Search Results (2,898)

This study proposes a hierarchical two-layer control framework aimed at advancing the sustainability of renewable-integrated microgrids. The framework combines droop-based primary control, PI-based voltage and current regulation, and a supervisory Model Predictive Control (MPC) layer to enhance dynamic power sharing and system stability in renewable-integrated microgrids. The proposed method addresses the limitations of conventional control techniques by coordinating real and reactive power flow through an adaptive droop formulation and refining voltage/current regulation with inner-loop PI controllers. A discrete-time MPC algorithm is introduced to optimize power setpoints under future disturbance forecasts, accounting for state-of-charge limits, DC-link voltage constraints, and renewable generation variability. The effectiveness of the proposed strategy is demonstrated on a small hybrid microgrid system that serve a small community of buildings with a solar PV, wind generation, and a battery storage system under variable load and environmental profiles. Initial uncontrolled scenarios reveal significant imbalances in resource coordination and voltage deviation. Upon applying the proposed control, active and reactive power are equitably shared among DG units, while voltage and frequency remain tightly regulated, even during abrupt load transitions. The proposed control approach enhances renewable energy integration, leading to reduced reliance on fossil-fuel-based resources. This contributes to environmental sustainability by lowering greenhouse gas emissions and supporting the transition to a cleaner energy future. Simulation results confirm the superiority of the proposed control strategy in maintaining grid stability, minimizing overcharging/overdischarging of batteries, and ensuring waveform quality. Full article

Climate change has prompted the adoption of sustainable measures to reduce greenhouse gas (GHG) emissions, particularly in urban transportation. The integration of renewable energy sources, such as solar energy, offers a promising strategy to enhance sustainability in urban transit systems. This study assessed solar irradiation along the tram route in Cuenca—an Andean city characterized by distinctive topographic and climatic conditions—with the aim of evaluating the technical feasibility of integrating solar energy into the tram infrastructure. A descriptive, applicative, and longitudinal approach was adopted. Solar irradiation was monitored using a system composed of a fixed station and a mobile station, the latter installed on a tram vehicle. Readings carried out over fourteen months facilitated the analysis of seasonal and spatial variability of the available solar resource. The fixed station recorded average irradiation values ranging from 3.80 to 4.61 kWh/m²·day, while the mobile station reported values between 2.60 and 3.41 kWh/m²·day, revealing losses due to urban shading, with reductions ranging from 14.7% to 18.8% compared to fixed-site values. It was estimated that a fixed photovoltaic system of up to 1.068 MWp could be installed at the tram maintenance depot using 580 Wp panels, with the capacity to supply approximately 81% of the annual electricity demand of the tram system. Complementary solar installations at tram stops, stations, and other related infrastructure are also proposed. The results demonstrate the technical feasibility of integrating solar energy—through fixed and mobile systems—into the tram infrastructure of Cuenca. This approach provides a scalable model for energy planning in urban transport systems in Andean contexts or other regions with similar characteristics. Full article

Agrivoltaics (APV) mitigates land-use competition between photovoltaic installations and agricultural activities, thereby supporting multifaceted policy objectives in energy transition and sustainability. The availability of organic residuals from agrifood practices may also open the way to their energy valorization. This paper examines a small-scale farm in the Basilicata Region, southern Italy, to investigate the potential installation of an APV plant or a combined APV and bioenergy system to meet the electrical needs of the existing processing machinery. A dynamic numerical analysis is performed over an annual cycle to properly size the storage system under three distinct APV configurations. The panel shadowing effects on the underlying crops are quantified by evaluating the reduction in incident solar irradiance during daylight and the consequent agricultural yield differentials over the life period of each crop. The integration of APV and a biomass-powered cogenerator is then considered to explore the possible off-grid farm operation. In the sole APV case, the single-axis tracking configuration achieves the highest performance, with 45.83% self-consumption, a land equivalent ratio (LER) of 1.7, and a payback period of 2.77 years. For APV and bioenergy, integration with a 20 kW cogeneration unit achieves over 99% grid independence by utilizing a 97.57 kWh storage system. The CO₂ emission reduction is 49.6% for APV alone and 100% with biomass integration. Full article

