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Amidst rapid technological advancements in the energy sector and increasing demands for sustainable practices, the transition to renewable energy sources is crucial for addressing environmental and economic challenges. This study optimizes a hybrid renewable energy system (HRES) incorporating photovoltaic panels, wind turbines, fuel cells, and battery storage in Libya's Darnah and Alkhums regions. By employing advanced optimization techniques, including Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), Ant Colony Optimization (ACO), and Genetic Algorithms (GA), this research enhances system performance and efficiency. The Alkhums region achieved the lowest cost of energy (COE) at $1.86 using PSO, while Darnah recorded a COE of $1.875 via WOA. Additionally, Darnah demonstrated superior Renewable Energy Fraction (REF) utilization at 97.95% with ACO. This study highlights the effectiveness of integrating hydrogen technology within HRES, offering a viable pathway for sustainable energy solutions in Libya and similar regions, thereby supporting global sustainable development and climate policies. • Optimized a hybrid renewable system with PV, Wind, Battery, and Fuel Cell components. • Evaluated optimization algorithms: PSO, WOA, ACO, and GA. • Conducted study in Darnah and Alkhums, Libya. • Achieved lowest COE using WOA in Darnah and PSO in Alkhums. • Achieved 97.95% Renewable Energy Fraction in Darnah with ACO. [ABSTRACT FROM AUTHOR]

A critical issue regarding the unreliable electricity supply in regions experiencing frequent grid outages poses significant economic and social challenges. Despite the integration of renewable energy sources like photovoltaic (PV) systems, the intermittent nature and low reliability of these resources necessitate additional energy storage solutions. The study investigates the effectiveness of various power system configurations, including PV only, PV/BES, and PV/BES/H 2 systems. Using HOMER software, the study delves into investigating the impact of different outage parameters, specifically focusing on the outage durations and frequencies to the reliability and cost-effectiveness of these systems. The study analyzes how these outage parameters influence the loss of power supply probability (LPSP) and the cost of energy (COE). Three cases were being investigated in this study, which are Case 1: Varying mean outage duration (MOD) with fixed outage frequency (OF), Case 2: Varying OF with MOD and Case 3: Varying both the MOD and OF. The inclusion of H 2 storage significantly reduced the LPSP in Case 1, from a range of 0.882%–2.79% in the PV/BES system to a much lower range of 0.15%–0.392%. In Case 2, the PV/BES/H 2 system also markedly improved reliability, lowering the LPSP from 0.0751% to 1.28% in the PV/BES system to just 0.0279%–0.189%. The results of Case 3 demonstrate that OF has a greater impact on system reliability, as evidenced by a significantly larger rate of change in LPSP when varying OF with constant MOD compared to varying MOD with constant OF. Therefore, the inclusion of energy storage significantly enhances reliability, with the PV/BES/H 2 system showing the lowest LPSP values in both cases. However, COE for the PV/BES/H 2 system was higher in both cases, ranging from 0.22 to 0.326 $/kWh, compared to 0.101 to 0.156 $/kWh for the PV/BES system. This highlights the need for advancements in H 2 storage technology to reduce cost. These findings underscore the critical importance of accurately sizing components to ensure a reliable and economical power supply in regions with unstable grids. • This study investigates the reliability and cost-effectiveness of the hybrid systems. • The outage durations and frequencies of the hydrogen-based hybrid systems are investigated. • The loss of power supply probability and the cost of energy parameters are analyzed. • Mean outage duration and outage frequency are investigated to demonstrate LPSP and COE. • This study highlights that the advanced H 2 storage technology can reduce the system cost. [ABSTRACT FROM AUTHOR]

The industrial sector of Pakistan is currently facing severe load-shedding, which ultimately affects its unit production. The greater dependency on conventional energy resources (Thermal, Nuclear, etc.) results in higher production costs and environmental pollution. A sustainable, cost-effective, and environment-friendly solution can help the industrial growth of Pakistan. This article proposes an optimal hybrid energy system (HES) for the industrial sector of Pakistan to overcome the mentioned challenges. The proposed HES is developed in HOMER Pro. Three different energy cases (Case I: Existing energy system including a utility grid and diesel generator, Case II: On-grid Biogas system, and Case III: On-grid PV system with batteries) are considered for the Gourmet food Industry in the Sundar Industrial estate, Pakistan. The Load profile of the selected site was calculated through on-site visits and data provided by the designated utility grid feeder. The analysis shows that Case III is more effective than other cases, indicating reduced Net Present Cost (NPC), Cost of Energy (COE), and Operating Cost (OC) to $ 19.2 million, $0.034/kWh, and $ 573,371/year respectively. Moreover, the On-grid PV system with batteries (Case III) provides an environmentally friendly solution by reducing 63.82% by and 62.22% . Comparing the sensitivity analysis for various grid sell-back prices ($0/kWh, $0.043/kWh, $0.061/kWh, and $0.09/kWh), Case III is more cost-effective than Case II. The revenue generation in Case III is $128,499.41/yr, considering the supply of excess electricity into nearby small industrial loads at $0.065/kWh, this indicates that installing optimal HES in industries will not only help in overall cost reduction but also support in mitigating environmental pollution and load shedding. [ABSTRACT FROM AUTHOR]

As global energy demands surge and the environmental implications of fossil fuel dependence become more pronounced, there is an urgent need to transition toward more sustainable and eco-friendly energy alternatives. This underscores the dire need for sustainable, secure, and environmentally friendly energy solutions. To this end, efficient energy management strategies combined with the optimal design of hybrid renewable energy systems are paramount for judiciously harnessing renewable resources. In such systems, wind turbines, photovoltaic panels, diesel generators, and battery storage must be meticulously sized to ensure cost-efficiency, environmental sensitivity, and resilience against unpredictable load variations. Addressing these design challenges, our study emphasized the significance of strategic efficiency, prudential component selection, and system dependability. We designed an off-grid hybrid renewable energy system, incorporating photovoltaic panels, wind turbines, battery storage, and diesel generators, to meet the annual energy requirements of a university campus. After recording data for a full year, which included metrics on solar radiation, wind speed, ambient temperature, and campus load, we developed a model founded on comprehensive energy management strategies. This model aims to identify optimal design parameters, reduce annual costs, achieve sustainable energy benchmarks, and ensure a harmonious power exchange between system components. For optimization, we used an array of algorithms, notably the genetic algorithms, particle swarm optimization, gravity search algorithms, and hybrid algorithms, such as the hybrid genetic algorithm-particle swarm optimization and the hybrid gravity search algorithm-particle swarm optimization, supplemented by the HOMERPro software. Our findings revealed that the integration of photovoltaic panels with battery storage led to an annual system cost of $671,474.98, a levelized cost of energy of $0.1800, a total net present cost of $10,898,221.74, and a renewable energy fraction of 100%. It became evident that the hybrid genetic algorithm combined with particle swarm optimization, when aligned with astute energy management strategies, was more effective in determining optimal design parameters than other methodologies. Through this research, we offer profound insights into the dynamics of hybrid renewable energy systems, serving as a guide for pragmatic design and tangible implementation. [ABSTRACT FROM AUTHOR]

