, PV-wind-battery and diesel-only system. However, the COE in optimal HRES is higher than the COE supplied by Afghanistan's national grid to the household resident in large cities, but COE in the hybrid system is about 37% lower than the cost of energy in the study area and some provinces of Afghanistan. The multi-year analysis was performed on the PV-biogas-battery hybrid system with considering a 0.8% yearly degradation of PV panels and a 2% load increase annually. The results show about an 11.2% increase in NPC and a 6.2% decrease in COE compare to the system without multi-year consideration. Moreover, the outputs from HOMER were evaluated using the Simplex algorithm. The results indicate that there were no significant variations in the results from HOMER and Simplex algorithms. Therefore, this illustrates that the simulations were consistent. The study's findings are anticipated to be helpful to stakeholders, decision-makers, and investors to achieve the goals and increase the electricity access rate in remote areas of Afghanistan. [ABSTRACT FROM AUTHOR]

Fereydounshahr experiences growing electricity shortfalls and an overreliance on polluting diesel generators. This analysis models renewable hybrid systems to electrify a local dairy operation using HOMER Pro 3.11 software. Despite higher upfront costs, adding just 5% solar photovoltaics maintained low net present costs while increasing clean energy penetration versus diesel generators alone. Furthermore, a combined diesel-solar-wind system reduced carbon dioxide and nitrogen oxide emissions by over 1%. Although diesel generators had the shortest payback period at 48 years, the capital recovery factor for a diesel–solar combination reached 62 years. Thus, tailored hybrid renewable systems could provide an affordable, low-emissions electricity solution for the Fereydounshahr livestock facility. With suitable wind and solar resources, the right policy incentives could also unlock substantial local renewable capacity to meet rising demand and mitigate dependence on imported, climate-harming fossil fuels. [ABSTRACT FROM AUTHOR]

Today, using systems based on renewable resources is a suitable alternative to fossil fuels. However, due to problems such as the lack of access in all the times needed to supply cargo and high‐investment cost, it has not been well‐received. In this research, in addition to maintaining the technical specifications and increasing the reliability of the system due to the addition of the hydroelectric power plant to other wind and solar systems, it has been tried to use biodiesel fuel (biofuel) as an alternative to fossil fuel in the diesel generator. To identify the most economical combination of the system with the application of social costs and the limit of pollutant and greenhouse gas emission in independent mode with the help of Homer software. the results showed that adding biodiesel to the designed system, the investment costs will increase by $282,038, which has a direct impact on the cost of energy and causes an increase of 0.0115 $/kWh. While the use of biodiesel reduces the emission of carbon dioxide by 28,947 kg/year. [ABSTRACT FROM AUTHOR]

The expansion of the industrial sector and the continuous increase in population are the reasons for the ever-increasing demand for electricity, which directly burdens the central grid. Absence and remoteness from the central grid make off-grid power generation the most reliable source of electricity to meet the needs of peripheral areas. Electrification of remote areas through decentralized generation using renewable energy sources has emerged as a low-cost and practically viable solution. Domestic-level energy trading makes the system more cost-effective. This study develops a hybrid energy model consisting of PV and diesel generators to electrify a remote village, considering the feasibility analysis of consumer-prosumer-based energy trading potential. First, resource evaluation and total load demand are estimated at the selected site, then system sizing optimization and techno-economic feasibility are evaluated using HOMER Pro software. Based on the optimized system, a new system is proposed and developed using HOMER Pro software to investigate the energy trading potential. Economic rationality is checked using the economic parameters of net present cost, levelized cost of electricity, initial capital, and operation and maintenance cost of the system. A sensitivity analysis is performed further to evaluate the system's feasibility under different conditions. This study fills the energy trading sector gap by providing a more efficient and cost-effective simulation-based study. The results show that the proposed system has a 22 % lower net present cost, 66 % lower levelized cost of electricity, 25.5 % lower operation and maintenance cost, and 4.36 % lower initial cost.

The high cost of fuel has become a significant challenge for farmers in operating water pumps for irrigation in agricultural fields. The pumps are rendered economically inefficient due to the associated high operational costs. Therefore, the proposed solution to address this issue is the utilization of wind energy. Wind energy is converted into electrical energy to power water pumps. This research aims to: determine the average power in the wind use statistical method based on the average of windspeed, evaluate the efficiency of wind power generators, and select the appropriate wind turbine type for installation in the Kedungweru region, Kebumen, Central Java. The study was conducted at the Wind Power Plant (PLTB) in Kedungweru Village, Kebumen Regency, Central Java, and the Laboratory of Thermal Systems Engineering and Renewable Energy at Jenderal Soedirman University. Sampling methods included measuring wind speed, voltage, and current, as well as data from the Hybrid Optimization of Multiple Energy Resources (HOMER) software. The variables of this research were maximum/minimum/average wind speed, electric pump load, power generated by the wind power plant, and the efficiency of wind turbine performance. The results of the study indicate that Kedungweru has a relatively good wind energy potential, with an average wind speed of 4.79 m/s. From the HOMER simulation using 2 AWS HC 650 W wind turbines, the generated electrical energy reached 2,543 kWh/year. Additionally, the simulation showed an electrical surplus of 33.2%, indicating a well-performing system as almost all generated energy can be efficiently utilized without wastage. Thus, the use of wind energy as a renewable resource for irrigating agricultural fields can be an efficient and economical solution to address the high operational costs resulting from expensive fuel prices.

