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Against the backdrop of an urgent energy crisis, solar energy has attracted sufficient attention as one of the most inexhaustible and friendly types of environmental energy. Faced with long service and harsh environment, the poor performance ratios of photovoltaic arrays and safety hazards are frequently boosted worldwide. In particular, the hot spot effect plays a vital role in weakening the power generation performance and reduces the lifetime of photovoltaic (PV) modules. Here, our research reports a spatial–temporal hot spot management system integrated with fiber Bragg grating (FBG) temperature sensor arrays and cooling hydrogels. Through finite element simulations and indoor experiments in laboratory conditions, a superior cooling effect of hydrogels and photoelectric conversion efficiency improvement have been demonstrated. On this basis, field tests were carried out in which the FBG arrays detected the surface temperature of the PV module first, and then a classifier based on an optimized artificial neural network (ANN) recognized hot spots with an accuracy of 99.1%. The implementation of cooling hydrogels as a feedback mechanism achieved a 7.7 °C reduction in temperature, resulting in a 5.6% enhancement in power generation efficiency. The proposed strategy offers valuable insights for conducting predictive maintenance of PV power plants in the case of hot spots. Full article

In recent years, solar energy has emerged as one of the most advanced renewable energy sources, with its production capacity steadily growing. To maximize output and efficiency, choosing the right configuration for a specific location for these installations is crucial. This study uniquely integrates detailed multi-variant fixed-tilt PV system simulations with comprehensive economic evaluation under temperate climate conditions, addressing site-specific spatial constraints and grid integration considerations that have rarely been combined in previous works. In this paper, an energy and economic efficiency analysis for a photovoltaic power plant, located in central Poland, designed in eight variants (10°, 15°, 20°, 25°, 30° PV module inclination angle for a south orientation and 10°, 20°, 30° for an east–west orientation) for a limited building area of approximately 300,000 m² was conducted. In PVSyst computer simulations, PVGIS-SARAH2 solar radiation data were used together with the most common data for describing the Polish local solar climate, called Typical Meteorological Year data (TMY). The most energy-efficient variants were found to be 20° S and 30° S, configurations with the highest surface production coefficient (249.49 and 272.68 kWh/m²) and unit production efficiency values (1123 and 1132 kWh/kW, respectively). These findings highlight potential efficiency gains of up to approximately 9% in surface production coefficient and financial returns exceeding 450% ROI, demonstrating significant economic benefits. In economic terms, the 15° S variant achieved the highest values of financial parameters, such as the return on investment (ROI) (453.2%), the value of the average annual share of profits in total revenues (56.93%), the shortest expected payback period (8.7 years), the value of the levelized cost of energy production (LCOE) (0.1 EUR/kWh), and one of the lowest costs of building 1 MWp of a photovoltaic farm (664,272.7 EUR/MWp). Among the tested variants of photovoltaic farms with an east–west geographical orientation, the most advantageous choice is the 10° EW arrangement. The results provide valuable insights for policymakers and investors aiming to optimize photovoltaic deployment in temperate climates, supporting the broader transition to renewable energy and alignment with national energy policy goals. Full article

