Search Results (4,277)

This research focused on determining the technical and economic feasibility of the design of a solar-powered electric vehicle charging station (EVCS) in Cairo, Egypt. Using HOMER Grid, hybrid system configurations are assessed technically and economically to reduce costs and ensure reliability. These systems incorporate photovoltaic (PV) systems, lithium-ion battery energy storage systems (ESS), and diesel generators. A comprehensive analysis was conducted in Cairo, Egypt, focusing on small vehicle charging needs in both grid-connected and generator-supported scenarios. In this study, a 468 kW PV array integrated with 29 units of 1 kWh lithium-ion batteries and supported by time-of-use (TOU) tariffs, were used to optimize energy utilization. This study demonstrated the feasibility of the system in a case of eight chargers of 150 kW each and forty chargers of 48 kW. Conclusions suggest that the PV + ESS has the lowest pure power costs and reduced carbon emissions compared to traditional network-dependent solutions. The optimal configuration of USD 10.23 million over 25 years, with lifelong savings, results in annual savings of tool billing of around USD 409,326. This study concludes that a solar-powered EVC in Egypt is both technically and economically attractive, especially in the light of increasing energy costs. Full article

The study investigates a hybrid energy system integrating photovoltaic (PV) panels, micro-CHP units, battery storage, and thermal storage to meet the winter energy demands of a residential building in Bacău, Romania. Using real-world experimental data from amorphous, polycrystalline, and monocrystalline PV panels, C++ Model 1 simulates building energy needs and PV system performance under varying irradiance levels. The results show that PV systems alone cannot meet the total winter demand, with polycrystalline slightly outperforming monocrystalline, yet still falling short. A second computational model (C++ Model 2) simulates hybrid energy flow, demonstrating how the CHP unit and storage systems can ensure off-grid autonomy. The model dynamically manages energy between components based on daily irradiance scenarios. The findings reveal critical thresholds for PV surplus, optimal CHP sizing, and realistic battery and thermal storage needs. This paper provides a practical framework for designing efficient, data-driven hybrid solar–CHP systems for cold climates. The novelty lies in the integration of real-world PV efficiency data with a dynamic irradiance-driven simulation framework, enabling precise hybrid system sizing for winter-dominant regions. Full article

Hybrid Renewable Energy Systems (HRESs) can be an effective and sustainable way to provide electricity for remote and rural villages in Morocco; however, the design and optimization of such systems can be a challenging and difficult task. In this context, the objective of this research is to design and optimize different (HRESs) that incorporate various renewable energy technologies, namely Photovoltaics (PVs), wind turbines, and Concentrating Solar Power (CSP), whereas biomass generators and batteries are used as a storage medium. Overall, 15 scenarios based on different HRES configurations were designed, simulated, and optimized by the HOMER software for the site of Ain Beni Mathar, located in eastern Morocco. Furthermore, the potential CO₂ emissions reduction from the different scenarios was estimated as well. The results show that the scenario including PVs and batteries is most cost-effective due to favorable climatic conditions and low costs. In fact, the most optimal HRES from a technical and economic standpoint is composed of a 48.8 kW PV plant, 213 batteries, a converter capacity of 43.8 kW, and an annual production of 117.5 MWh with only 8.8% excess energy, leading to an LCOE of 0.184 USD/kWh with a CO₂ emissions reduction of 81.7 tons per year, whereas scenarios with wind turbines, CSP, and biomass exhibit a higher LCOE in the range of 0.472–1.15 USD/kWh. This study’s findings confirm the technical and economic viability of HRESs to supply 100% of the electricity demand for rural Moroccan communities, through a proper HRES design. Full article

The integration of photovoltaic (PV) panels in greenhouses enables dual land use, combining crop production with electricity generation. However, PV installations can reduce both the intensity and uniformity of light at the canopy level, potentially affecting crop growth. This study employed computational fluid dynamics (CFD) simulations to evaluate the effects of different layouts of commercial-size thin PV modules—both opaque and semi-transparent—installed at gutter height in greenhouses on irradiance and, in particular, on its distribution within the greenhouse. Achieving a homogeneous distribution of light is critical for effective plant growth beneath photovoltaic systems. The influence of greenhouse size and roof shape on the intensity and uniformity of visible radiation was investigated as well. The results showed that during winter (21 December), irradiance in a mono-span tunnel greenhouse was 4–6% higher than in a multi-span large structure; in summer (21 June), this difference increased to 10–13%. Among the opaque PV layouts tested, the north–south (NS) straight-line arrangement provided the most uniform light distribution, outperforming the checkerboard and east–west (EW) layouts. The EW straight-line layout was the least effective regarding light uniformity. Roof shape (arched vs. pitched) had minimal impact on radiation distribution. Semi-transparent PV modules consistently resulted in 17% higher irradiance and more uniform light distribution than opaque ones. These findings can inform efficient PV deployment strategies in greenhouses to enhance both energy yield and crop productivity. Full article

With rapid urbanization, rooftop photovoltaic (PV) systems play an important role in mitigating the energy crisis and reducing emissions, yet achieving scientific and cost-effective deployment at the urban block scale remains challenging. This study proposes a transferable framework that integrates spatial morphology quantification, clustering, and numerical simulation to evaluate PV potential in residential blocks of Jinan, China. Six key morphological indicators were extracted through principal component analysis (PCA), and blocks were classified into five typical types, followed by simulations under different PV material scenarios. The main findings are: (1) Block type differences: Cluster 1 achieved the highest annual generation, 61.76% above average, but with a 75.08% cost increase and a 3.54-year payback. Clusters 4 and 5 showed moderate generation and the shortest payback of 2.91–2.97 years, reflecting better energy–economic balance. (2) PV materials: monocrystalline silicon (m-Si) yielded the highest generation, suitable for maximizing output; polycrystalline silicon (p-Si) produced slightly less but reduced costs by 32.43% and shortened payback by 19.58%, favoring cost-sensitive scenarios. (3) Seasonal variation: PV output peaked in February–March and September–December, requiring priority in grid operation and maintenance. The proposed framework can serve as a useful reference for planners in developing PV deployment strategies, with good transferability and potential for wider application, thereby contributing to urban energy transition and low-carbon sustainable development. Full article

This study investigates the asymmetric trade-off between cost and reliability in the optimal sizing of stand-alone Hybrid Renewable Energy Systems (HRESs) composed of photovoltaic panels (PV), wind turbines (WT), battery storage, a diesel generator (DG), and an inverter. The optimization is formulated as a multi-objective problem with Cost of Energy (CoE) and Loss of Power Supply Probability (LPSP) as conflicting objectives, highlighting that those small gains in reliability often require disproportionately higher costs. To ensure practical feasibility, the installation roof area limits both the number of PV panels, wind turbines, and batteries. Two metaheuristic algorithms—NSGA-II and MOPSO—are implemented in a Python-based framework with an Energy Management Strategy (EMS) to simulate operation under real-world load and resource profiles. Results show that MOPSO achieves the lowest CoE (0.159 USD/kWh) with moderate reliability (LPSP = 0.06), while NSGA-II attains a near-perfect reliability (LPSP = 0.0008) at a slightly higher cost (0.179 USD/kWh). Hypervolume (HV) analysis reveals that NSGA-II offers a more diverse Pareto front (HV = 0.04350 vs. 0.04336), demonstrating that explicitly accounting for asymmetric sensitivity between cost and reliability enhances the HRES design and that advanced optimization methods—particularly NSGA-II—can improve decision-making by revealing a wider range of viable trade-offs in complex energy systems. Full article

This paper presents a novel methodology for the optimal sizing of solar photovoltaic (PV) systems in distribution networks by determining the monthly optimum tilt and azimuth angles to maximize solar energy capture. Using one year of solar irradiation data, the Grey Wolf Optimizer (GWO) is employed to optimize the tilt and azimuth angles with the objective of maximizing monthly solar insolation. Unlike existing approaches that assume fixed azimuth angles, the proposed method calculates both tilt and azimuth angles for each month, allowing for a more precise alignment with solar trajectories. The optimized orientation parameters are subsequently utilized to determine the optimal number and placement of PV panels, as well as the optimal location and sizing of shunt capacitor (SC) banks, for the IEEE 69-bus distribution system. This optimization is performed under peak load conditions using the GWO, with the objectives of minimizing active power losses, enhancing voltage profile stability, and maximizing PV system penetration. The long-term impact of this approach is assessed through a 20-year energy and economic savings analysis, demonstrating substantial improvements in energy efficiency and cost-effectiveness. Full article

As the core component of photovoltaic (PV) power generation systems, PV cells are susceptible to subtle surface defects, including thick lines, cracks, and finger interruptions, primarily caused by stress and material brittleness during the manufacturing process. These defects substantially degrade energy conversion efficiency by inducing both optical and electrical losses, yet existing detection methods struggle to precisely identify and localize them. In addition, the complexity of background noise and other factors further increases the challenge of detecting these subtle defects. To address these challenges, we propose a novel PV Cell Surface Defect Detector (PSDD) that extracts subtle defects both within the backbone network and during feature fusion. In particular, we propose a plug-and-play Subtle Feature Refinement Module (SFRM) that integrates into the backbone to enhance fine-grained feature representation by rearranging local spatial features to the channel dimension, mitigating the loss of detail caused by downsampling. SFRM further employs a general attention mechanism to adaptively enhance key channels associated with subtle defects, improving the representation of fine defect features. In addition, we propose a Background Noise Suppression Block (BNSB) as a key component of the feature aggregation stage, which employs a dual-path strategy to fuse multiscale features, reducing background interference and improving defect saliency. Specifically, the first path uses a Background-Aware Module (BAM) to adaptively suppress noise and emphasize relevant features, while the second path adopts a residual structure to retain the original input features and prevent the loss of critical details. Experiments show that PSDD outperforms other methods, achieving the highest $mA{P}_{50}$ scores of 93.6% on the PVEL-AD. Full article

This paper presents the optimal design and cost–benefit analysis of an off-grid solar photovoltaic system integrated with a hybrid energy storage system for a Category 3 rural healthcare facility in Elands Bay, South Africa. The optimal configuration, designed in Homer Pro, consists of a 16.1 kW solar PV array, 10 kW lithium-ion battery, 23 supercapacitor strings (2 modules per string), 50 kW fuel cell, 50 kW electrolyzer, 20 kg hydrogen tank, and 10.8 kW power converter. The daily energy consumption for the selected healthcare facility is 44.82 kWh, and peak demand is 9.352 kW. The off-grid system achieves 100% reliability (zero unmet load) and zero CO₂ emissions, compared to the 24,128 kg/year of CO₂ emissions produced by the diesel generator. Economically, it demonstrates strong competitiveness with a levelized cost of energy (LCOE) of ZAR24.35/kWh and a net present cost (NPC) of ZAR6.05 million. Sensitivity analysis reveals the potential for a further 20–40% reduction in LCOE by 2030 through anticipated declines in component costs. Hence, it is established that the proposed model is a reliable and viable option for off-grid rural healthcare facilities. Full article

Renewable energy sources play a crucial role in the urgent global pursuit of decarbonizing electricity systems. However, persistent grid congestion and lengthy planning approval processes remain the main barriers to the accelerated deployment of new green energy source capacities. Capitalizing on the synergies afforded by co-locating hybrid power plants—particularly those that harness temporally anti-correlated renewable sources such as wind and solar—behind a unified connection point presents a compelling opportunity. To this end, this paper pioneers a comprehensive planning framework for hybrid configurations, integrating transmission grid and renewable energy assets planning to include energy storage systems, wind, and solar energy capacities within a long-term planning horizon. A mixed-integer linear programming model is developed that considers both the technical and economic aspects of combined grid planning and hybrid power plant allocation. Additionally, the proposed framework incorporates the N − 1 contingency criterion, ensuring system reliability in the face of potential transmission line outages, thereby adding a layer of versatility and resilience to the approach. The model minimizes the net present value of costs, encompassing both capital and operational expenditures as well as curtailment costs. The efficacy of the proposed model is demonstrated through its implementation on the benchmark IEEE 24-bus RTS system, with findings underscoring the pivotal role of hybrid power plants in enabling cost-effective and rapid sustainable energy integration. Full article

Mass market adoption of EVs is critical for decreasing greenhouse gas emissions and dependence on fossil fuels. However, this transition faces significant challenges, particularly the limited availability of public charging infrastructure. Expanding charging stations and renewable integrated EV parking lots can accelerate the adoption of EVs by enhancing charging accessibility and sustainability. This paper introduces an integrated optimization framework to determine the optimal siting of a Residential Parking Lot (RPL), a Commercial Parking Lot (CPL), and an Industrial Fast Charging Station (IFCS) within the IEEE 33-bus distribution system. In addition, the optimal sizing of rooftop solar photovoltaic (SPV) systems on the RPL and CPL is addressed to enhance energy sustainability and reduce grid dependency. The framework aims to minimize overall power losses while considering long-term technical, economic, and environmental impacts. To solve the formulated multi-dimensional optimization problem, Horse Herd Optimization (HHO) is used. Comparative analyses on IEEE-33 bus demonstrate that HHO outperforms well-known optimization algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO) in achieving lower energy losses. Case studies show that installing a 400-kW rooftop PV system can reduce daily energy expenditures by up to 51.60%, while coordinated vehicle scheduling further decreases energy purchasing costs by 4.68%. The results underscore the significant technical, economic, and environmental benefits of optimally integrating EV charging infrastructure with renewable energy systems, contributing to more sustainable and resilient urban energy networks. Full article