Abstract This study aimed to provide a techno‐economic analysis of hybrid energy systems, including wind turbines, photovoltaic systems (PV) panels, diesel generators, and batteries, for selected cities in five different climate zones in Spain to meet the load requirements of industrial towns. Homer software was used to determine the most efficient configuration for supplying the average load of the industrial sector, with a value of 1500 kWh/day and a peak load of 114.58 kW, and the residential sector, with a value of 150 kWh/day and a peak load of 27.85 kW. Optimization is carried out to minimize the evaluation parameters of net present cost (NPC) and cost of energy (COE). According to the software outputs, it appears that the system utilizes a variety of renewable energies. The priority is to use all hybrid system components, and the wind–PV–diesel–battery configuration has performed best in all cities. The cities of A Coruña, Bilbao, Ponferrada, Almería, Barcelona, Salamanca, Seville, Zaragoza, and Madrid, respectively, with NPC values of 1.39, 1.67, 1.76, 1.92, 2.23, 2.29, 2.39, 2.55, 2.61 M$ and COE values of 0.199, 0.24, 0.252, 0.276, 0.32, 0.329, 0.343, 0.366, 0.374 $/kWh have economic efficiency from the highest to the lowest. Reducing pollution production is one of the key reasons for approaching hybrid technologies. In this regard, A Coruña has the lowest carbon emissions among the selected cities, with 25,190, and 95.5% of its energy production is renewable. On the other hand, Madrid, which uses 89% renewable energy, has the highest carbon dioxide production with a value of 59,242. The system analysis in different cities of Spain provides insight into the conditions necessary for establishing such systems in different climate zones, which can serve as a road map for other places in the country.

The feasibility of a hybrid renewable energy system for long-term rural electrification in Billerahalli village, Karnataka, India, is investigated in this paper. This paper presents a systematic methodology for planning and designing of an efficient hybrid system that incorporates techno-economic optimization analysis. Using HOMER PRO software, several hybridization situations are modelled and analyzed. In this design, electrolyzer and a hydrogen tank are included to reduce the need for batteries. The results shown that the optimal configuration system is a wind turbine, electrolyzer, hydrogen tank, converter, and LL1500-W battery (4 units of 800 kW/ 100 kW/ 100 kg/ 734 kW/ 500 units), with a low net present cost, cost of energy, a significant return on investment, and reductions in carbon emissions. This system offers a steady power supply by utilizing 100 % renewable sources, with a net present cost of $5.21 million and a relatively low energy cost of $0.25 per kilowatt-hour. The optimized hybrid system outperforms other system configurations in terms of cost-effectiveness and environmental performance. Concurrently, the sensitivity analysis emphasizes the system costs majorly depends on the unpredictability of solar radiation and wind speed, as well as changes in interest rates impacting future investment decisions. Finally, the study expects to provide the awareness of renewable energy potential usage in Billerahalli village and significant information for the efficient design and exploitation of hybrid renewable energy systems within the larger energy sector.

The current study proposes a model of autonomous Hydrogen Refuelling Stations (HRFS) installed on different sites in twenty French cities powered by renewable clean energy sources. The station is fully powered by photovoltaic (PV) panels, wind turbines with battery storage and involving an electrolyzer and hydrogen tank for producing and storing hydrogen. Using Homer simulation, three scenarios are investigated to propose an optimized model, namely Scenario 1 containing (PV-Wind-Battery) system, Scenario 2 with (Wind-Battery) technologies and Scenario 3 with (PVBattery) components. The otimization process executed demonstrates very competitive levelized cost of energy (LCOE) and levelized cost of hydrogen (LCOH) especially for the third scenario solely based on PV power with LCOE in range $0.354-0.435/kWh and a LCOH varying within $13.5-16.5/kg, for all 20 cities. An average net present cost (NPC) value of $ 1,561,429 and $ 2,522,727 are predicted for the first and second architectures while least net present cost of $1,038,117 is estimated for the third combination solely based on solar power according to all sites considered. For instance, minimum values are obtained for Marseille city with LCOE=$ 0.354/kWh and a LCOH=$ 13.5/kg in conformity with the minimum obtained value of NPC value of $886,464 with respect to the winner third scenario. In addition, more costly hydrogen production is expected for Grenoble city especially for scenario 1 and 2 where wind turbine technology is introduced. On another hand, thorough analysis of PV/wind hydrogen techno-economic operation is provided including improvements recommendations, scenarios comparison and environmental impact discussion. [ABSTRACT FROM AUTHOR]