The increasing deployment of stand-alone photovoltaic (PV) power supply systems is driven by their capability to convert solar irradiance into electrical energy. A typical application of such systems is solar-powered water pumping. However, since solar irradiance varies throughout the day, the maximum power output of PV panels may be lower than the load demand. A viable solution to this issue is the integration of hybrid energy storage systems (HESSs) combining batteries and supercapacitors (SCs). In this work, HESS charging and discharging control strategies were developed based on adaptive droop control, which regulates the power distribution between the SC and the battery and limits DC grid voltage deviations. In the developed method, the SC droop coefficient is adaptively adjusted in a stepwise manner depending on the SC state of charge (SoC), while the battery droop coefficient remains constant. The performance of the proposed strategies was evaluated through simulations, showing SC-battery internal loss minimization by up to 50% compared with the scenario without droop control when the SC is discharged first, and only then is the battery engaged. Step response of the converter was investigated experimentally, showing less than a 2 ms response time, and no undesired influence from the proposed control method was detected. Full article

Vacuum membrane distillation (VMD) is a promising desalination technology, which is likely to be integrated with solar energy, and offers a sustainable solution to freshwater scarcity. However, its industrial application remains limited due to high specific energy consumption and water production costs. The key to improving VMD performance lies in enhancing the recovery of the latent heat of condensation. In this investigation, four different configurations are proposed; each differs in the method of condensation and energy recovery. The first is applied by using a basic condenser, preheating seawater with latent heat from vapor. The second is implemented by incorporating a liquid ring vacuum pump (LRVP), enabling both condensation and vacuum generation. The third is performed by coupling VMD with a heat pump, which operates by using a refrigerant fluid. Lastly, the fourth is employed by using mechanical vapor compression (MVC), where the vapor is compressed to recover heat efficiently. The results show that the VMD-MVC is the most efficient configuration, offering the lowest specific energy consumption (154.6 kWh/m³), the highest energy recovery rate (54.64%), the highest gained output ratio (GOR) of 5.52, and the lowest water production cost (4.6 USD/m³). In contrast, the VMD system coupled with a heat pump presented the highest water production cost (36.4 USD/m³) among all the evaluated configurations. Full article

Sudan’s rural regions face acute challenges in energy access, exacerbated by ongoing conflict that has destroyed major power infrastructure and crippled conventional electricity generation. This study investigates the technical and economic feasibility of photovoltaic (PV) solar systems as a sustainable alternative for powering off-grid rural communities. Using MATLAB simulations (Version 24b), Global Solar Atlas data, and HOMER software (Version 4.11) for hybrid system optimization, a case study of a village in Shariq al-Nil, Khartoum, demonstrates the viability of solar energy to meet residential, medical, and agricultural needs. Beyond technical analysis, this paper highlights the transformative role of solar energy in post-conflict reconstruction, with potential applications in powering irrigation systems and supporting agricultural livelihoods. It also emphasizes the importance of integrating community-centered policy frameworks to ensure equitable access, long-term adoption, and sustainable development outcomes. The findings advocate for policies that support renewable energy investment as a cornerstone of rebuilding efforts in Sudan and similar contexts affected by conflict and infrastructure collapse. Full article

Remote First Nations communities in Australia experience ongoing energy insecurity due to geographic isolation, reliance on diesel, and uneven consumer protections relative to grid-connected households. This paper analyses evidence on electricity access, infrastructure and practical experience along with initiatives for improving existing infrastructure; highlights government policies, funding frameworks and regulation; demonstrates the benefits of community-led projects; provides geographic and demographic insights; and relevels key challenges along with pathways for effective solutions. Drawing on existing program experience, case studies and recent reforms (including First Nations–focused strategies and off-grid consumer-protection initiatives), this paper demonstrates that community energy systems featuring solar-battery systems can significantly improve reliability and affordability by reducing reliance on diesel generators and delivering tangible household benefits. The analyses reveal that there is an ongoing gap in protecting off-grid consumers. Hence, this work proposes a practical agenda to improve electricity supply systems for First Nations community energy systems through advanced community microgrids (including long-duration storage), intelligent energy management and monitoring systems, rights-aligned consumer mechanisms for customers with prepaid metering systems, fit-for-purpose regulation, innovative blended finance (e.g., Energy-as-a-Service and impact investment) and on-country workforce development. Overall, this paper contributes to a perspective for an integrated framework that couples technical performance with equity, cultural authority and energy sovereignty, offering a replicable pathway for reliable, affordable and clean electricity for remote First Nations communities. Full article