Abstract The off-grid Hybrid Renewable Energy Systems (HRES) demonstrate great potential to be sustainable and economically feasible options to meet the growing energy needs and counter the depletion of conventional energy sources. Therefore, it is crucial to optimize the size of HRES components to assess system cost and dependability. This paper presents the optimal sizing of HRES to provide a very cost-effective and efficient solution for supplying power to a rural region. This study develops a PV-Wind-Battery-DG system with an objective of 3E analysis which includes Energy, Economic, and Environmental CO2 emissions. Indispensable parameters like technical parameters (Loss of Power Supply Probability, Renewable factor, PV fraction, and Wind fraction) and social factor (Human Developing Index) are evaluated to show the proposed modified Harris Hawks Optimization (mHHO) algorithm’s merits over the existing algorithms. To achieve the objectives, the proposed mHHO algorithm uses nine distinct operators to obtain simultaneous optimization. Furthermore, the performance of mHHO is evaluated by using the CEC 2019 test suite and the most optimal mHHO is chosen for sizing and 3E analysis of HRES. The findings demonstrate that the mHHO has achieved optimized values for Cost of Energy (COE), Net Present Cost (NPC), and Annualized System Cost (ASC) with the lowest values being 0.14130 $/kWh, 1,649,900$, and 1,16,090$/year respectively. The reduction in COE value using the proposed mHHO approach is 0.49% in comparison with most of the other MH-algorithms. Additionally, the system primarily relies on renewable sources, with diesel usage accounting for only 0.03% of power generation. Overall, this study effectively addresses the challenge of performing a 3E analysis with mHHO algorithm which exhibits excellent convergence and is capable of producing high-quality outcomes in the design of HRES. The mHHO algorithm attains optimal economic efficiency while simultaneously minimizing the impact on the environment and maintaining a high human development index.

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%.

Hybrid energy system (HES) is considered a solution to the energy supply issue, particularly in rural areas to achieve their sustainable development goals. The rise in energy consumption has increased the appeal of renewable resources, because of their potential to supply consumers with competitive, carbon-free electricity. This paper suggests strategies for managing energy and the most recently published optimizers for designing a stand-alone HES positioned in a remote region of southwest Egypt. This HES includes two green energy sources (wind and solar) and a storage system for energy (battery) as the first backup in addition to a second backup (diesel). The most recent sizing techniques employing the Chernobyl disaster optimizer, dynamic control cuckoo search (DCCS), and gold rush optimizer have been suggested to obtain the optimal design of the utilized HES. Furthermore, an in-depth evaluation of the applied optimization approaches has been achieved based on a comparative study. A detailed analysis of the studied algorithms aims to identify the optimum algorithm that provides the lowest possible cost at the highest level of reliability for the proposed HES. The simulation results verified that, the DCCS algorithm outperformed other algorithms, indicating its potential for achieving promising solutions. [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%. [ABSTRACT FROM AUTHOR]

The off-grid Hybrid Renewable Energy Systems (HRES) demonstrate great potential to be sustainable and economically feasible options to meet the growing energy needs and counter the depletion of conventional energy sources. Therefore, it is crucial to optimize the size of HRES components to assess system cost and dependability. This paper presents the optimal sizing of HRES to provide a very cost-effective and efficient solution for supplying power to a rural region. This study develops a PV-Wind-Battery-DG system with an objective of 3E analysis which includes Energy, Economic, and Environmental CO2 emissions. Indispensable parameters like technical parameters (Loss of Power Supply Probability, Renewable factor, PV fraction, and Wind fraction) and social factor (Human Developing Index) are evaluated to show the proposed modified Harris Hawks Optimization (mHHO) algorithm's merits over the existing algorithms. To achieve the objectives, the proposed mHHO algorithm uses nine distinct operators to obtain simultaneous optimization. Furthermore, the performance of mHHO is evaluated by using the CEC 2019 test suite and the most optimal mHHO is chosen for sizing and 3E analysis of HRES. The findings demonstrate that the mHHO has achieved optimized values for Cost of Energy (COE), Net Present Cost (NPC), and Annualized System Cost (ASC) with the lowest values being 0.14130 $/kWh, 1,649,900$, and 1,16,090$/year respectively. The reduction in COE value using the proposed mHHO approach is 0.49% in comparison with most of the other MH-algorithms. Additionally, the system primarily relies on renewable sources, with diesel usage accounting for only 0.03% of power generation. Overall, this study effectively addresses the challenge of performing a 3E analysis with mHHO algorithm which exhibits excellent convergence and is capable of producing high-quality outcomes in the design of HRES. The mHHO algorithm attains optimal economic efficiency while simultaneously minimizing the impact on the environment and maintaining a high human development index. [ABSTRACT FROM AUTHOR]

The power generation capacity must be increased to accommodate population growth and address the lack of electricity access in rural areas. Traditional power plants in South Africa are unable to keep up with the growing demand for electricity. By strategically planning and building clusters of renewable energy sources like solar and wind, microgrid operators can provide a sustainable solution that boosts electricity supply while being cost-effective and environmentally friendly. Utilizing renewable energy can help alleviate strain on power plants by reducing peak demand in constrained distribution networks. The benefits of renewable energy include lower electricity expenses, enhanced system reliability, investment reallocation, and reduced environmental impact. These advantages will enhance the efficiency of the power system and contribute economic value to society. However, integrating solar power into the network infrastructure presents challenges such as fundamental changes in network structure, its intermittent nature due to unpredictability, and geographical constraints, which can complicate the task of grid operators in balancing electricity supply and demand within system limits while minimizing costs. The study employs Homer Pro 3.18.1 software to assess the economic costs and benefits of effectively integrating renewable technologies into the power grid. The aim is to evaluate the economic and technical feasibility of investing in renewable energy projects within the network. The research outcomes can guide power system operators, planners, and designers in leveraging solar energy to drive economic growth and industrial advancement, as well as assist independent power producers in making informed investment choices. [ABSTRACT FROM AUTHOR]