This study aimed to provide a techno‐economic analysis of hybrid energy systems, including wind turbines, photovoltaic systems (PV) panels, diesel generators, and batteries, for selected cities in five different climate zones in Spain to meet the load requirements of industrial towns. Homer software was used to determine the most efficient configuration for supplying the average load of the industrial sector, with a value of 1500 kWh/day and a peak load of 114.58 kW, and the residential sector, with a value of 150 kWh/day and a peak load of 27.85 kW. Optimization is carried out to minimize the evaluation parameters of net present cost (NPC) and cost of energy (COE). According to the software outputs, it appears that the system utilizes a variety of renewable energies. The priority is to use all hybrid system components, and the wind–PV–diesel–battery configuration has performed best in all cities. The cities of A Coruña, Bilbao, Ponferrada, Almería, Barcelona, Salamanca, Seville, Zaragoza, and Madrid, respectively, with NPC values of 1.39, 1.67, 1.76, 1.92, 2.23, 2.29, 2.39, 2.55, 2.61 M$ and COE values of 0.199, 0.24, 0.252, 0.276, 0.32, 0.329, 0.343, 0.366, 0.374 $/kWh have economic efficiency from the highest to the lowest. Reducing pollution production is one of the key reasons for approaching hybrid technologies. In this regard, A Coruña has the lowest carbon emissions among the selected cities, with 25,190, and 95.5% of its energy production is renewable. On the other hand, Madrid, which uses 89% renewable energy, has the highest carbon dioxide production with a value of 59,242. The system analysis in different cities of Spain provides insight into the conditions necessary for establishing such systems in different climate zones, which can serve as a road map for other places in the country. [ABSTRACT FROM AUTHOR]

This paper presents a very alarming forecasts about our future and particularly for a medium and long-term future. That is to say, several actions are being carried out by different civil and state parties to deal with these very concrete threats. And it is within this framework that this paper fits, and its objective is to highlight the hybrid systems and more precisely the photovoltaic-wind hybrid systems coupled with storage batteries, as an efficient alternative to the classical means of electricity production. This work will adopt a method of obtaining results called performance evaluation, so this manuscript will present firstly the mathematical model of this hybrid system to best conceive what it is about, then as second part will determine the exact figures of the largest amount of carbon dioxide (CO2) that can be avoided using this technology and following a precise methodology, this can be applied to our situation, i.e., a simple house or to any other type of installation. [ABSTRACT FROM AUTHOR]

Rural tourism is an important factor in achieving economic, social, and cultural development. Given that villages in Iran do not have access to permanent electricity or are associated with high power outages, the provision of sustainable electricity through renewable energy can cause more tourists to choose these villages as their ultimate goal. Therefore, in this paper, for the first time, a hybrid system has been evaluated based on solar energy in 10 tourism target villages in Iran using HOMER software. This study investigated the design of the system with real and up-to-date data on equipment and fossil fuel prices taking into account transportation costs as well as a comprehensive study of energy-economic-environmental with electricity generation approach to the development of rural tourism. The results demonstrated that for the studied stations, the LCOE parameter was in the range of $ 0.615-0.722, the percentage of power supply by solar cells was in the range of 90-99 %, and the prevention of pollutants was 33.9-277 kg/year. According to the results, Meymand village is the most suitable and Mazichal village is the unsuitable station in the field of energy supply required by solar cells. The production pollution in the studied stations is mainly CO2 and results from the operational phase of the project and its amount is 979.5 kg/year. Given that the rural tourism has grown and become a solution for development, the authors hope that the present work results can be used as a perspective to help energy and rural tourism decision-makers.

Background: The generation of clean and affordable energy by 2030 is a challenging task, necessitating the integration of renewable energy sources to reduce greenhouse gas emissions associated with coal, crude oil, and natural gas. This study examines the optimization and performance analysis of a hybrid microgrid for a university campus as a potential solution to achieve this goal. The primary objective is to decrease the cost of energy and reduce CO2 emissions on the campus using a hybrid approach. Results: The Howard college campus of the University of KwaZulu Natal (UKZN) was used as a case study, with meteorological data obtained from NASA and real hourly electrical load data for 2019 from the university smart meters. HOMER, an optimization software, was employed to model and simulate the case study. The results demonstrated significant savings of R15.7 million (approximately $ 820 000) in annual utility bills, a 51% reduction in CO2 emissions, a return on investment of 20%, and a payback period of 4 years. Conclusion: The study's findings suggest that universities can become self-sustaining during load shedding periods, as recently experienced in South Africa. The implementation of a hybrid microgrid system on a university campus offers considerable economic and environmental benefits, providing a potential blueprint for other large institutions seeking to achieve similar sustainability goals. [ABSTRACT FROM AUTHOR]

The main goal of this paper is to design an efficient renewable energy system that meets the required electricity demands. Consequently, it is essential to find the most cost-effective hybrid system that can reduce energy costs and provide access to the required electricity generation. An international school in New Administrative Capital in New Cairo, Egypt was chosen as a study area for the proposed system. Solar, wind, and biomass resources are abundant at the chosen location throughout the year. Using the HOMER (hybrid optimization model for electric renewables) software, eight distinct models of renewable energy hybrid systems were designed, simulated, and optimized to meet the required load in this study. For wind and solar resources, the National Aeronautics and Space Administration (NASA) provided the input data; for biomass resources, real-time field data were used for the selected study site. In this study, lithium-ion and lead acid batteries were used to choose the most cost-effective option. The hybrid power system's PV, wind, and biomass generators were utilized to meet the load demand. The overabundance of energy requests was utilized to charge the battery banks as required when accessible to cover the load requirements during times of low energy production.