Floating solar technology has gained significant attention as part of the global expansion of renewable energy due to its potential for installation in underutilized water bodies. Several countries, including the Netherlands, have initiated efforts to extend this technology from inland freshwater applications to open offshore environments, particularly within offshore wind farm areas. This development is motivated by the synergistic benefits of increasing site energy density and leveraging the existing offshore grid infrastructure. The deployment of offshore floating photovoltaic (OFPV) systems involves assembling multiple modular units in a marine environment, introducing operational risks that may give rise to safety concerns. To mitigate these risks, weather windows must be considered prior to the task execution to ensure continuity between weather-sensitive activities, which can also lead to additional time delays and increased costs. Consequently, optimizing marine logistics becomes crucial to achieving the cost reductions necessary for making OFPV technology economically viable. This study employs a simulation-based approach to estimate the installation duration of a 5 MWp OFPV plant at a Dutch offshore wind farm site, started in different months and under three distinct risk management scenarios. Based on 20 years of hindcast wave data, the results reveal the impacts of campaign start months and risk management policies on installation duration. Across all the scenarios, the installation duration during the autumn and winter period is 160% longer than the one in the spring and summer period. The average installation durations, based on results from 12 campaign start months, are 70, 80, and 130 days for the three risk management policies analyzed. The result variation highlights the additional time required to mitigate operational risks arising from potential discontinuity between highly interdependent tasks (e.g., offshore platform assembly and mooring). Additionally, it is found that the weather-induced delays are mainly associated with the campaigns of pre-laying anchors and platform and mooring line installation compared with the other campaigns. In conclusion, this study presents a logistics modeling methodology for OFPV systems, demonstrated through a representative case study based on a state-of-the-art truss-type design. The primary contribution lies in providing a framework to quantify the performance of OFPV installation strategies at an early design stage. The findings of this case study further highlight that marine installation logistics are highly sensitive to local marine conditions and the chosen installation strategy, and should be integrated early in the OFPV design process to help reduce the levelized cost of electricity. Full article

Sources of renewable energy have attracted considerable attention. Their expanded use will have a substantial impact on both the cost of energy production and climate change. Solar energy is one efficient and safe option; however, solar energy harvesting sites, irrespective of the location, can impact the ecosystem. This experimental study explores the energy available inside and outside of novel miniature energy harvesting cages by measuring light intensity and power generated. Varying light intensity outside the cage has been utilized to study the remaining energy inside the cage of a flexible design, where the heights of the harvesting panels are parameters. Cages are built from custom photovoltaic panels arranged in a staircase manner to provide access to growing plants. The balance between power generation and biological development is investigated. Two different structures are presented to explore the variation of illumination intensity inside the cages. The experimental results show a substantial reduction in energy inside the cages. The experimental results showed up to 24% reduction in illumination inside the cages in winter. The reduction is even larger in summer, up to 57%. The results from the models provide a framework to study the possible impact on a biological system residing inside the cages, paving the way for practical farming with sustainable energy harvesting. Full article

This work proposes a new method to refill fuel cell electric vehicle hydrogen tanks from a storage system in hydrogen refueling stations. The new method uses the storage tanks in cascade to supply hydrogen to the refueling station dispensers. This method reduces the hydrogen compressor power requirement and the energy consumption for refilling the vehicle tank; therefore, the proposed alternative design for hydrogen refueling stations is feasible and compatible with low-intensity renewable energy sources like solar photovoltaic, wind farms, or micro-hydro plants. Additionally, the cascade method supplies higher pressure to the dispenser throughout the day, thus reducing the refueling time for specific vehicle driving ranges. The simulation shows that the energy saving using the cascade method achieves 9% to 45%, depending on the vehicle attendance. The hydrogen refueling station design supports a daily vehicle attendance of 9 to 36 with a complete refueling process coverage. The carried-out simulation proves that the vehicle tank achieves the maximum attainable pressure of 700 bars with a storage system of six tanks. The data analysis shows that the daily hourly hydrogen demand follows a sinusoidal function, providing a practical tool to predict the hydrogen demand for any vehicle attendance, allowing the planners and station designers to resize the elements to fulfill the new requirements. The proposed system is also applicable to hydrogen ICE vehicles. Full article

Under the dual-carbon goals, with the rapid increase in the proportion of fluctuating power sources such as wind and solar energy, the regulatory capacity of traditional thermal power generation can no longer meet the demand for intra-day fluctuations. There is an urgent need to tap into the potential of flexible load-side regulatory resources. To this end, this paper proposes a low-carbon economic optimal dispatching strategy for virtual power plants (VPPs), considering the aggregation of diverse flexible and adjustable resources with the integration of wind and solar power. Firstly, the method establishes mathematical models by analyzing the dynamic response characteristics and flexibility regulation boundaries of adjustable resources such as photovoltaic (PV) systems, wind power, energy storage, charging piles, interruptible loads, and air conditioners. Subsequently, considering the aforementioned diverse adjustable resources and aggregating them into a VPP, a low-carbon economic optimal dispatching model for the VPP is constructed with the objective of minimizing the total system operating costs and carbon costs. To address the issue of slow convergence rates in solving high-dimensional state variable optimization problems with the traditional plant growth simulation algorithm, this paper proposes an improved plant growth simulation algorithm through elite selection strategies for growth points and multi-base point parallel optimization strategies. The improved algorithm is then utilized to solve the proposed low-carbon economic optimal dispatching model for the VPP, aggregating diverse adjustable resources. Simulations conducted on an actual VPP platform demonstrate that the proposed method can effectively coordinate diverse load-side adjustable resources and achieve economically low-carbon dispatching, providing theoretical support for the optimal aggregation of diverse flexible resources in new power systems. Full article