A new concept based on Power Plant Units, able to deliver renewable energy on demand, for the transition from fossil fuels to renewable energy in Switzerland is presented. The technically realized efficiencies showed that complete electrification leads to the most efficient energy system and cheapest electricity. The electricity demand is expected to almost double, and the overall energy cost will increase by 20% compared to 2019. However, the technical challenges of seasonal electricity storage, without any reserves and redundancy, amounts to 20 TWh. Hydropower and PV without storage produce the cheapest electricity. Future nuclear fission technologies, e.g., molten salt Thorium breading reactor -- currently still in an experimental stage--might become the most economical and least environmental impact solution for CO2 neutral continuous electricity production. The opportunities for a massive increase of hydroelectric production are limited, already shifting the use of water (9 TWh) from summer to winter is a great challenge. PV and hydrogen production in Switzerland have the advantage to provide approximately 75% of the electricity without seasonal storage leading to significantly lower electricity cost than from imported hydrogen or synthetic hydrocarbons. The most economical solution for aviation and reserves is imported bio-oil converted to synthetic Kerosene, for which large storages already exist. [ABSTRACT FROM AUTHOR]

Amidst the current global pursuit for access to energy by all as well as energy transition, the actual performance of existing power plants, particularly in developing countries, has often attracted little interest in scientific research. This study evaluated the performance of selected power plants in Uganda using the techno-economic performance assessment model based on actual operational data of hydropower, solar photovoltaic, cogeneration, and thermal power plants for the period 2010–2021. The analysis revealed that the average combined capacity factors are 19.8%, 22.9%, 18.4% and 58.6%, respectively, for thermal power plants, co-generation power plants, solar power plants and hydropower power plants. Furthermore, the levelised cost of electricity for the selected power plants’ financial performance is found to be lower than the retail price for a unit of electricity in Uganda. Overall, the study revealed that the real-life techno-economic performance of the selected power plants in Uganda agrees with the globally expected performance ranges.

The Central Business District (CBD) office building is making efforts to reduce building electricity costs, and one alternative is solar power plant installation. PT. Rancang Prima Sejahtera, engaged in the solar energy industry, conducts consulting services with Central Business District office buildings, so PT. Rancang Prima Sejahtera made an indicative proposal with several solar power plant installation scenarios to be installed on the roof of the Central Business District office building. Four scenarios are created from the combination of 2 PV modules and two inverters. Each scenario created will be assessed for the level of opt, and the investment value will be calculated. In combining components using the principles of the Vereun Deutsche Ingineuer (VDI) 2222 method and assessed each scenario using six aspects of assessment. Meanwhile, the investment analysis assessment uses the parameters of Cost of Energy (CoE), Net Present Value (NPV), Internal Rate of Return (IRR), Benefit-Cost Ratio (B-CR), and discounted payback period. The results of the analysis conducted found that the third scenario was the best scenario with a percentage of the design value of 82.5%, CoE value of Rp398.31/kWh, NPV value of Rp2,451,719,005, IRR percentage of 23.75%, B-CR value of 7.8, and DPP value for 6.8 years with a project life of 30 years. The findings of the investment research indicate that the implementation of solar power plant installations in office buildings located in Central Business Districts yields long-term cost reductions in electricity expenses over a 30-year period, as opposed to relying solely on the services provided by the State Electricity Enterprise.

The welfare of the villages is one of the primary objectives of the rural electrification programmes. Compared to electrifying urban regions, electrifying rural areas is more expensive. Energy requirements in rural areas can be met using hybrid energy technologies. This study proposes a cost-effective power solution to reduce the net present cost (NPC), cost of energy (COE), unmet loads and CO2 emissions. Grey Wolf Optimizer (GWO) and Homer Pro are used to optimize the size of the components of the system. The combination of solar, wind and biogas with a battery storage system is cost-effective with zero unmet loads. Of the three combinations considered, the values of COE and NPC for combination-1 were 0.156 ($/kWh) and $2.05 M respectively. The comparative analysis of optimization between the GWO technique and Homer Pro carried out shows that the value of COE and NPC are reduced by 5.45% and 3.30% respectively. [ABSTRACT FROM AUTHOR]

Electricity supply reliability in an electricity distribution network is majorly affected due to unexpected power failures and power cuts. A hybrid renewable energy system (HRES) with the optimal size of renewable energy sources can substantially improve power reliability. Therefore, this article develops an objective function incorporating socio‐techno‐economic‐environmental (STEE) factors for HRES optimal sizing to supply reliable power to a rural village. The factors considered in the objective function are namely social (employment generation factor, human progress index, and land cost), technical (excess energy factor, renewable energy portion, and loss of power supply probability), economical (total net present cost, cost of energy, and annualized cost of system), and environmental (emission cost). In this article, for the first time, marine predators algorithm (MPA) based metaheuristic optimizer is devised to address the sizing optimization problem of HRES. Three HRES configurations, having different arrangements of diesel generator (DG), biogas generator (BG), battery (BAT), wind turbine (WT), and photovoltaic (PV), are examined utilizing MPA, particle swarm optimization (PSO), salp swarm algorithm (SSA), and genetic algorithm (GA) for optimal configuration. Due to the lowest value of economical and environmental factors and the highest value of the social factor, the PV‐WT‐BAT‐BG‐DG configuration is optimal compared to other investigated configurations with MPA. Comparing the four optimizers, MPA has the best STEE factor values, as well as stronger convergence, greater ability to escape from local minima, and higher ability to approach the global optimum. Additionally, by contrasting it with the PSO result for the three HRES configurations, the MPA result quality is confirmed. Furthermore, the cost of energy (0.1799 $/kWh) of the optimal configuration is less than the latest addressed in the literature. [ABSTRACT FROM AUTHOR]

A new concept based on Power Plant Units, able to deliver renewable energy on demand, for the transition from fossil fuels to renewable energy in Switzerland is presented. The technically realized efficiencies showed that complete electrification leads to the most efficient energy system and cheapest electricity. The electricity demand is expected to almost double, and the overall energy cost will increase by 20% compared to 2019. However, the technical challenges of seasonal electricity storage, without any reserves and redundancy, amounts to 20 TWh. Hydropower and PV without storage produce the cheapest electricity. Future nuclear fission technologies, e.g., molten salt Thorium breading reactor - currently still in an experimental stage–might become the most economical and least environmental impact solution for CO2 neutral continuous electricity production. The opportunities for a massive increase of hydroelectric production are limited, already shifting the use of water (9 TWh) from summer to winter is a great challenge. PV and hydrogen production in Switzerland have the advantage to provide approximately 75% of the electricity without seasonal storage leading to significantly lower electricity cost than from imported hydrogen or synthetic hydrocarbons. The most economical solution for aviation and reserves is imported bio-oil converted to synthetic Kerosene, for which large storages already exist.