There is no way for developing countries to prosper economically or improve their living standards in rural areas if they lack access to energy and power. Access to electricity is frequently a disadvantage in rural areas of developing nations. This work aims to investigate rural electrification in Port Harcourt, Nigeria, using the Choba community as a case study. The investigation was divided into two stages: the first determined the current state of electrification in Choba, and the second study conducted a detailed assessment of integrating the renewable energy system for increased electricity access using the simulation software HOMER pro to estimate the number of photovoltaic modules (PVMs) and wind turbines required to ensure optimal performance. The analysis was examined by selecting the optimum configuration based on levelized cost of energy (LCOE) and net present cost (NPC). The normal energy consumption for the community is estimated to be approximately 39.12–46.80 MW for full 24-hour supply to all residents. In 2021, 6067.64 megawatt hours of electricity were supplied by Port Harcourt electricity distribution company (PHEDC). From the obtained results, this paper proposes an on-grid hybrid PVM/wind turbine system configuration that yields the optimal results in the case study to solve the power outages currently experienced in Choba. The optimal configuration has an NPC of $20.8 Million and LCOE $0.0117/kWh, with an operating cost of $204.52. This system reduce cost of energy by about 87% when compared with the non-MD customers in Band D.

In an environment with unstable power supply, incessant load shedding and inconsistent energy availability remains a major challenge. Hence, there is a need for an urgent alternative source of energy to mitigate this challenge. Over the years, fossil fuel-based energy sources have been considered as an effective solution, however the greenhouse gases emissions from these sources contribute largely to the rise in the depletion of the ozone layer which eventually leads to pollution and global warming. This work contributes to efforts in curbing this menace by reducing the use of diesel generators and focus more on a hybrid renewable energy system. This study, used selected residential buildings as a case study. A photovoltaic system and a diesel generator were incorporated as hybrid energy system, and the data gathered was processed using the HOMER software. The output of the simulation provided two optimal systems (PV-Diesel Generator, Battery coupled with the complete Hybrid system) and (PV- Diesel generator). The optimal and cost-effective system from the analysis is the PV-diesel hybrid system. This consists of a 10kW solar PV, 45kW Diesel generator, a 10kW converter and six 6FM200D batteries. This study provides a synergy of individual subsystems as analyzed in the result to enhanced the reliability of the system.

Fereydounshahr experiences growing electricity shortfalls and an overreliance on polluting diesel generators. This analysis models renewable hybrid systems to electrify a local dairy operation using HOMER Pro 3.11 software. Despite higher upfront costs, adding just 5% solar photovoltaics maintained low net present costs while increasing clean energy penetration versus diesel generators alone. Furthermore, a combined diesel-solar-wind system reduced carbon dioxide and nitrogen oxide emissions by over 1%. Although diesel generators had the shortest payback period at 48 years, the capital recovery factor for a diesel–solar combination reached 62 years. Thus, tailored hybrid renewable systems could provide an affordable, low-emissions electricity solution for the Fereydounshahr livestock facility. With suitable wind and solar resources, the right policy incentives could also unlock substantial local renewable capacity to meet rising demand and mitigate dependence on imported, climate-harming fossil fuels.

Iran is one of the most energy-consuming countries, especially in the construction sector, and more than 40% of its energy consumption is in the construction sector. Therefore, considering the very high potential of Iran in the field of solar energy, the need to pay attention to providing part of the energy required by buildings by solar energy seems necessary. The study of the effect of climate on the performance of a BIPV has not been done in Iran so far. Also, the use of ranking methods using the weighting of parameters affecting the performance of BIPV has not been done so far. The purpose of this study is to investigate the power supply of BIPV connected to the grid in the eight climates of Iran. Technical–economic–environmental energy analyses were performed by HOMER 2.81 software. In order to study different types of BIPV, four angles of 0°, 30°, 60°, and 90° were considered for the installation of solar cells. The effective output parameters of HOMER software were weighted by the Stepwise Weight Assessment Ratio Analysis (SWARA) method based on the opinion of experts, and it was observed that payback time (year) has the highest weight among the studied criteria. Then, different cities were ranked using the evaluation based on distance from the average solution (EDAS) method. The results showed that Jask is the most suitable and Ramsar is the most unsuitable city. Also, the results of the EDAS method were confirmed by Additive Ratio Assessment (ARAS), Weighted Aggregates Sum Product Assessment (WASPAS), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. [ABSTRACT FROM AUTHOR]