The transition towards a power system characterized by a reduced presence of synchronous generators (SGs) and an increased reliance on inverter-based resources (IBRs), including wind, solar photovoltaics (PV), and battery storage, presents new operational challenges, particularly when these sources exceed 50–60% of the system’s demand. While current grid-following (GFL) IBRs, which are equipped with fast and rigid control systems, continue to dominate the inverter landscape, there has been a notable surge in research focused on grid-forming (GFM) inverters in recent years. This study conducts a comparative analysis of the practicality and control methodologies of GFM inverters relative to traditional GFL inverters from a system planning perspective. A comprehensive framework aimed at assisting system developers and consulting engineers in the grid-integration of wide-scale renewable energy sources (RESs), incorporating strategies for the deployment of inverters, capacitor banks, and harmonic filters, is proposed in this paper. The discussion includes an examination of the reactive power capabilities of the plant’s inverters and the provision of additional reactive power to ensure compliance with grid interconnection standards. Furthermore, the paper outlines a practical approach to assess the necessity for enhanced filtering measures to mitigate potential resonant conditions and achieve harmonic compliance at the installation site. The objective of this work is to offer useful guidelines and insights for the effective addition of RES into contemporary power systems. Full article

With the large-scale global deployment of photovoltaics (PV), traditional monitoring technologies face challenges such as wiring difficulties, high energy consumption, and high maintenance costs in remote or complex terrains, which limit long-term environmental sensing. Therefore, energy-harvesting systems are crucial for the intelligent operation of photovoltaic systems; however, their deployment depends on the accurate mapping of wind energy fields and solar irradiance fields. This study proposes a multi-scale simulation method based on computational fluid dynamics (CFD) to optimize the placement of energy-harvesting systems in photovoltaic power plants. By integrating wind and irradiance distribution analysis, the spatial characteristics of airflow and solar radiation are mapped to identify high-efficiency zones for energy harvesting. The results indicate that the top of the photovoltaic panel exhibits a higher wind speed and reflected irradiance, providing the optimal location for an energy-harvesting system. The proposed layout strategy improves overall energy capture efficiency, enhances sensor deployment effectiveness, and supports intelligent, maintenance-free monitoring systems. This research not only provides theoretical guidance for the design of energy-harvesting systems in PV stations but also offers a scalable method applicable to various geographic scenarios, contributing to the advancement of smart and self-powered energy systems. Full article

Forecasting future solar power plant production is essential to continue the development of photovoltaic energy and increase its share in the energy mix for a more sustainable future. Accurate solar radiation forecasting greatly improves the balance maintenance between energy supply and demand and grid management performance. This study assesses the influence of input selection on short-term global horizontal irradiance (GHI) forecasting across two contrasting Algerian climates: arid Ghardaïa and coastal Algiers. Eight feature selection methods (Pearson, Spearman, Mutual Information (MI), LASSO, SHAP (GB and RF), and RFE (GB and RF)) are evaluated using a Gradient Boosting model over horizons from one to six hours ahead. Input relevance depends on both the location and forecast horizon. At t+1, MI achieves the best results in Ghardaïa (nMAE = 6.44%), while LASSO performs best in Algiers (nMAE = 10.82%). At t+6, SHAP- and RFE-based methods yield the lowest errors in Ghardaïa (nMAE = 17.17%), and RFE-GB leads in Algiers (nMAE = 28.13%). Although performance gaps between methods remain moderate, relative improvements reach up to 30.28% in Ghardaïa and 12.86% in Algiers. These findings confirm that feature selection significantly enhances accuracy (especially at extended horizons) and suggest that simpler methods such as MI or LASSO can remain effective, depending on the climate context and forecast horizon. Full article

To alleviate the impact of economic and environmental detriments caused by the increased demands of electric vehicle battery production and disposal, the use of spent batteries in second-life stationary applications such as energy storage for renewable sources or backup power systems, offers many benefits. This paper focuses on reducing the energy consumption cost and greenhouse gas emissions of Internet-of-Things-enabled campus microgrids by installing solar photovoltaic panels on rooftops alongside energy storage systems that leverage second-life batteries, a gas-fired campus power plant, and a wind turbine while considering the potential loads of a prosumer microgrid. A linear optimization problem is derived from the system by scheduling energy exchanges with the Ontario grid through net metering and solved by using Python 3.11. The aim of this work is to support Sustainable Development Goals, namely 7 (Affordable and Clean Energy), 11 (Sustainable Cities and Communities), 12 (Responsible Consumption and Production), and 13 (Climate Action). A comparison between a base case scenario and the results achieved with the proposed scenarios shows a significant reduction in electricity cost and greenhouse gas emissions and an increase in self-consumption rate and renewable fraction. This research work provides valuable insights and guidelines to policymakers. Full article

With the development of alternative energy technologies, energy production from renewable sources is gaining wide application. One of the types of renewable energy sources is solar power. In the past 5 years, solar cells have become very popular for both private electricity microgeneration and large power plants. There are two main options for installing solar photovoltaic panels: on the roof of a house or the ground; on specially made frames. When installing solar cells on the roof, it is not always possible to choose a tilt angle that is appropriate for all seasons, since the angle is mainly adjusted to the plane of the roof. When installing solar cells on the ground, it is usually possible to choose both the orientation relative to the cardinal points and the tilt angle relative to the ground. There are various theories about the best tilt angle of solar cells for producing the most amount of energy during the year. Therefore, the aim of the present research study is to develop an original research methodology for determining an optimal tilt angle for solar cells. The research study examined six different tilt angles of solar cells, 0°, 30°, 35° 40° 45° and 50°, orienting the cells towards the south. The research study used 18 identical monocrystalline solar panels with a power of 20 W. Three solar panels were set at each angle. This way, the experiment had three replications at each angle of the solar cells. The measurements were recorded by a GWL840 data logger with an interval of 10 s. The experiment was conducted by placing all solar cell modules on the roof of the building at Lat. 56.66181° and Long. 23.75238°. During the experimental period, the highest efficiency was found for the solar panels set at 50° and 40°, reaching the total solar irradiation of 266.61 Wm⁻² and 266.27 Wm⁻², respectively. Full article

Multi-criteria Decision Making (MCDM) presents a novel approach towards truly holistic green sustainability, particularly within the context of chemical process plants (CPPs). ASPEN Plus v12.0 was utilised for two representative CPP cases: isopropanol (IPA) production via isopropyl acetate, and green ammonia (NH₃) production. An integrated Fuzzy Analytic Hierarchy Process (FAHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was modelled in MATLAB v24.1 to prioritise the holistically green and sustainable pathways. Life cycle assessments (LCAs) were employed to select the pathways, and the most suitable sub-criteria per the four criteria are as follows: social, economic, environmental, and technical. In descending order of optimality, the pathways were ranked as follows for green NH₃ and IPA, respectively: Hydropower (HPEA) > Wind Turbine (WGEA) > Biomass Gasification (BGEA)/Solar Photovoltaic (PVEA) > Nuclear High Temperature (NTEA), and Propylene Indirect Hydration (IAH) > Direct Propylene Hydration (PH) > Acetone Hydrogenation (AH). Sensitivity analysis evaluated the FAHP–TOPSIS framework to be overall robust. However, there are potential uncertainties within and/or among sub-criteria, particularly in the social dimension, due to software and data limitations. Future research would seek to integrate FAHP with VIKOR and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE-II). Full article

This study focuses on the challenge of short-term economic dispatch in hybrid generation systems, specifically under scenarios where energy constraints arise due to reduced water availability. The primary aim is to compare various generation scenarios to evaluate the influence of renewable energy-based power plants on the overall operating cost of an Electric Power System. The hybrid generation system under analysis comprises hydroelectric, thermoelectric, photovoltaic solar, and wind power plants. The latter two, in particular, play a crucial role, yet their performance is highly dependent on the variability of their primary resources—solar radiation, wind speed, and ambient temperature—which are inherently stochastic. To estimate their behavior, the Monte Carlo method is applied, utilizing probability distribution functions to predict resource availability throughout the planning horizon. Once the scenarios are established, the problem is formulated as a hydrothermal dispatch optimization, which is then tackled using heuristic and metaheuristic approaches, with a strong focus on the Differential Evolution algorithm. Full article

Enhancing solar photovoltaic (PV) power generation is fundamental to achieving energy sustainability goals. However, elevated module temperatures can diminish photoelectric conversion efficiency and output power, impacting the safe and efficient operation of PV modules. Therefore, understanding module temperature distribution is crucial for predicting power generation performance and optimizing cleaning schedules in PV power plants. To investigate the combined effects of multiple factors on the temperature distribution and output power of dusty PV modules, a heat transfer model was developed. Validation against experimental data and comparisons with the NOCT model demonstrated the validity and advantages of the proposed model in accurately predicting PV module behavior. This validated model was then employed to simulate and analyze the influence of various parameters on the temperature of dusty modules and to evaluate the module output power, providing insights into sustainable PV energy generation. Results indicate that the attenuation of PV glass transmittance due to dust accumulation constitutes the primary determinant of the lower temperature observed in dusty modules compared to clean modules. This highlights a significant factor impacting long-term performance and resource utilization efficiency. Dusty module temperature exhibits a positive correlation with irradiance and ambient temperature, while displaying a negative correlation with wind speed and dust accumulation. Notably, alignment of wind direction and module orientation enhances module heat dissipation, representing a passive cooling strategy that promotes efficient and sustainable operation. At an ambient temperature of 25 °C and a wind speed of 3 m/s, the dusty module exhibits a temperature reduction of approximately 11.0% compared to the clean module. Furthermore, increasing the irradiance from 200 W/m² to 800 W/m² results in an increase in output power attenuation from 51.4 W to 192.6 W (approximately 30.4% attenuation rate) for a PV module with a dust accumulation of 25 g/m². This underscores the imperative for effective dust mitigation strategies to ensure long-term viability, economic sustainability, and optimized energy yields from solar energy investments. Full article

The growing global demand for sustainable energy solutions has spurred interest in hybrid renewable energy systems, particularly those combining photovoltaic (PV) solar and wind power. This study records the technical and financial feasibility of establishing hybrid solar photovoltaic and wind power stations in Iraq, Al-Rutbah and Al-Nasiriya, with a total power of 60 MW for each, focusing on optimizing energy output and cost-efficiency. The analysis evaluates key technical factors, such as resource availability, system design, and integration challenges, alongside financial considerations, including capital costs, operational expenses, and return on investment (ROI). Using the RETScreen program, the research explores potential locations and configurations for maximizing energy production and minimizing costs, and the evaluation is performed through the calculation Internal Rate of Return (IRR) on equity (%), the Simple Payback (year), the Net Present Value (NPV), and the Annual Life Cycle Savings (ALCSs). The results show that both PV and wind technologies demonstrate significant energy export potential, with PV plants exporting slightly more electricity than their wind counterparts. Al Nasiriya Wind had the highest output, indicating favorable wind conditions or better system performance at that site. The results show that the analysis of the proposed hybrid system has a standardizing effect on emissions, reducing variability and environmental impact regardless of location. The results demonstrate that solar PV is significantly more financially favorable in terms of capital recovery time at both sites, and that financial incentives, especially grants, are essential to improve project attractiveness, particularly for wind power. The analysis underscores the superior financial viability of solar PV projects in both regions. It highlights the critical role of financial support, particularly capital grants, in turning renewable energy investments into economically attractive opportunities. Full article