This study aims to establish an energy assessment system and provide low-carbon design strategies for block-scale science and technology industrial parks in the Yangtze River Delta region of China. To investigate low-carbon design strategies for these parks, the impact of solar energy utilization potential and heat island effect on the energy consumption of buildings is taken as the entry point. Through an analysis of the spatial characteristics of twenty block-scale science and technology industrial parks in the Yangtze River Delta region of China, two types of idealized park models comprising a total of eighteen variations were established. The simulation process involved six key morphological parameters to describe the specific shape of the parks quantitatively. The Ladybug Tools 1.6.0, Radiance 5.4a, and URBANopt v0.9.2 software were used to simulate the potential for photovoltaic power generation and the energy consumption of the parks. Net Energy Use Intensity (NEUI) and Potential Utilization Ratio of Renewable Energy (PURRE) were selected as the final evaluation indexes to represent the integrated energy performance of the park. The results show that for the park with a circular layout, the optimal integrated energy performance is achieved when the building density is between 35% and 40%; the average building height is designed with lower values within the range of 20 m to 24 m, and the height-to-depth ratio is around 0.3. Finally, based on the results of the analysis, four major low-carbon design strategies were proposed: high-density development, courtyard layout, supporting-function centralized layout, and carbon sink enhancement. Full article

China possesses abundant solar energy resources and remains heavily dependent on agriculture. The integration of photovoltaic (PV) power generation with agricultural production has emerged as a strategic pathway to advance China’s ecological transition and dual carbon goals. By 2023, PV power generation represented 21% of the nation’s total installed capacity. The cumulative capacity was projected to reach approximately 887 GW by 2024. The novelty of this study lies in offering a systematic and integrative review of PV agriculture in China. This paper used a combination of field research, case studies, policy analysis, and a comparative evaluation of diverse “PV+” development models. The findings reveal a pronounced spatial imbalance. Western China possesses 42% of the country’s solar energy resources, whereas the eastern provinces of Jiangsu, Zhejiang, and Anhui collectively comprise 37.8% of all PV agricultural projects. Three dominant “PV+” models are identified and categorized as follows: “PV + ecological restoration”, “PV + agriculture, forestry, animal husbandry, and fisheries,” and “PV + facility agriculture.” These models provide multiple benefits. They enhance land use efficiency, stimulate local economic development, and contribute to food security by expanding the supply of essential agricultural products. Based on these insights, the study highlights future priorities in technological innovation, ecological evaluation, intelligent equipment, digitalization, and region-specific policy support. Overall, this research fills a key gap in systematically and comprehensively describing the current development status of photovoltaic agriculture in China. It also offers transferable lessons for sustainable agriculture and global energy transitions. Full article

This paper presents a broadband omnidirectional rectenna combined with a solar cell for hybrid energy harvesting, addressing the daytime-only limitation of solar cells via complementary RF energy harvesting. To avoid mutual interaction in integration, the solar cell is placed above the antenna to receive light/EM waves from different directions. A broadband discone antenna ensures omnidirectional RF reception from 1.56 to 6.63 GHz, while a single-stub matching circuit and voltage doubler enable rectifier operation from 1.4 to 3.6 GHz, with over 50% power conversion efficiency at 5 dBm. The measurement demonstrates that the hybrid system can yield 20.25 mW from combined RF/solar power. This broadband hybrid energy harvesting system shows potential for powering sensors throughout the day by integrating two complementary energy sources with minimal interaction. Full article

Snow accumulation on photovoltaic (PV) panels can cause significant energy losses in cold climates. While drone-based monitoring offers a scalable solution, real-world challenges like varying illumination can hinder accurate snow detection. We previously developed a YOLO-based drone system for snow coverage detection using a Fixed Thresholding segmentation method to discriminate snow from the solar panel; however, it struggled in challenging lighting conditions. This work addresses those limitations by presenting a reliable drone-based system to accurately estimate the Snow Coverage Percentage (SCP) over PV panels. The system combines a lightweight YOLOv11n-seg deep learning model for panel detection with an adaptive image processing algorithm for snow segmentation. We benchmarked several segmentation models, including MASK R-CNN and the state-of-the-art SAM2 segmentation model. YOLOv11n-seg was selected for its optimal balance of speed and accuracy, achieving 0.99 precision and 0.80 recall. To overcome the unreliability of static thresholding under changing lighting, various dynamic methods were evaluated. Otsu’s algorithm proved most effective, reducing the absolute error of the mean in SCP estimation to just 1.1%, a significant improvement over the 13.78% error from the previous fixed-thresholding approach. The integrated system was successfully validated for real-time performance on live drone video streams, demonstrating a highly accurate and scalable solution for autonomous snow monitoring on PV systems. Full article