In an environment with unstable power supply, incessant load shedding and inconsistent energy availability remains a major challenge. Hence, there is a need for an urgent alternative source of energy to mitigate this challenge. Over the years, fossil fuel-based energy sources have been considered as an effective solution, however the greenhouse gases emissions from these sources contribute largely to the rise in the depletion of the ozone layer which eventually leads to pollution and global warming. This work contributes to efforts in curbing this menace by reducing the use of diesel generators and focus more on a hybrid renewable energy system. This study, used selected residential buildings as a case study. A photovoltaic system and a diesel generator were incorporated as hybrid energy system, and the data gathered was processed using the HOMER software. The output of the simulation provided two optimal systems (PVDiesel Generator, Battery coupled with the complete Hybrid system) and (PV-Diesel generator). The optimal and costeffective system from the analysis is the PV-diesel hybrid system. This consists of a 10kW solar PV, 45kW Diesel generator, a 10kW converter and six 6FM200D batteries. This study provides a synergy of individual subsystems as analyzed in the result to enhanced the reliability of the system. [ABSTRACT FROM AUTHOR]

The reliance on grid electricity generated from fossil fuels in many countries continues to contribute to annual CO2 emissions. Implementing renewable energy systems helps reduce the carbon footprint and enhances local grid stability, particularly in areas with high demand where power outages are frequent. This study used the Hybrid Optimization of Multiple Energy Resources (HOMER) software to determine the most cost-effective composition of a Hybrid Renewable Energy System (HRES). Simulation results indicate that a system comprising a 3007 PV array, two 1.5 MW wind turbines, and a 1927 kW converter is most suitable. Combining solar panels and wind turbines remains the most economically feasible option for on-site electricity production. The study demonstrates that installing a hybrid renewable energy system is viable on an academic campus, with an initial investment cost of US $6.58 million and yearly operational costs of US $1.38 million, which is 40.8% lower than the current system. The project payback time is estimated to be 10.11 years. These findings may be used to recommend similar systems in other regions with comparable climatic conditions. The positive monetary effects may incentivize policymakers to implement comparable systems, contributing to a carbon-neutral goal. [ABSTRACT FROM AUTHOR]

In this paper, the design and simulation of a 5 MW solar power plant in Ghor province, Afghanistan have been investigated. A suitable place at a distance of about 8.17 km from the center of the province was selected as the power plant location. The main objective of this study is the investigation of solar renewable energy resources' capacity for generation of electrical energy from domestic resources to provide reliable and sustainable energy in the center of the Ghor province which is currently not connected to the national electrical grid. In this power plant, 6399 kWp, STP-320 W PV module, and 5300 kW Growatt convertor type were used. The PVSYST, PVGIS, and HOMER renewable energy simulation tools were used for analyzing the system. The results obtained from each simulation tool were compared together. Analysis of the results using HOMER and PVGIS shows that the annual energy generated using each simulation tool is about 11698 MWh and 10673 MWh respectively while the result from PVSYST is 11938 MWh per year. According to the obtained values, results from PVSYST depict 240 MWh more energy generation than HOMER and 1265 MWh than PVGIS simulation tools annually. These values indicate that PVSYST produces higher annual power for this system than HOMER and PVGIS. Comparing the annual generated power results of the simulations with reference to the PVSYST results, it can be concluded that PVGIS is 10.6% lower and HOMER is 2% lower. There is about a 2% difference between PVSYST and HOMER.

Global warming from fossil fuels is a growing concern for governments. A potential solution is using renewable energy microgrids, which reduce dependence on the power grid. On the other hand, Electric vehicles are a solution to combat environmental pollution as they emit no harmful pollutants compared to conventional vehicles. However, charging these vehicles can lead to congestion, reliability, and resiliency issues for power systems. To address this issue, renewable energy sources are being utilized to ease the burden of electric vehicles on power grids. Therefore, this paper assumes a proposed microgrid's planning and management in Kermanshah city and uses unique renewable energy sources such as the INVELOX wind turbine and common photovoltaic panels by utilizing Homer software. Results show that for the first scenario, excluding PV panels, the NPC is $432,173. Adding PV panels reduces the optimized NPC by 53 % to $282,523. Sensitivity analysis highlights the impact of inflation, fuel prices, and PV longevity. In the second scenario with the INVELOX wind turbine, the NPC without PV is $373,199, with $26,070 in annual repairs. Adding PV panels decreases the NPC to $253,405 and maintenance to $14,288, showing significant cost reductions. Novel technologies like INVELOX and PV panels enhance microgrid cost efficiency and environmental impact. • Evaluating feasibility of building an EV charging station with real-world parameters. • A case study of Kermanshah city in Iran is assumed for this investigation. • Homer software is utilized to evaluate the various aspects of this research. • INVELOX turbines, a novel technology, are assumed to supply the charging stations. • Results show the effectiveness of this kind of planning based on the local needs. [ABSTRACT FROM AUTHOR]