Photovoltaic (PV) energy conversion is expected to contribute to the creation of a clean energy society. For realizing such a vision, various developments such as high-efficiency, low-cost and highly reliable materials, solar cells, modules and systems are necessary. Cooperation with storage batteries is also very important for regulation and self-consumption. The creation of new applications such as building integrated PV, vehicle integrated PV, agriculture PV and floating PV is also very important for further installation of PV and reducing CO₂ emission. The sustainability of material consumption, along with reducing, reusing and recycling are also key issues for widespread deployment of PV. This paper provides an overview of the current status of photovoltaics and discusses future directions for photovoltaics from the view-points of high-efficiency, low-cost, reliability, and importance of integrated photovoltaics and sustainability. Full article

The increasing penetration of photovoltaic (PV) generation in power systems is progressively displacing traditional synchronous generators, leading to a significant reduction in the system’s equivalent inertia. This decline undermines the system’s ability to withstand rapid frequency variations, adversely affecting its dynamic stability. In this context, battery energy storage systems (BESS) have emerged as a viable alternative for providing synthetic inertia and enhancing the system’s response to frequency disturbances. This paper proposes the design and implementation of an adaptive fuzzy logic controller aimed at frequency regulation in PV-BESS systems. The controller uses frequency deviation (Δf), rate of change of frequency (ROCOF), and battery state of charge (SOC) as input variables, with the objective of improving the system’s response to frequency variations. The controller’s performance was evaluated through simulations conducted in the MATLAB environment, considering various operating conditions and disturbance scenarios. The results demonstrate that the proposed controller achieves the lowest maximum frequency deviation across all analyzed scenarios when the initial SOC is 50%, outperforming other comparative methods. Finally, compliance with primary frequency regulation (PFR) was verified in accordance with the Technical Procedure PR-21 related to spinning reserve, issued by the Peruvian Committee for Economic Operation of the System. Full article

The Dynamic Voltage Restorer (DVR), which is connected in series between the power grid and the load, can rapidly compensate for voltage disturbances to maintain stable voltage at the load end. To enhance the energy supply capacity of the DVR and utilize its shared circuit topology with photovoltaic (PV) inverters—which enables the dual functions of voltage compensation and PV-storage power generation—this study integrates PV and energy storage as a coordinated energy unit into the DVR, forming a PV-storage-integrated DVR system. The core innovation of this system lies in extending the voltage disturbance detection capability of the DVR to include harmonics. By incorporating a Butterworth filtering module and voltage fluctuation tracking technology, high-precision disturbance identification is achieved, thereby supporting power balance control and functional coordination. Furthermore, a multi-mode-power coordinated regulation method is proposed, enabling dynamic switching between operating modes based on PV output. Simulation and experimental results demonstrate that the proposed system and strategy enable smooth mode transitions. This approach not only ensures reliable voltage compensation for sensitive loads but also enhances the grid-support capability of PV systems, offering an innovative technical solution for the integration of renewable energy and power quality management. Full article

Integrating renewable energy with biomass valorization offers a scalable pathway toward circular and climate-resilient campus operations. This study presents a replicable model implemented at Alanya Alaaddin Keykubat University (ALKU, Türkiye), where post-consumer food waste from 30 cafeteria menus is converted into pet food and compost using a 150 L ECOAIR-150 thermal drying and grinding unit powered entirely by a 1.7 MW rooftop photovoltaic (PV) system. The PV infrastructure, established under Türkiye’s first public-sector Energy Performance Contract (EPC), ensures zero-electricity-cost operation. On average, 260 kg of organic waste are processed monthly, yielding 180 kg of pet food and 50 kg of compost, with an energy demand of 1.6 kWh h⁻¹ and a conversion efficiency of 68.4%, resulting in approximately 17.5 t CO₂ emissions avoided annually. Economic analysis indicates a monthly revenue of USD 55–65 and a payback period of ~36 months. Sensitivity analysis highlights the influence of input quality, seasonal waste composition, PV output variability, and operational continuity during academic breaks. Compared with similar initiatives in the literature, this model uniquely integrates EPC financing, renewable energy generation, and waste-to-product transformation within an academic setting, contributing directly to SDGs 7, 12, and 13. Full article