Applications for alternative energy sources range from very small scale to large scale grid-coupled hybrid energy systems. In addition, hybrid energy systems are safer to generate power and cheaper to produce than single-source energy systems. The main goal of this study is to determine whether renewable energy hybrid system with horizontal axis wind turbine (HAWT) or vertical axis wind turbine (VAWT) is more efficient and cost effective in terms of energy, economics, and environmental performance. The use of the Multi Objective Genetic Algorithm (MOGA) in MATLAB software for the sizing of hybrid sustainable energy system with wind turbine (horizontal and vertical axis), solar photovoltaic, and grid connection is evaluated in this study. The results revealed that the cost of energy, NPC and system total cost for the case where HRES consists of HAWT is $0.02 /kWh, $85,905, and $332,240, respectively, while for the case when VAWT is used, these values are $0.06 /kWh, $129,932 and $502,511, respectively. The renewable fraction and CO2 emission saving are 80.5% and 73.2% for cases 1 and 2, respectively. The use of renewable energy sources will spread more widely and there will be less air pollution as a result of less reliance on grid electricity. The findings from both situations show that adopting HAWTS-based HRESs is more cost effective and efficient for electrifying rural areas. This study paves the way for researchers to focus on types of wind turbines while designing HRESs.

Integrating renewable energy into existing power grids is essential to maintaining a balance between supply and demand. They ensure a stable and reliable energy supply by seamlessly adjusting to the variations in energy production and consumption. This study introduces an innovative approach to achieving energy balance by integrating floating photovoltaic (FPV) systems with hydropower. This combination addresses not only environmental concerns but also the issue of underproduction in hydropower dams. The primary objective is to find the most economical combination of components for a 100% hybrid renewable energy system using a Multi-Objective Genetic Algorithm (MOGA). The integrated system is projected to add 988,508 MWh of electricity to the grid each year, surpassing the required amount needed to meet demand. Despite some energy losses, the contribution of each system is derived from the optimization process, where the FPV system contributes approximately 29% of the total energy produced, while the hydroelectric system provides the remaining 71%. These percentages are based on the modeled energy output of the combined system in the study. The study highlights the consistency and reliability of the FPV source, emphasizing its low cost of energy (COE) and net present cost (NPC). Moreover, implementing a 166.3 MW FPV system significantly reduces 238,739 tons of CO2 emissions. By exploring this approach, ongoing research and development in renewable energy technologies can enhance efficiency, cost-effectiveness, and overall performance, leading to a more robust and sustainable energy balance.

This paper presents the techno-economic feasibility of using grid-connected PV hybrid systems to supply power in large grid-dependent academic institutions. The study was conducted using the administration building of Moi University in Kenya. The power consumption profile of the building was collected using a PCE-360 power analyzer. The peak load demand was found to be 60 kW. Using random variability constants of 4% for day-to-day and 4% time-step load variability, a peak demand of 70.58 kW was obtained, which was used in our simulation. The solar radiation and temperature data for this site were collected from the weather station of the university. The hybrid system was simulated using HOMER Pro software. It was found from the simulation results that the optimal system was the solar PV/grid without battery storage, which had a levelized cost of energy (LCOE) of KSH 8.78/kWh (USD 0.072), net present cost (NPC) of KSH 27,974,492 (USD 230,813), capital expenditure (CAPEX) of KSH 26,300,000 (USD 216,997), and a simple payback period (SPBP) of 5.08 years for a 25-year life span. This system, when compared to the existing grid, showed an 83.94% reduction in the annual electricity bill of the administration building. These results demonstrate a reduction in energy cost by a renewable energy fraction of 67.1%.

This paper presents the techno-economic feasibility of using grid-connected PV hybrid systems to supply power in large grid-dependent academic institutions. The study was conducted using the administration building of Moi University in Kenya. The power consumption profile of the building was collected using a PCE-360 power analyzer. The peak load demand was found to be 60 kW. Using random variability constants of 4% for day-to-day and 4% time-step load variability, a peak demand of 70.58 kW was obtained, which was used in our simulation. The solar radiation and temperature data for this site were collected from the weather station of the university. The hybrid system was simulated using HOMER Pro software. It was found from the simulation results that the optimal system was the solar PV/grid without battery storage, which had a levelized cost of energy (LCOE) of KSH 8.78/kWh (USD 0.072), net present cost (NPC) of KSH 27,974,492 (USD 230,813), capital expenditure (CAPEX) of KSH 26,300,000 (USD 216,997), and a simple payback period (SPBP) of 5.08 years for a 25-year life span. This system, when compared to the existing grid, showed an 83.94% reduction in the annual electricity bill of the administration building. These results demonstrate a reduction in energy cost by a renewable energy fraction of 67.1%. [ABSTRACT FROM AUTHOR]

This paper presents both the techno-economic planning and a comprehensive sensitivity analysis of an off-grid fully renewable energy-based microgrid (MG) intended to be used as an electric vehicle (EV) charging station. Different possible plans are compared using technical, economic, and techno-economic characteristics for different numbers of wind turbines and solar panels, and both single and hybrid energy storage systems (ESSs) composed of new Li-ion, second-life Li-ion, and new lead–acid batteries. A modified cost of energy (MCOE) index including EVs' unmet energy penalties and present values of ESSs is proposed, which can combine both important technical and economic criteria together to enable a techno-economic decision to be made. Bi-objective and multi-objective decision-making are provided using the MCOE, total met load, and total costs in which different plans are introduced as the best plans from different aspects. The number of wind turbines and solar panels required for the case study is obtained with respect to the ESS capacity using weather data and assuming EV demand according to the EV population data, which can be generalized to other case studies according to the presented modelling. Through studies on hybrid-ESS-supported MGs, the impact of two different global energy management systems (EMSs) on techno-economic characteristics is investigated, including a power-sharing-based and a priority-based EMS. Single Li-ion battery ESSs in both forms, new and second-life, show the best plans according to the MCOE and total met load; however, the second-life Li-ion shows lower total costs. The hybrid ESSs of both the new and second-life Li-ion battery ESSs show the advantages of both the new and second-life types, i.e., deeper depths of discharge and cheaper plans. [ABSTRACT FROM AUTHOR]

Green energy technologies have been widely acknowledged as a supplement to conventional power sources due to the finite nature of fossil fuels, ever-increasing load demand and GHG emissions. This paper proposes a HRES that encompasses photovoltaic, electric vehicle, battery system and grid. The viability analysis of the HRES is implemented in this paper by using the load profile of Tucson Mall, U.S. and the meteorological data from the NASA. This study seeks to create a framework for sustainable energy that enhances the performance of the conventional power system by reducing the NPC, payback period, GHG emissions, COE and energy obtained from the grid by using HOMER application. The NPC, COE, payback period and return on investment for the best configuration of the proposed HRES are $1,600,623.00, $0.0420, 4.10 years and 19.0%. The outcomes of the study demonstrate that the most feasible configuration achieved 60.38% of COE and 39.48% of NPC better than case study 1. The optimal HRES has been subjected to a sensitivity analysis to establish the influence of several parameters such as interest rate, load demand, capital cost, inflation rate, solar radiation and temperature on the COE and NPC. The findings of the study demonstrate that the PV system plays an important role in decreasing GHG emissions, NPC and COE as well as achieving the optimal operation of the HRES. The incorporation of green energy technologies into the utility grid can sustainably address the global energy crisis and improve access to electricity. The government agencies can use the findings of this study as a crucial step in increasing the proportion of green energy technology in the global's energy mix. [ABSTRACT FROM AUTHOR]

Wind energy is a clean and practical way to create electricity. It necessitates the assessment of Wind Power Potential (WPP) and its economic analysis at different heights. In this context, this study examines WPP assessment for 62 different locations of 12 states in India from 10 m to 150 m height using six methods. The effectiveness of each method was performed through the computation of Relative Power Density Error (RPDE). The results suggested that the best method to estimate the WPP is the Novel Energy Pattern Factor Method (NEPFM) followed by the Empirical Method of Mabchour (EMM), the Empirical Method of Justus (EMJ), and the Empirical Method of Lysen (EML). A technical assessment is also made using six different wind turbine Models, through the computation of their respective capacity factors, annual power, and energy outputs. Furthermore the economic feasibility of these wind turbines gave Cost of Energy (COE) variation from 0.28 to 15.31 $/kWh at 10 m hub height of wind turbine and 150 m hub height of wind turbine COE varies from 0.10 to 3.53 $/kWh. This study is useful for industry. [ABSTRACT FROM AUTHOR]

The widespread use of green energy sources creates a significant demand for energy storage. Hybrid floating photovoltaic (FPV) and pumped hydro storage (PHS) represent one of the most dependable and cost-effective solutions, which uses the PV system on the water body combined with a pair of lakes with different heights. This study focuses on the load side as well as the PHS capacity factor and aims to lower the cost of energy (COE) by raising the PHS capacity factor. Since building a PHS requires a significant upfront investment, doing so will also lower the COE and enable the acquisition of PHS for large-scale power production, which will guarantee power access in large cities. To simulate the FPV-PHS system, the multi-objective genetic algorithm (MOGA) is employed. Sufficient power management is a prerequisite for achieving system reliability in the best possible hybrid energy system design and implementation. Considering the 60-year system lifespan, the net present cost (NPC) analysis shows that, out of all the communities evaluated, the FPV-PHS system has the lowest NPC and COE. For the optimal configuration (FPV (Block A) 105 MW, PHS 80 MW, FPV (Block B) 357 MW, and the current hydropower plant), the expected NPC and energy costs for implementing the hybrid energy system (HRS) at the chosen location are $44,737,613 and $40/MWh, respectively. The existing FPV system spans 4.65 km2 and lowers the evaporation fraction by 17,279,400 m3. The hybrid FPV-PHS system reduces annual CO2 emissions by 581,830 tons. Our research reveals that a hybrid floating PV and pump storage hydropower system offers more steady clean electricity, implying a great significance for power grid infrastructure.

Abstract One major criterion in the selection of wind farm location is the cost of energy (COE). COE is the cost of producing 1 kWh electric energy on an annual basis. Mathematical model of COE includes site‐specific constants (such as reference height, mean wind speed, shape factors, wind shear coefficient, average temperature, and turbine altitude) and wind turbine parameters (such as maximum power coefficient, total loss of energy, cut‐in/cut‐off wind speed, rated wind speed, rated power, and the fix charge rate). In this work, we evaluate the COE of an onshore wind farm located at Dumat Al‐Jandal (Saudi Arabia) according to the hub height and rotor size. The 99 Vestas turbines can be mounted at a hub height ranging from 105 to 166 m with available rotor diameters of 105, 112, 117, 126, 136, 150, 155, or 163 m. Particle swarm optimization with a normal distribution is used to optimize the COE. Results show that COE is varying around the average value of $0.029335/kWh by ±$0.00021/kWh. The minimum COE was achieved with a rotor diameter of 150 m at hub height of 105 m. COE increases with the increase of hub height. At 105 m‐hub height, COE is almost the same, with a variation of 0.03% (It ranges between $0.029125/kWh and $0.029133/kWh). COE is more sensitive to rotor size than hub height. This investigation revealed that the COE estimation is in a range of 39%–48% greater than that announced COE by the developing project consortium.

Considering the potential of renewable resources in the Persian Gulf islands, this study proposed a hybrid system in two scenarios of limited and unlimited generators. Also, the five wave energy converters’ technical and economic impact was evaluated as a new approach to sustainable electricity generation. In addition, a comprehensive sensitivity analysis was provided for the net present cost relative to cost changes of wave converters. Results indicated that in the scenario of limited generator, the hybrid system, including the photovoltaic panel, the diesel generator, and the Wavestar wave energy converter with a cost of energy 0.224 $/kWh and net present cost of 11 M$ and the unlimited scenario, the photovoltaic panel, the diesel generator, and AquaBuOY wave energy converter hybrid system with the cost of energy 0.209 $/kWh and net present cost 10.3 M$ are the most optimal scenarios. Also, the OWC-SPA converter had the largest electricity generation among the five selected converters. In addition, in the optimal scenario, the cost of energy of the Wavestar wave converter was 0.385 $/kWh, and in the second scenario, the cost of energy of the AquaBuOY wave converter was 2.05 $/kWh. The cost of energy for the photovoltaic panel was 0.0244 $/kWh and it was 0.0394 $/kWh for diesel generator. Finally, the range of changes in the net present cost was estimated from 10.3 M$ to 13.9 M$, despite the fluctuations in wave converter costs.

The industrial sector is the world’s largest energy consumer and carbon emitter. In Iran, the importance of applying new energy resources is even greater due to industrial growth, the capacity shortage of conventional power plants, and the low reliability of power supply during peak times. However, detecting the optimal dispatch strategy for managing the application of nonrenewable sources along with renewable technologies is a major challenge. In this study, we performed the design and optimization of a hybrid energy system, including photovoltaic, wind turbines, a diesel generator, a natural gas generator, and a storage bank, for a small-scale industrial case in a southern industrial park of Iran. The HOMER Pro software was utilized to optimize the hybrid renewable energy system and supply an average demand of about 820 kWh/day through five different dispatch strategies. The results showed that predictive dispatch, with the foresight of renewable production and demand in the next 48 h, outperforms combined dispatch, cycle charging, load following, and generator order dispatch strategies. The optimum scenario showed an 84% renewable fraction, a cost of energy of 0.105–0.120 $/kWh, and about 24.8% excess power, which improves local grid reliability and the potential for renewable energy utilization by the industrial unit. The technical results showed that the optimum use of battery bank capacity based on upcoming predicted power consumption/generation potential effectively reduces the need for installation capacity of power equipment, which is critical for remote industrial demands.

Due to the global energy crisis and the limited availability of conventional fuels and their reserves in certain areas, the utilization of renewable energy resources is significantly paramount for sustainable development. Grid disruptions have been discovered in areas where demand for electricity has surpassed supply. The purpose of this work is to size a grid-integrated hybrid renewable energy system (HRES) during a scheduled power outage. The HRES model was created to meet the requirements for residential load as well as EV charging load at midnight when the residential load is lower. Using the HOMER Pro software tool, the HRES system is developed to satisfy the residential load demand of 1940 kWh/day and the electric vehicle (3-wheeler) charging load requirement of 645 kWh/day, respectively. This study examined the effects of grid purchasing capacity and grid scheduling outages on techno-economic and environmental performance. The results show that the most optimal configuration among the various configurations is the PV/WT/Batt with grid-integrated system, which has a COE of 0.0714 $/kWh, an NPC of $1,822,653, and emits 164,812 kg/yr of CO2 into the environment. The optimized system consists of a 377 kW PV module, a 2 kW wind turbine, an 836 kWh battery bank, and a 237 kW inverter. In addition, the impacts of sensitivity of the grid purchase and selling capacity, and the different tariffs on the techno-economic indicators of the HRES have been investigated. The daytime grid outage lowers environmental emissions and increases the renewable contribution compared to the grid outage at night. Reducing the grid’s purchase capacity while increasing the share of renewable energy provides significant advantages. The stand-alone PV/Batt has a higher COE (0.26 $/kWh) than the PV/Batt system (0.072 $/kWh) with the net metering option connected to the national grid.

The power generation capacity must be increased to accommodate population growth and address the lack of electricity access in rural areas. Traditional power plants in South Africa are unable to keep up with the growing demand for electricity. By strategically planning and building clusters of renewable energy sources like solar and wind, microgrid operators can provide a sustainable solution that boosts electricity supply while being cost-effective and environmentally friendly. Utilizing renewable energy can help alleviate strain on power plants by reducing peak demand in constrained distribution networks. The benefits of renewable energy include lower electricity expenses, enhanced system reliability, investment reallocation, and reduced environmental impact. These advantages will enhance the efficiency of the power system and contribute economic value to society. However, integrating solar power into the network infrastructure presents challenges such as fundamental changes in network structure, its intermittent nature due to unpredictability, and geographical constraints, which can complicate the task of grid operators in balancing electricity supply and demand within system limits while minimizing costs. The study employs Homer Pro 3.18.1 software to assess the economic costs and benefits of effectively integrating renewable technologies into the power grid. The aim is to evaluate the economic and technical feasibility of investing in renewable energy projects within the network. The research outcomes can guide power system operators, planners, and designers in leveraging solar energy to drive economic growth and industrial advancement, as well as assist independent power producers in making informed investment choices.

One major criterion in the selection of wind farm location is the cost of energy (COE). COE is the cost of producing 1 kWh electric energy on an annual basis. Mathematical model of COE includes site‐specific constants (such as reference height, mean wind speed, shape factors, wind shear coefficient, average temperature, and turbine altitude) and wind turbine parameters (such as maximum power coefficient, total loss of energy, cut‐in/cut‐off wind speed, rated wind speed, rated power, and the fix charge rate). In this work, we evaluate the COE of an onshore wind farm located at Dumat Al‐Jandal (Saudi Arabia) according to the hub height and rotor size. The 99 Vestas turbines can be mounted at a hub height ranging from 105 to 166 m with available rotor diameters of 105, 112, 117, 126, 136, 150, 155, or 163 m. Particle swarm optimization with a normal distribution is used to optimize the COE. Results show that COE is varying around the average value of $0.029335/kWh by ±$0.00021/kWh. The minimum COE was achieved with a rotor diameter of 150 m at hub height of 105 m. COE increases with the increase of hub height. At 105 m‐hub height, COE is almost the same, with a variation of 0.03% (It ranges between $0.029125/kWh and $0.029133/kWh). COE is more sensitive to rotor size than hub height. This investigation revealed that the COE estimation is in a range of 39%–48% greater than that announced COE by the developing project consortium. [ABSTRACT FROM AUTHOR]

Efficient coordination in transmission planning and locating variable renewable energy (VRE) generation is important in transitioning to a low carbon electricity system. Renewable Energy Zones (REZ) provide an opportunity to strategically augment and expand the existing transmission network to maximise use of the available renewable resources. The Queensland region of Australia's National Electricity Market provides a unique case for analysis, where complementary patterns of wind and solar supply exist across a broad geographical area. This article presents new information about the nine proposed REZ across the region and their utility in supplying energy as the incumbent fleet of baseload generators is forecast to retire. Understanding their locational and market value provides insight into the underlying cost of energy and its ability to satisfy energy demands. The recent entry cost shocks impacting the VRE industry in the post-pandemic recovery have been quantified, where increases of 23%–44% to the cost of energy have been observed. These increases have been driven by shifts in the capital and operating costs for new projects, which are compounded by the simultaneous increases to the cost of capital. Real world analysis has occurred to support the modelled outcomes and highlight the value of REZ in Queensland. [ABSTRACT FROM AUTHOR]

Concerns surrounding the environment along with inadequate energy supply and high cost of same are responsible for pollution, high energy demand, unpredictable and uneconomical power generation. These have contributed to the widespread agreement that sustainable renewable energy sources (RES) must be developed, particularly in isolated villages where expanding the grid may be challenging and financially unviable for power corporations. As a result, in order to effectively and cheaply utilize the plentiful renewable energy resources, an optimal sizing approach is required. This study is aimed at investigating the economic performance of the hybrid system of a stand-alone Small Hydropower/PV/Diesel generator with battery electricity production. The cost function was minimized using Dragonfly Algorithm (DA) in order to minimize the Cost of Energy (COE) generation. The decision variables are the number of small hydro turbines (NSHP), number of solar panels (NPV), number of batteries (NBATT) and the capacity of Diesel generator (PDG). The developed method is applied to a typical Kiri village in Shelleng Local Government area of Adamawa State. For uniformity, the hourly solar irradiance data were created by converting the monthly average solar irradiance data. A dragonfly optimization technique was utilized to reach an optimum solution for the hybrid system. The result obtained showed that the system components: small Hydropower, solar PV and Diesel generator were able to generate electrical power of 5,783,600 W, 56,259 W and 5.2941e-05 W respectively to meet the energy demand. Results obtained from the developed scheme were compared with those obtained when TORSCHE algorithm was used in optimizing the hybrid system. It was observed that a total energy cost of $5,224,500 was obtained for the developed technique while $5,839,600 was obtained as the total cost for the TORSCHE model. This showed that the developed scheme outperformed the system output from the TORSCHE algorithm in terms of cost of energy by 89.46%. [ABSTRACT FROM AUTHOR]

Due to the global energy crisis and the limited availability of conventional fuels and their reserves in certain areas, the utilization of renewable energy resources is significantly paramount for sustainable development. Grid disruptions have been discovered in areas where demand for electricity has surpassed supply. The purpose of this work is to size a grid-integrated hybrid renewable energy system (HRES) during a scheduled power outage. The HRES model was created to meet the requirements for residential load as well as EV charging load at midnight when the residential load is lower. Using the HOMER Pro software tool, the HRES system is developed to satisfy the residential load demand of 1940 kWh/day and the electric vehicle (3-wheeler) charging load requirement of 645 kWh/day, respectively. This study examined the effects of grid purchasing capacity and grid scheduling outages on techno-economic and environmental performance. The results show that the most optimal configuration among the various configurations is the PV/WT/Batt with grid-integrated system, which has a COE of 0.0714 $/kWh, an NPC of $1,822,653, and emits 164,812 kg/yr of CO 2 into the environment. The optimized system consists of a 377 kW PV module, a 2 kW wind turbine, an 836 kWh battery bank, and a 237 kW inverter. In addition, the impacts of sensitivity of the grid purchase and selling capacity, and the different tariffs on the techno-economic indicators of the HRES have been investigated. The daytime grid outage lowers environmental emissions and increases the renewable contribution compared to the grid outage at night. Reducing the grid's purchase capacity while increasing the share of renewable energy provides significant advantages. The stand-alone PV/Batt has a higher COE (0.26 $/kWh) than the PV/Batt system (0.072 $/kWh) with the net metering option connected to the national grid. [ABSTRACT FROM AUTHOR]

Abstract 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.

Kawaluso Island is one of the outermost islands in Indonesia with a distance of 68 KM from the city of Tahuna or 5-10 hours by boat from the capital of the Sangihe Islands Regency, Tahuna. Currently, electricity on Kawaluso Island is supplied by a diesel power plant (PLTD) with a capacity of 200 kW. This condition causes Kawaluso Island to be electrified 12 hours per day. So that additional sources of power plant are needed so that the electricity on Kawaluso Island is on 24 hours a day. Therefore, a solar power plant (PLTS) is one of alternative as additional power for Kawaluso Island and reduces the cost of production. A diesel power plant where the price of industrial fuel reaches up to Rp. 24.500 and it make Cost of Energy Rp. 10.360/kWh. The method used in this study uses the Levelized Cost of Energy (LcoE) method. The results of the analysis show that the hybrid between diesel power plant and solar power plant 64 kWp and 72 kWp has a Life Cycle Cost (LCC) value of Rp24.389.601.114,40 and Rp. 20.589.498.278,40 With a Cost of Energy (COE) of Rp. 7.432 and Rp. 5.601/kWh. Net Present Value (NPV) obtained is positive. And the payback period is 3 and 9 years of investment and is categorized as feasible to continue.

To combat the adverse environmental effects of fossil fuel burning for power generation and to conserve it for strategic use, new, clean, and renewable energy sources are being utilized for power generation. The study presents techno-economic analysis of a grid-connected solar photovoltaic (PV) power plant to partially meet the energy consumption of the people of Kuttiady village in Kerala, India. The proposed 2315.5 kW installed capacity PV is found to be feasible for the village and can produce 3878.3 MWh of energy annually while the demand is 4044.86 MWh at a plant capacity factor of 19.1% and cost of energy of 290.73 $/MWh. The performance of the proposed PV plant measured in terms of final yield (4.59 h), reference yield (5.64 h), and performance ratio (82%) is compatible and even higher with many such plants in India and other countries. Economic sensitivity analysis is also performed by varying the interest, discount, and inflation rates to check their effect on cost of energy, benefit cost ratio, and payback period. As the interest and discount rates decrease, the cost of energy and payback period also decreases while benefit cost ratio increases. The proposed plant can help in avoiding around 785 tons of greenhouse gases entering the local atmosphere of the Kuttiady village. [ABSTRACT FROM AUTHOR]

The interest for microgrids has increased in the last decades, bringing important conditions such as energy efficiency, reduction of production pollution, reliability of the system. Microgrid as a key of Smart Grid plays a vital role in power losses reduction, voltage profile improvement, mitigating the pollutant emission, enhance the reliability and quality of power system. In this paper the techno-economic and environmental analysis of Karabuk university Microgrid are considered. The Microgrid of Karabuk university campus is simulated and analyzed by HOMER (Hybrid Optimization Models for Energy Resources) software for optimization, sensitivity, demand response and pollutant emissions. The results of the techno-economic and environmental analysis suggest the integration of new distributed generation for 25-years of service time. In the proposed scenario, legalized cost of energy is $0.284 with renewable fraction of 14.8%, net present cost and operating cost decrease to 11.28% and 21.21%, respectively. It has showed that the proposed hybrid microgrid system contributes to the clean university campus concept and provides the lowest cost of electricity with the best payback time. [ABSTRACT FROM AUTHOR]

The pollution and toxic greenhouse gases produced by fossil fuel combustion are troubling as global energy demand continues to rise. To mitigate the consequences of global warming, a transition to sustainable energy sources is necessary. This manuscript presents a feasible community microgrid design in Hazaribagh, Dhaka based on meteorological data that leads to photovoltaic installation on the rooftop of a local community building. This study shows a microgrid design of a system with the lowest cost of energy and a large renewable fraction, which is analysed using the HOMER Pro software. Using real-time data, analysis of the system cost, cost of energy, renewable fraction, unmet load, energy purchased and energy sold is discussed. A suitable case for electrification is also identified and presented for the selected community. The proposed case yields a cost of energy of $0.0357/kWh, which is 52% less than the current tariff rate, with a 70% renewable fraction. This study will provide people in this community with more green energy at a lower cost; in addition, this designed microgrid sells additional energy to the grid to avoid possible power outages. The potential for a positive energy community is also investigated in terms of energy consumption and renewable output of the planned microgrid. [ABSTRACT FROM AUTHOR]

Renewable energy solutions play a crucial role in addressing the growing energy demands while mitigating environmental concerns. This study examines the techno-economic viability and sensitivity of utilizing solar photovoltaic/polymer electrolyte membrane (PEM) fuel cells (FCs) to meet specific power demands in NEOM, Saudi Arabia. The novelty of this study lies in its innovative approach to analyzing and optimizing PV/PEMFC systems, aiming to highlight their economic feasibility and promote sustainable development in the region. The analysis focuses on determining the optimal size of the PV/PEMFC system based on two critical criteria: minimum cost of energy (COE) and minimum net present cost (NPC). The study considers PEMFCs with power ratings of 30 kW, 40 kW, and 50 kW, along with four PV panel options: Jinko Solar, Powerwave, Tindo Karra, and Trina Solar. The outcomes show that the 30 kW PEMFC and the 201 kW Trina Solar TSM-430NEG9R.28 are the most favorable choices for the case study. Under these optimal conditions, the study reveals the lowest values for NPC at USD 703,194 and COE at USD 0.498 per kilowatt-hour. The levelized cost of hydrogen falls within the range of USD 15.9 to 23.4 per kilogram. Furthermore, replacing the 30 kW Trina solar panel with a 50 kW Tindo PV module results in a cost reduction of 32%. The findings emphasize the criticality of choosing optimal system configurations to attain favorable economic outcomes, thereby facilitating the adoption and utilization of renewable energy sources in the region. In conclusion, this study stands out for its pioneering and thorough analysis and optimization of PV/PEMFC systems, providing valuable insights for sustainable energy planning in NEOM, Saudi Arabia. [ABSTRACT FROM AUTHOR]

Using clean energy sources instead of traditional methods of energy production is important to tackle global warming and climate change. As in the rest cities of the Kurdistan Region and Iraq, the national electricity outage crisis continues in Duhok Governorate and the production of energy via different sources is still needed. This paper studies the simulation of two different types of solar energy systems on school roofs using the Homer Pro software. The first is a grid-connected system and the second, is an off-grid system for six different regions of Duhok Governorate, using the solar radiation data for each site. Our findings confirm the preference for on-grid PV over an off-grid PV system at all sites. As the cost of energy in USD per kWh in both grid-tied and stand-alone models varies from one region to another, which is as follows: Amedi (0.089, 0.339), Kani Masi (0.091, 0.0338), Bamarni (0.093, 0.338), Mangesh (0.095, 0.349), Semel (0.107, 0.341), and Akre (0.127, 0.347). The net present cost NPC in both grid-connected and grid-independent for 160 kW PV systems is as follows: Kani Masi ($217303, $260504), Amedi ($217621, $260710), Bamarni ($219007, $260587), Mangesh ($220167, $261239), Semel ($227566, $261222), and finally Akre ($238671, $262203). [ABSTRACT FROM AUTHOR]

The intensity of solar radiation in Thailand is sufficient to produce electricity, thus the government has unconditionally promoted electricity production from solar energy, known as photovoltaic power system. Although it can reduce energy costs, it should also be environmentally friendly. This research aims to design and evaluate the photovoltaic rooftop system by concerning economic feasibility, cost of energy, and the compensation for carbon dioxide emissions. The research methodology also calculates the installation area and the solar power generation potential. Carbon dioxide emissions compensation and cost-effectiveness tools are used to evaluate the overall system. The results revealed that the photovoltaic rooftop system had the production capacity of 31.49 kilowatt-hours with an installation area of 184 m2. Solar panels orient to north direction with 11 degrees tilt from horizontal plane. The PV rooftop system generated the highest electricity around 137.103 kilowatt-hours per year and electricity production per installed system size is 4.354 kilowatt-hours per kilowatt-power. Within the period of 25 years and interest rate of 6.3145 percent, this project would be worthwhileness for the investment because the payback period is 6.83 years, the net present value is 1,523,571.70 baht, internal rate of return is 17.85 percent, benefit–cost​ ratio is 1.77, cost of energy is 2.31 baht per kilowatt-hour, in addition to the project can reduce carbon dioxide emissions by up to 643.77 tons of carbon dioxide equivalent. The promotion of electricity production from solar energy will increase the sustainability of energy and environment. In addition, the project sensitivity study indicated that initial cost, interest rate, and electricity price will be the important factors in making a decision to initiate a project.

The aim of this study is to evaluate the economic, technical, and environmental performances of grid-tied and stand-alone hybrid renewable energy systems (HRESs) in 21 provinces in seven regions of Turkey, considering different regional solar radiation and wind speed diversity. HRES were designed and modeled using the Hybrid Optimization of Multiple Energy Resources software (HOMER PRO) to meet the daily load of 13.26 kWh/day of a household. The analysis results for each province were compared considering the cost of energy, net present cost (NPC), greenhouse gas emissions, renewable fraction (RF), and optimum system configuration. The findings demonstrated that the optimal system configurations are Grid/PV/WT and PV/WT/DG/BESS for grid-tied and stand-alone HRES, respectively. The value of NPC ranges from $\$ $ 2,540.00 to $\$ $ 8,951.00 for grid-tied HRES, while it varies from $\$ $ 23,372.00 to $\$ $ 40,858.00 for stand-alone HRES. The provinces of Çanakkale in the Marmara Region and Artvin in the Black Sea Coast Region have the lowest and highest NPC values, respectively, for all systems. The PV capital cost, WT capital cost, BESS capital cost, solar radiation, and wind speed are considered as sensitivity input parameters that might affect the economic output of the HRES in this study. According to the sensitivity analysis, the NPC value as an economic indicator input decreased for both on-grid and off-grid HRES as the wind speed and solar radiation increased. It was also found that when the capital cost of PV panels and WT were changed, the NPC of the stand-alone HRES was in the range of $\$ $ 21,402.27- $\$ $ 29,978.89 for the province of Çanakkale, while it was in the range of $\$ $ 37,518.11- $\$ $ 51,939.00 for the province of Artvin. Moreover, when solar radiation and wind speed were increased, the results showed that NPC and CO2 emissions decreased by 9.30% and 9.23%, respectively, for Çanakkale, and by 25.58% and 66.95%, respectively, for Artvin. Finally, the results indicated that the optimal system configuration changes depending on the PV and WT capital cost variations for the grid-tied HRES. This research can be useful for planning grid-tied and stand-alone HRES from different aspects in Turkey, as well as other countries around the world. It contributes to the literature by comparing grid-tied and stand-alone HRES to determine the optimum system configuration and to find the best optimization results in seven regions of Turkey under different climate conditions. In addition, most of the studies related to HRES for residential areas in the literature are reviewed in this research, which intends to serve as a guide for engineers and researchers.