In this study, a combination of Geographic Information System (GIS) and a Multi-Criteria Decision Making (MCDM) method were used to select the most desirable place for wind farm construction. Furthermore, a techno-economical assessment was performed to construct an on-grid hybrid energy system including the wind turbine, diesel generator, battery, and converter in a desirable location. The decision criteria of this study were divided into four main categories, including technical-economical, environmental, climate, and topographical, alongside 11 sub-criteria. These sub-criteria were wind speed, proximity to transmission lines, proximity to road and railway networks, distance from high load demand areas, distance from land cover, distance from protected areas, distance from rivers and water bodies, distance from the airport, the slope of the terrain, elevation, and distance from the fault. Based on the results of the first section, Izadkhast city in Abadeh county was selected as the most desirable location for wind farm construction. In the second section, an on-grid hybrid energy configuration composed of 26 wind turbines, a 500 kW diesel generator, 43 battery units, and a 574 kW converter with cos of energy, net present cost, and renewable fraction equal to 0.0719 $/kWh, 12.3 M$, and 60%, was chosen as the optimum structure for supplying electricity of Izadkhast city. [ABSTRACT FROM AUTHOR]

Tehran is one of the most populous and polluted cities in Iran with a fossil fuel-dependent economy. This paper aims to assess a techno-economic and environmental feasibility of biomass-based power plant in off-grid mode to present optimal planning for reliable electrification to Tehran. To achieve this goal, size optimization and sensitivity analysis of the proposed hybrid renewable electric system (HRES) is performed by simulating a model in HOMER software to determine the most economical and environment-friendly HRES for the studied area. The assessment criteria for selection of optimal architecture are based on the lowest of net present cost (NPC), cost of energy (COE), and carbon emission quantity (CEQ). Accordingly, HOMER proposes the seven feasible HRES that among them, the biomass generator (BG), photovoltaic (PV) and Wind turbine (WT) hybrid system including 3,181 kW PV panels, 4300 kW WT, a 5,100 kW BG, 17,035 kWh battery storage and 4,415 kW converters is the most optimum power system. Besides, the aforesaid system has COE of 0.281 $/kWh and NPC of 113 M$. Techno-economic comparison of seven systems shows that the integration of PV and WT with biomass systems could be an effective method to make a cost-optimal and reliable HRES, especially in a large scale city- for low-carbon and climate-resilient communities.

The development of hybrid renewable energy systems (HRESs) can be the most feasible solution for a stable, environment-friendly, and cost-effective power generation, especially in rural and island territories. In this studied HRES, solar and wind energy are used as the major resources. Moreover, the electrolyzed hydrogen is utilized to store energy for the operation of a fuel cell. In case of insufficiency, battery and fuel cell are storage systems that supply energy, while a diesel generator adds a backup system to meet the load demand under bad weather conditions. An isolated HRES energy management system (EMS) based on a Deep Q Network (DQN) is introduced to ensure the reliable and efficient operation of the system. A DQN can deal with the problem of continuous state spaces and manage the dynamic behavior of hybrid systems without exact mathematical models. Following the power consumption data from Basco island of the Philippines, HOMER software is used to calculate the capacity of each component in the proposed power plant. In MATLAB/Simulink, the plant and its DQN-based EMS are simulated. Under different load profile scenarios, the proposed method is compared to the convectional dispatch (CD) control for a validation. Based on the outstanding performances with fewer fuel consumption, DQN is a very powerful and potential method for energy management. [ABSTRACT FROM AUTHOR]

From a worldwide perspective, increasing grid reliability by applying renewable energies is one of the most affordable and environmentally-friendly options available for governments. In this study, the possible numbers of future rural power outages in Iran were predicted using machine learning methods based on nine different prediction models such as PLS Regression, Basian Ridge, and LARS Lasso. Then, the predicted blackouts were imported into the grid tool of HOMER software to analyze a common grid-connected HRES that includes PV, biodiesel generator, and battery bank under three power outage scenarios, including peak-time outages, planned outages, and random outages. The analyzed results until 2040 showed that using renewable sources to electrify possible annual blackouts under a day-hours planned power outage scheme can be an affordable solution with energy costs ranging from 0.066 to 0.070 $/kWh. With less than a 5% increase over the national energy tariff, more than 15% of the supplied electricity was renewable and without any blackouts. Furthermore, the sensitivity analysis showed that the government must keep the power outage's mean repair time to less than 2 h to ensure the effective use of renewables and solve the increasing rural blackouts problem in the hot months of the year. • Nine linear regression machine learning methods are evaluated for outage prediction. • The summer possible outages by 2040 are estimated to be > 90 h per year in Iran. • Day-hours planned outage scenario showed proper compatibility with the hybrid system. • Optimized system has a 0.06 $/kWh energy cost and more than a 15% renewable fraction. • The CO 2 emissions are decreased by an average of 16–28% compared to the pure grid. [ABSTRACT FROM AUTHOR]