This study presents the development and validation of a high-efficiency optical interface designed for ultra-high-concentration photovoltaic (UHCPV) systems, with a focus on enabling clean and sustainable solar energy conversion. A Fresnel lens serves as the primary optical concentrator in a novel system architecture that integrates advanced optical design with system-level thermal management. The proposed modeling framework combines detailed 3D ray tracing with coupled thermal simulations to accurately predict key performance metrics, including optical concentration ratios, thermal loads, and component temperature distributions. Validation against theoretical and experimental benchmarks demonstrates high predictive accuracies within 1% for optical efficiency and 2.18% for thermal performance. The results identify critical thermal thresholds for long-term operational stability, such as limiting mirror temperatures to below 52 °C and photovoltaic cell temperatures to below 130 °C. The model achieves up to 89.08% optical efficiency, with concentration ratios ranging from 240 to 600 suns and corresponding focal spot temperatures between 37.2 °C and 61.7 °C. Experimental benchmarking confirmed reliable performance, with the measured results closely matching the simulations. These findings highlight the originality of the coupled optical–thermal approach and its applicability to concentrated photovoltaic design and deployment. This integrated design and analysis approach supports the development of scalable, clean photovoltaic technologies and provides actionable insights for real-world deployment of UHCPV systems with minimal environmental impact. Full article

Perovskites (ABX₃) exhibit remarkable potential in optoelectronic conversion, catalysis, and diverse energy-related fields. However, the tunability of A, B, and X-site compositions renders conventional screening methods labor-intensive and inefficient. This review systematically synthesizes the roles of physical simulations and machine learning (ML) in accelerating perovskite discovery. By harnessing existing experimental datasets and high-throughput computational results, ML models elucidate structure-property relationships and predict performance metrics for solar cells, (photo)electrocatalysts, oxygen carriers, and energy-storage materials, with experimental validation confirming their predictive reliability. While data scarcity and heterogeneity inherently limit ML-based prediction of material property, integrating high-throughput computational methods as external mechanistic constraints—supplementing standardized, large-scale training data and imposing loss penalties—can improve accuracy and efficiency in bandgap prediction and defect engineering. Moreover, although embedding high-throughput simulations into ML architectures remains nascent, physics-embedded approaches (e.g., symmetry-aware networks) show increasing promise for enhancing physical consistency. This dual-driven paradigm, integrating data and physics, provides a versatile framework for perovskite design, achieving both high predictive accuracy and interpretability—key milestones toward a rational design strategy for functional materials discovery. Full article

Adverse climate events have recently highlighted an increasing need to deploy sustainable energetic infrastructures. The existing electric conversion circuits for solar energy provide high efficiency; however, gaps in sustainability and robustness can be identified by considering their operation during intense perturbations, potentially occurring for interplanetary energy transfer. Additionally, charging characteristics for energy storage units influence differently the operation life of battery arrays, with increased stability providing favorable operating conditions. Therefore, the present study develops an alternative controller for managing solar energy as well as a prototype for tracking the maximum power point, both constrained by robustness and renewability studies. For the presented design, stability analyses and simulations validated the management of electric energy from solar panels and the developed configuration resulted in improving current peak integral transient characteristics by using an alternative control method, demonstrating stability for an indefinite number of energy storage units. Furthermore, the estimation for VLSI (Very-Large-Scale Integration) of this constrained design has been concluded to potentially provide a solution with adequate performance, comparable to state-of-the-art computational circuits. However, certain limitations could arise when substituting the main computation parts with analyzed solutions and proceeding with integration-based manufacturing. Full article

This research offers valuable improvements in the efficiency and water yield of a parabolic dish concentrator (PDC) solar distillation system, contributing to more sustainable and effective renewable energy solutions. Three hybrid nanofluids were evaluated, and their performance was measured through experiments and simulations. The numerical model is within 5% agreement with the measurements. Daily distilled water production increases by 25.7% with hybrid nanofluids (from 4.50 L to 5.67 L). The average exergy efficiency is approximately 19%. Furthermore, an interpretable, rule-based AI controller optimized with the Coati algorithm was integrated; this controller suggested operating setpoints and revealed transparent decision thresholds. This work is the first systematic PDC study where three different hybrid nanofluids were examined and explainable artificial intelligence (XAI) was applied within a single framework. The results demonstrate that higher performance and more predictable operation are achievable for producing distilled water based on PDC. Full article