Diesel generators have long been in use in rural communities in Nigeria despite the impact of emissions caused by these generators on the environment. Due to the high cost and fluctuation in the diesel price and the need for a greener environment, such electric generating systems seem not to be economical and environmentally friendly and need to be addressed. The potential of utilizing the major renewable energy sources prevailing in the Umuejim Amorka community was investigated based on related site surveys and data collected from each household. This paper also investigates the feasibility and economic viability of employing a hybrid-electric system in rural communities. The HOMER software that analyzes system configuration was used to study the application and functional limitations of each hybridized arrangement. The results showed that the renewable energy (RE) based system, photovoltaic (PV)//battery(B), has the lowest cost of energy (COE) and net profit cost (NPC) compared to the PV/Diesel Generator (DG)/B and standalone DG systems. Although the diesel generator (DG) hybrid-electric system (HES) has lower NPC and COE values compared to PV/DG/B, the DG system has the highest significant pollution emission. Furthermore, the result revealed that the PV/B system has the lowest capital and total costs compared to the other two HESs. Moreso, the PV/B system, has the highest return on investment (ROI), making the system the most economically viable and adjudged to be a better candidate for rural community electrification demands. [ABSTRACT FROM AUTHOR]

Several obstacles impede renewable energy penetration into the global energy sector. Amongst the apparent challenges which require credible research attention, is the selection of appropriate energy storage technologies in the context of intermittent renewable resources and frequent grid outages. Given these, the present study investigated the technical, economic, and environmental effects of an erratic national grid on four distinct battery technologies in hybrid wind, solar, and diesel energy systems. The study was conducted at Baze University Abuja, Nigeria using the Hybrid Optimization Model for Electric Renewables software. The battery types considered are vanadium redox flow battery (VRB), lead-acid battery, nickel-iron battery, and lithium-ion battery (LIB). The VRB-based hybrid energy systems demonstrated superior performances in meeting the electricity demands of the university at the lowest net present cost, levelized cost of energy, and carbon dioxide emissions of $6,328,003.00, $0.0722/kWh, and 21,754 kg/year respectively. This battery technology is characterized by storage depletion, throughput, and losses of 796 kWh/year, 406,570 kWh/year, and 182,757 kWh/year respectively. The sensitivity analysis showed that the frequency and duration of main grid outages affect the optimal systems' economics, component sizes, battery energy losses, battery energy storage depletion, and renewable energy penetration. • Performance of HRES utilizing different battery technologies has been analyzed. • The analysis considered grid outage frequency and mean repair time. • Frequent grid outage impacts battery losses, storage depletion, and state of charge. • Compared to other batteries, VRB is superior in complementing HRES operation. • HRES performance can be improved by selecting an appropriate battery technology. [ABSTRACT FROM AUTHOR]

The operational safety and reliability of the railway in monitoring systems are constantly increasing. However, the self-powered functioning of sensors utilizing energy harvesting technologies could be a challenge due to wireless sensors in the railway. This paper presents a hybrid multimodal renewable energy harvesting system (HHMRES) to power the wireless monitoring sensors such as accelerometer, humidity sensor, inclinometer, and light sensor alongside the railway in remote areas. The system design consists of a multimodal renewable energy system, power generation, and energy storage system. A hybrid solar photovoltaic system combined with a 3D printed wind turbine coupled with an electromagnetic generator was proposed as HHMRES to harvest solar and wind energy simultaneously. The harvested energy can be stored in super-capacitors and utilized for wireless monitoring sensors alongside the railway. A theoretical model has been developed to characterize the HHMRES. The total pressure and velocity contours were studied through the simulations in ANSYS FLUENT. The experiments were carried out to validate the performance and dynamics of the HHMRES by simulating solar radiations and wind flow with a solar simulator and the wind tunnel, respectively. The results showed that the average output power of the proposed system was 12.31 W at 17.5 m/s wind speed and 1700 W/m2 solar radiations. The techno-economic optimization of HHMRES was performed in HOMER software to find the most optimal design structure, capital cost, operating cost, and replacement cost of the proposed model. The harvester was demonstrated to have significant power output to operate wireless sensors alongside the railway. • The design for Harvester of hybrid multimodal renewable energy system (HHMRES) is proposed. • The system is the compensation of solar, wind, and electromagnetic to harvest the energy. • Theory and analysis show the performance of the hybrid harvester. • The output power of the HHMRES is 12.31 W at 17.5 m/s and 2.660 W at 5.5 m/s. • The results are productive for the power supply of the wireless sensors in the railway. [ABSTRACT FROM AUTHOR]

A hybrid system proposed by three different specifications for the equipment of a tourist lodge in the headland of south-west Morocco was sized by analysing the limits of load profile constraints, such as hour-to-hour variability (HHR), day-to-day variability (DDR) and the operating reserve rate (ROR). Based on the three-factor Doehlert matrix recommendations, the simulations employed an energy-sizing tool for hybrid renewable-energy systems. Testing was conducted with DDR at 5–30%, HHR at 10–30% and ROR at 0–20%. Under these conditions, a second-order polynomial relationship with a correlation rate of ~90% was found between the net present cost (NPC) of the system, the levelized cost of electricity and the various constraint factors. The first specification, SPC(1), composed of generators and batteries, was introduced to control and validate the simulation independently of renewable energy, which showed a positive manifestation with the imposed constraints. The analysis expanded by introducing solar and wind energy resources. The SPC(2) configuration added PV modules to the SPC(1) and the SPC(3) configuration added wind turbines to SPC(2). The effect of DDR, HHR and ROR in the trials was significant by linear regression. At the same time, only DDR had a significant quadratic regression. The others, with their pairwise interactions, were insignificant. The desirability procedure made it possible to calculate the maximum limits of load profile constraint variables leading to targets of LCOE = 0.41 US$/kWh and NPC =  US$320 080.1 of the load profile constraints: the DDR = 15.47% and the HHR = 26.55% at an ROR rate of 17.77%. [ABSTRACT FROM AUTHOR]

Salalah is known for its Al-Khareef unique weather that is marked by influx of tourists into the community resulting in high electrical load demand during the Al-Khareef season. This paper investigates the viability of two hybridised energy systems for application in Salalah community. The result demonstrated that the Photovoltaic, Wind and Battery combination is more cost effective in terms of energy consumption, initial cost and renewal price, in comparison to the other hybrid energy system. The Homer Pro software, return on investment and internal rate of return analysis showed that the Photovoltaic/Wind/Battery scheme commands higher economic and environmental viability, presenting the Photovoltaic, Wind and Battery scheme as a better option to meet the power demand for Salalah city.

Smart grid is a network created through information technology, communication technology and electrical power systems. It is simply a "smarter" power grid which ensures a two-way communication between user and the power supplier. This work proposes a smart microgrid design hybrid renewable energy system based on solar, grid and wind energy resources. The optimization has been performed using homer software programme to get the best and optimal operation system. Hybrid system combines several energy systems together which offer increased energy reliability and security, and carry a large economic opportunity in terms of cost saving. A typical microgrid system would also include intelligent management that interfaces with the equipment via wired or wireless communication protocols. In the present work the optimization model has been developed for the optimal operation of the system. The modelled system collects meteorological and load data from a town. The optimal hybrid system design is realized by satisfying the load demand, nonlinear seasonal variations and equipment constraints. The main focus of the system is on operation of smart microgrids to maximize usage of green energy, reduction of environmental emissions, decrement of levelized cost of electricity and intelligent management of overall system. [ABSTRACT FROM AUTHOR]

This work presents the results of a study to optimize the production of electricity, by hybrid system Photovoltaic - Diesel - Batteries, to power the village of Kalakala in the north of Côte d'Ivoire. The study site is an isolated rural community, powered by a diesel generator. It is located in northern Côte d'Ivoire. HOMER software has been used for system simulation and optimization. The result of this study is then compared to those of PV - Batteries and diesel alone systems. From the results of the simulations, it appears that the optimal combination of the hybrid system includes a diesel generator of 50 kW, a photovoltaic field of 46 kW, 10 batteries of 48V and a converter of 100 kW. With a photovoltaic penetration rate of 52.7%, this system, compared to the photovoltaic - batteries system, reduces the photovoltaic field by 56%, the number of batteries by 61.5% and increases battery life by 42.84%. Compared to diesel alone, it reduces fuel consumption and the quantity of CO2 by 60% and improves diesel efficiency by 17%. The cost of generating electricity for the hybrid system is €0.373/kWh compared to €0.466 and €0.608/kWh respectively, for the PV-Batteries and diesel alone systems. The hybrid system with the best technical, economic and environmental performance could be a good alternative for generating electricity in remote communities. [ABSTRACT FROM AUTHOR]

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The paper focuses on the use of the Homer software on an autonomous hybrid system. The dedicated Homer software is intended for the energy management analysis of renewable electricity sources. The program simulates the operation of the systems, performing calculations on energy variations for each of the 8760 hours (specific to one year).

Iran is one of the most energy-consuming countries, especially in the construction sector, and more than 40% of its energy consumption is in the construction sector. Therefore, considering the very high potential of Iran in the field of solar energy, the need to pay attention to providing part of the energy required by buildings by solar energy seems necessary. The study of the effect of climate on the performance of a BIPV has not been done in Iran so far. Also, the use of ranking methods using the weighting of parameters affecting the performance of BIPV has not been done so far. The purpose of this study is to investigate the power supply of BIPV connected to the grid in the eight climates of Iran. Technical–economic–environmental energy analyses were performed by HOMER 2.81 software. In order to study different types of BIPV, four angles of 0°, 30°, 60°, and 90° were considered for the installation of solar cells. The effective output parameters of HOMER software were weighted by the Stepwise Weight Assessment Ratio Analysis (SWARA) method based on the opinion of experts, and it was observed that payback time (year) has the highest weight among the studied criteria. Then, different cities were ranked using the evaluation based on distance from the average solution (EDAS) method. The results showed that Jask is the most suitable and Ramsar is the most unsuitable city. Also, the results of the EDAS method were confirmed by Additive Ratio Assessment (ARAS), Weighted Aggregates Sum Product Assessment (WASPAS), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods.