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Search Results (1,346)

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Keywords = PV economics

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23 pages, 4261 KiB  
Article
Characterisation of Harmonic Resonance Phenomenon of Multi-Parallel PV Inverter Systems: Modelling and Analysis
by Kasun Peiris, Sean Elphick, Jason David and Duane Robinson
Energies 2025, 18(2), 443; https://doi.org/10.3390/en18020443 - 20 Jan 2025
Abstract
Solar PV inverters require output filters to reduce unwanted harmonics in their output, where LCL filters are a more economical choice than larger inductance-only filters. A drawback of these filters is that they can introduce power quality disturbances, especially at higher frequencies (above [...] Read more.
Solar PV inverters require output filters to reduce unwanted harmonics in their output, where LCL filters are a more economical choice than larger inductance-only filters. A drawback of these filters is that they can introduce power quality disturbances, especially at higher frequencies (above 2 kHz). This paper investigates and characterises the resonance phenomenon introduced by different filter types, i.e., LC or LCL, and identifies their behavioural change when combined with multiple parallel grid-tied PV inverter systems. MATLAB/Simulink modelling aspects of PV inverter systems related to resonance phenomenon are presented, including establishing resonance at a specific frequency where potentially large variations in the parameter selection across manufacturers may exist. In addition, a method is developed to establish output filter frequency response through measurements, which is used to develop validated solar PV harmonic models for high-frequency analysis. The low-frequency harmonic models can be used up to the resonant frequency where the current flowing through the filter capacitor is insignificant compared to the current flowing into the electricity network. Full article
(This article belongs to the Special Issue Power Quality and Hosting Capacity in the Microgrids)
17 pages, 6525 KiB  
Article
Impact Assessment of Grid-Connected Solar Photovoltaic Systems on Power Distribution Grid: A Case Study on a Highly Loaded Feeder in Ulaanbaatar Ger District
by Turmandakh Bat-Orgil, Battuvshin Bayarkhuu, Bayasgalan Dugarjav and Insu Paek
Energies 2025, 18(2), 440; https://doi.org/10.3390/en18020440 - 20 Jan 2025
Abstract
Adopting and widely implementing solar photovoltaic (PV) systems are regarded as a promising solution to address energy crises by providing a sustainable and independent electricity supply while significantly reducing greenhouse gas emissions to combat climate change. This encourages households, organizations, and enterprises to [...] Read more.
Adopting and widely implementing solar photovoltaic (PV) systems are regarded as a promising solution to address energy crises by providing a sustainable and independent electricity supply while significantly reducing greenhouse gas emissions to combat climate change. This encourages households, organizations, and enterprises to install solar PV systems. However, there are many solar PV systems that have been connected to the power distribution grid without following the required procedures. Power distribution grid operators cannot detect the locations of these solar PV systems. Thus, it is necessary to assess the impact of solar PV systems on the power distribution grid in detail, even though there are multiple economic and environmental advantages associated with installing solar PV systems. This study analyzes the changes in an overloaded power distribution grid’s power losses and voltage deviations with solar PV systems. There are two main factors considered for assessing the impact of the solar PV system on the power distribution grid: the total installed capacity of the solar PV systems and the location of the connection. Based on a comparison between the measurement results of three feeders with higher loads in the Ulaanbaatar area, the Dambadarjaa feeder, which has the highest load, was selected. The impact of the solar PV systems on the selected feeder was analyzed by connecting eight solar PV systems at four different locations. Their total installed capacities vary between 25 and 80 percent of the highest daily load of the selected feeder. The results show that the power loss of the feeder can be greatly reduced when the total installed capacity of the solar PV systems is selected optimally, and the location of the connection is at the end of the power distribution grid. Full article
(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)
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20 pages, 3595 KiB  
Article
Integration of a Heterogeneous Battery Energy Storage System into the Puducherry Smart Grid with Time-Varying Loads
by M A Sasi Bhushan, M. Sudhakaran, Sattianadan Dasarathan and Mariappane E
Energies 2025, 18(2), 428; https://doi.org/10.3390/en18020428 - 19 Jan 2025
Viewed by 498
Abstract
A peak shaving approach in selected industrial loads helps minimize power usage during high demand hours, decreasing total energy expenses while improving grid stability. A battery energy storage system (BESS) can reduce peak electricity demand in distribution networks. Quasi-dynamic load flow analysis (QLFA) [...] Read more.
A peak shaving approach in selected industrial loads helps minimize power usage during high demand hours, decreasing total energy expenses while improving grid stability. A battery energy storage system (BESS) can reduce peak electricity demand in distribution networks. Quasi-dynamic load flow analysis (QLFA) accurately assesses the maximum loading conditions in distribution networks by considering factors such as load profiles, system topology, and network constraints. Achieving maximum peak shaving requires optimizing battery charging and discharging cycles based on real-time energy generation and consumption patterns. Seamless integration of battery storage with solar photovoltaic (PV) systems and industrial processes is essential for effective peak shaving strategies. This paper proposes a model predictive control (MPC) scheme that can effectively perform peak shaving of the total industrial load. Adopting an MPC-based algorithm design framework enables the development of an effective control strategy for complex systems. The proposed MPC methodology was implemented and tested on the Indian Utility 29 Node Distribution Network (IU29NDN) using the DIgSILENT Power Factory environment. Additionally, the analysis encompasses technical and economic results derived from a simulated storage operation and, taking Puducherry State Electricity Department tariff details, provides significant insights into the application of this method. Full article
(This article belongs to the Section F: Electrical Engineering)
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29 pages, 4950 KiB  
Article
Sustainable Design in Agriculture—Energy Optimization of Solar Greenhouses with Renewable Energy Technologies
by Danijela Nikolić, Saša Jovanović, Nebojša Jurišević, Novak Nikolić, Jasna Radulović, Minja Velemir Radović and Isidora Grujić
Energies 2025, 18(2), 416; https://doi.org/10.3390/en18020416 - 18 Jan 2025
Viewed by 549
Abstract
In modern agriculture today, the cultivation of agricultural products cannot be imagined without greenhouses. This paper presents an energy optimization of a solar greenhouse with a photovoltaic system (PV) and a ground-source heat pump (GSHP). The PV system generates electricity, while the GSHP [...] Read more.
In modern agriculture today, the cultivation of agricultural products cannot be imagined without greenhouses. This paper presents an energy optimization of a solar greenhouse with a photovoltaic system (PV) and a ground-source heat pump (GSHP). The PV system generates electricity, while the GSHP is used for heating and cooling. A greenhouse is designed with an Open Studio plug-in in the Google SketchUp environment, the EnergyPlus software (8.7.1 version) was used for energy simulation, and the GenOpt software (2.0.0 version) was used for optimization of the azimuth angle and PV cell efficiency. Results for different solar greenhouse orientations and different photovoltaic module efficiency are presented in the paper. The obtained optimal azimuth angle of the solar greenhouse was −8°. With the installation of a PV array with higher module efficiency (20–24%), it is possible to achieve annual energy savings of 6.87–101.77%. Also, with the PV module efficiency of 23.94%, a concept of zero-net-energy solar greenhouses (ZNEG) is achieved at optimal azimuth and slope angle. Through the environmental analysis of different greenhouses, CO2 emissions of PV and GSHP are calculated and compared with electricity usage. Saved CO2 emission for a zero-net-energy greenhouse is 6626 kg CO2/year. An economic analysis of installed renewable energy systems was carried out: with the total investment of 19,326 € for ZNEG, the payback period is 8.63 years. Full article
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23 pages, 3142 KiB  
Article
Performance Improvement of a Standalone Hybrid Renewable Energy System Using a Bi-Level Predictive Optimization Technique
by Ayman Al-Quraan, Bashar Al-Mharat, Ahmed Koran and Ashraf Ghassab Radaideh
Sustainability 2025, 17(2), 725; https://doi.org/10.3390/su17020725 - 17 Jan 2025
Viewed by 345
Abstract
A standalone hybrid renewable energy system (HRES) that combines different types of renewable energy sources and storages offers a sustainable energy solution by reducing reliance on fossil fuels and minimizing greenhouse gas emissions. In this paper, a standalone hybrid renewable energy system (HRES) [...] Read more.
A standalone hybrid renewable energy system (HRES) that combines different types of renewable energy sources and storages offers a sustainable energy solution by reducing reliance on fossil fuels and minimizing greenhouse gas emissions. In this paper, a standalone hybrid renewable energy system (HRES) involving wind turbines, photovoltaic (PV) modules, diesel generators (DG), and battery banks is proposed. For this purpose, it is necessary to size and run the proposed system for feeding a residential load satisfactorily. For two typical winter and summer weeks, weather historical data, including irradiance, temperature, wind speed, and load profiles, are used as input data. The overall optimization framework is formulated as a bi-level mixed-integer nonlinear programming (BMINLP) problem. The upper-level part represents the sizing sub-problem that is solved based on economic and environmental multi-objectives. The lower-level part represents the energy management strategy (EMS) sub-problem. The EMS task utilizes the model predictive control (MPC) approach to achieve optimal technoeconomic operational performance. By the definition of BMINLP, the EMS sub-problem is defined within the constraints of the sizing sub-problem. The MATLAB R2023a environment is employed to execute and extract the results of the entire problem. The global optimization solver “ga” is utilized to implement the upper sub-problem while the “intlinprg” solver solves the lower sub-problem. The evaluation metrics used in this study are the operating, maintenance, and investment costs, storage unit degradation, and the number of CO2 emissions. Full article
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25 pages, 9576 KiB  
Article
Renewable Energy Community Sizing Based on Stochastic Optimization and Unsupervised Clustering
by Luka Budin and Marko Delimar
Sustainability 2025, 17(2), 600; https://doi.org/10.3390/su17020600 - 14 Jan 2025
Viewed by 485
Abstract
Renewable Energy Communities (RECs) are emerging as significant in the global paradigm shift towards a smart and sustainable energy environment. By empowering energy consumers to actively participate in local energy generation, and sharing, using renewable energy sources, energy storage, and flexible loads, REC [...] Read more.
Renewable Energy Communities (RECs) are emerging as significant in the global paradigm shift towards a smart and sustainable energy environment. By empowering energy consumers to actively participate in local energy generation, and sharing, using renewable energy sources, energy storage, and flexible loads, REC participants can reduce costs, and also contribute to low-carbon objectives, providing the flexibility needed to address modern smart grid challenges. This article presents a mixed integer linear programming model for optimal sizing of the solar PVs and battery energy storage systems (BESS) of REC participants who engage in P2P energy exchange. The model is formulated using a two-stage stochastic optimization to address load and PV uncertainty, and unsupervised clustering to structure the data for the stochastic optimization process. The model enables sizing solar PVs for different rooftop geometries and the objective function includes comprehensively defined electricity, operational, and scaled investment costs for solar PV and BESS, where economic fairness constraints are analyzed and implemented. The model is validated on real solar and atmospheric measured data from Zagreb, Croatia, and publicly available household consumption data from Northern Germany. The article also analyzes how tariff models, and electricity prices affect PV and BESS sizes, cost reductions, and P2P energy exchange for different REC participants with varying consumption and production profiles. Full article
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26 pages, 4478 KiB  
Article
A Two-Stage Robust Optimization Strategy for Long-Term Energy Storage and Cascaded Utilization of Cold and Heat Energy in Peer-to-Peer Electricity Energy Trading
by Yun Chen, Yunhao Zhao, Xinghao Zhang, Ying Wang, Rongyao Mi, Junxiao Song, Zhiguo Hao and Chuanbo Xu
Energies 2025, 18(2), 323; https://doi.org/10.3390/en18020323 - 13 Jan 2025
Viewed by 371
Abstract
This study addresses the optimization of urban integrated energy systems (UIESs) under uncertainty in peer-to-peer (P2P) electricity trading by introducing a two-stage robust optimization strategy. The strategy includes a UIES model with a photovoltaic (PV)–green roof, hydrogen storage, and cascading cold/heat energy subsystems. [...] Read more.
This study addresses the optimization of urban integrated energy systems (UIESs) under uncertainty in peer-to-peer (P2P) electricity trading by introducing a two-stage robust optimization strategy. The strategy includes a UIES model with a photovoltaic (PV)–green roof, hydrogen storage, and cascading cold/heat energy subsystems. The first stage optimizes energy trading volume to maximize social welfare, while the second stage maximizes operational profit, considering uncertainties in PV generation and power prices. The Nested Column and Constraint Generation (NC&CG) algorithm enhances privacy and solution precision. Case studies with three UIESs show that the model improves economic performance, energy efficiency, and sustainability, increasing profits by 1.5% over non-P2P scenarios. Adjusting the robustness and deviation factors significantly impacts P2P transaction volumes and profits, allowing system operators to optimize profits and make risk-aligned decisions. Full article
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18 pages, 1262 KiB  
Article
Evaluation of Technical Aspects of Solar Photovoltaic (PV) Power Installations on Farmland
by Lorenzo Sabino, Rafiq Asghar, Fabio Crescimbini and Francesco Riganti Fulginei
Energies 2025, 18(2), 317; https://doi.org/10.3390/en18020317 - 13 Jan 2025
Viewed by 318
Abstract
This research evaluates the technical and economic aspects of solar photovoltaic (PV) power installations on farmland, utilizing a simulation model in MATLAB to forecast annual system output based on nominal power and meteorological data. This study compares various configurations, including single-sided versus double-sided [...] Read more.
This research evaluates the technical and economic aspects of solar photovoltaic (PV) power installations on farmland, utilizing a simulation model in MATLAB to forecast annual system output based on nominal power and meteorological data. This study compares various configurations, including single-sided versus double-sided modules and fixed versus tracker structures, to determine their efficiency, losses, and economic viability. The findings indicate that, while theoretically superior technologies may offer better production rates, their economic feasibility varies significantly depending on specific project conditions. The main conclusions drawn from this research emphasize that land-based PV systems present a promising solution for sustainable energy generation. By addressing challenges such as solar energy intermittency and the need for supportive infrastructure, this study highlights the potential for these systems to significantly contribute to reducing greenhouse gas emissions and enhancing energy resilience. This analysis underscores the importance of optimizing configurations to maximize both technical performance and economic returns, ultimately supporting a transition towards a more sustainable energy future. Full article
(This article belongs to the Special Issue Renewable Energy System Technologies: 2nd Edition)
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19 pages, 4115 KiB  
Article
Techno-Economic Design Analysis of Electric Vehicle Charging Stations Powered by Photovoltaic Technology on the Highways of Saudi Arabia
by Yassir Alhazmi
Energies 2025, 18(2), 315; https://doi.org/10.3390/en18020315 - 13 Jan 2025
Viewed by 418
Abstract
The globalization of electric vehicle development and production is a significant goal. The availability of charging stations helps to encourage the global transition to electric vehicles, which may lead to a decrease in traditional fuel consumption. Nevertheless, the rise in the number of [...] Read more.
The globalization of electric vehicle development and production is a significant goal. The availability of charging stations helps to encourage the global transition to electric vehicles, which may lead to a decrease in traditional fuel consumption. Nevertheless, the rise in the number of electric vehicles is accompanied by sustainability issues, such as managing the grid’s electrical demand, building more charging stations, and providing electricity from renewable resources in an efficient and sustainable manner, especially in Saudi Arabia. This work focused on three challenges regarding the installation of fast charging stations (FCSs) for electric vehicles (EVs) on highways. The first challenge is choosing optimal locations on highways to address the range of anxiety of EV drivers. The second challenge is to fuel these FCSs using renewable resources, such as photovoltaic (PV) panels, to make FCSs sustainable. The last challenge is to design FCSs by considering both highway driving behavior and the available renewable energy resources in order to cover charging demand. All of these challenges should be considered while planning the EV charging infrastructure of Saudi highways from both technical and economic perspectives. Thus, using the HOMER® Grid software (version 1.10.1 June 2023), locations on Saudi Arabian highways were selected based on the renewable resources of several roads that support a large number of vehicles traveling on them. These roads were the Makkah to Riyadh, Makkah to Abha, Riyadh to Dammam, Riyadh to NEOM, and Jeddah to NEOM roads. Electric vehicle charging stations with a capacity of 200 kW, 300 kW, and 500 kW were designed on these roads based on their natural renewable resources, which is PV energy. These roads are the most important roads in the Kingdom and witness heavy traffic. An economic study of these stations was carried out in addition to considering their efficiency. This study revealed that the 500 kW station is ideal for charging electric vehicles, with an annual energy production of 3,212,000 kWh. The 300 kW station had better efficiency but higher capital expenses. The 200 kW station could charge 6100 vehicles annually. The three stations on the Makkah to Riyadh, Makkah to Abha, and Riyadh to Dammam roads can charge 65,758 vehicles annually. The total cost of the project was USD 2,786,621, with the 300 kW plant having the highest initial investment, which can be potentially justified due to its higher power output. This study provides a comprehensive overview of the project costs and the potential returns of using solar power plants for charging electric vehicles. Full article
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25 pages, 2374 KiB  
Review
Sustainable Management of Photovoltaic Waste Through Recycling and Material Use in the Construction Industry
by Sandra Bulińska, Agnieszka Sujak and Michał Pyzalski
Materials 2025, 18(2), 284; https://doi.org/10.3390/ma18020284 - 10 Jan 2025
Viewed by 590
Abstract
The rapid expansion of photovoltaic (PV) technology as a source of renewable energy has resulted in a significant increase in PV panel waste, creating environmental and economic challenges. A promising strategy to address these challenges is the reuse of glass waste from decommissioned [...] Read more.
The rapid expansion of photovoltaic (PV) technology as a source of renewable energy has resulted in a significant increase in PV panel waste, creating environmental and economic challenges. A promising strategy to address these challenges is the reuse of glass waste from decommissioned PV panels as a component of cementitious materials. This review explores the potential of integrating glass waste from PV panels into cementitious materials, focusing on its impact on their mechanical, thermal, and durability properties. This analysis includes various methods of processing PV glass waste, such as crushing and grinding, to obtain the desired particle size for cementitious applications. It goes on to analyze how advances in cementitious materials can facilitate the incorporation of PV glass waste, helping to improve properties such as compressive strength, workability, and setting time. In addition, this review makes a detailed analysis of the long-term sustainability and environmental benefits of PV glass waste, highlighting its potential to reduce the carbon footprint of cementitious materials. Incorporating PV glass waste can improve certain properties of cementitious materials, resulting in increased durability and improved thermal insulation, while contributing to waste reduction and resource conservation. This review highlights the importance of developing standardized recycling methods and integration processes and identifies areas for further research to optimize the use of PV glass waste in cement formulations. Ultimately, the sustainable integration of PV glass panel waste into cementitious materials is a viable approach to promote green building practices and support a circular economy in the construction industry. Full article
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24 pages, 3302 KiB  
Article
Techno-Economic Analysis of Waste Heat Recovery in Automotive Manufacturing Plants
by Putu Diah Prajna Paramita, Sindu Daniarta, Attila R. Imre and Piotr Kolasiński
Appl. Sci. 2025, 15(2), 569; https://doi.org/10.3390/app15020569 - 9 Jan 2025
Viewed by 451
Abstract
This study proposes an innovative system for recovering waste heat from exhaust air after a regenerative thermal oxidiser process, integrating a Carnot battery and photovoltaic (PV) modules. The Carnot battery incorporates an organic Rankine cycle (ORC) with a recuperator, thermal energy storage (TES), [...] Read more.
This study proposes an innovative system for recovering waste heat from exhaust air after a regenerative thermal oxidiser process, integrating a Carnot battery and photovoltaic (PV) modules. The Carnot battery incorporates an organic Rankine cycle (ORC) with a recuperator, thermal energy storage (TES), and heat pump. Waste heat is initially captured in TES, with additional energy extracted by a heat pump to increase the temperature of a secondary fluid, effectively charging TES from both direct and indirect sources. The stored heat enables electricity generation via ORC. The result of this study shows a heat pump COP between 2.55 and 2.87, the efficiency of ORC ranging from 0.125 to 0.155, and the power-to-power of the Carnot battery between 0.36 and 0.40. Moreover, PV generates 1.35 GWh annually, primarily powering the heat pump and ORC system pump. The proposed system shows a total annual net generation of 4.30 GWh. Economic evaluation across four configurations demonstrates favourable outcomes, with a return on investment between 25% and 160%. The economic evaluation examined configurations with and without the PV system and recuperation process in the ORC. Results indicate that incorporating the PV system and recuperator significantly increases power output, offering a highly viable and sustainable energy solution. Full article
(This article belongs to the Section Energy Science and Technology)
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26 pages, 12223 KiB  
Article
Integrating GIS and AHP for Photovoltaic Farm Site Selection: A Case Study of Ikorodu, Nigeria
by Hubert Onuoha, Iheanacho Denwigwe, Olubayo Babatunde, Khadeejah Adebisi Abdulsalam, John Adebisi, Michael Emezirinwune, Taiwo Okharedia, Akintade Akindayomi, Kolawole Adisa and Yskandar Hamam
Processes 2025, 13(1), 164; https://doi.org/10.3390/pr13010164 - 9 Jan 2025
Viewed by 430
Abstract
Large-scale renewable energy plants such as solar photovoltaic (PV) farms are vital to the global transition to a green energy economy. They reduce greenhouse gas emissions, mitigate climate change, and promote sustainable and resilient energy. However, large-scale solar PV farms need adequate planning [...] Read more.
Large-scale renewable energy plants such as solar photovoltaic (PV) farms are vital to the global transition to a green energy economy. They reduce greenhouse gas emissions, mitigate climate change, and promote sustainable and resilient energy. However, large-scale solar PV farms need adequate planning and site selection for optimal performance. This study presents a geographic information system (GIS)-based multi-criteria decision-making (MCDM) framework utilizing the analytic hierarchy process (AHP) to identify optimal sites for utility-scale photovoltaic (PV) farms in Ikorodu, Lagos State, Nigeria. By integrating critical environmental, technical, economic, and social factors, the model evaluates land suitability for solar energy projects across the study area. The finding indicates that 68.77% of the land is unsuitable for development, with only 17.78% classified as highly suitable and 12.67% as moderately suitable. Marginally suitable and most appropriate areas are minimal, at 0.73% and 0.04%, respectively. This study provides a replicable approach for stakeholders and policymakers aiming to implement sustainable energy solutions, aligning with national renewable energy targets. Future research could integrate dynamic factors such as community engagement, land use changes, and evolving environmental policies to enhance decision-making models. This framework offers valuable insights into renewable energy planning and contributes to advancing Nigeria’s transition to sustainable energy systems. Full article
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17 pages, 19075 KiB  
Article
A Channel Attention-Driven Optimized CNN for Efficient Early Detection of Plant Diseases in Resource Constrained Environment
by Sana Parez, Naqqash Dilshad and Jong Weon Lee
Agriculture 2025, 15(2), 127; https://doi.org/10.3390/agriculture15020127 - 8 Jan 2025
Viewed by 467
Abstract
Agriculture is a cornerstone of economic prosperity, but plant diseases can severely impact crop yield and quality. Identifying these diseases accurately is often difficult due to limited expert availability and ambiguous information. Early detection and automated diagnosis systems are crucial to mitigate these [...] Read more.
Agriculture is a cornerstone of economic prosperity, but plant diseases can severely impact crop yield and quality. Identifying these diseases accurately is often difficult due to limited expert availability and ambiguous information. Early detection and automated diagnosis systems are crucial to mitigate these challenges. To address this, we propose a lightweight convolutional neural network (CNN) designed for resource-constrained devices termed as LeafNet. LeafNet draws inspiration from the block-wise VGG19 architecture but incorporates several optimizations, including a reduced number of parameters, smaller input size, and faster inference time while maintaining competitive accuracy. The proposed LeafNet leverages small, uniform convolutional filters to capture fine-grained details of plant disease features, with an increasing number of channels to enhance feature extraction. Additionally, it integrates channel attention mechanisms to prioritize disease-related features effectively. We evaluated the proposed method on four datasets: the benchmark plant village (PV), the data repository of leaf images (DRLIs), the newly curated plant composite (PC) dataset, and the BARI Sunflower (BARI-Sun) dataset, which includes diverse and challenging real-world images. The results show that the proposed performs comparably to state-of-the-art methods in terms of accuracy, false positive rate (FPR), model size, and runtime, highlighting its potential for real-world applications. Full article
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11 pages, 798 KiB  
Article
Sustainability Impact Evaluation of the Recycling of End-of-Life Crystalline Silicon Solar Photovoltaic Panel Waste in South Korea
by Soonho Kwon, Hae Jong Kim, Samyeon Kim and Sung Joo Hong
Sustainability 2025, 17(2), 431; https://doi.org/10.3390/su17020431 - 8 Jan 2025
Viewed by 604
Abstract
The end-of-life (EoL) management of solar panel waste has emerged as an important issue related to first-generation solar panels in South Korea, which have already entered their retirement stage. In this study, the sustainability impacts of three scenarios for recycling EoL solar panels, [...] Read more.
The end-of-life (EoL) management of solar panel waste has emerged as an important issue related to first-generation solar panels in South Korea, which have already entered their retirement stage. In this study, the sustainability impacts of three scenarios for recycling EoL solar panels, namely mechanical recycling (MR), chemical recycling (CR), and thermal recycling (TR), were investigated, and their environmental and economic benefits were evaluated using the life cycle sustainability assessment (LCSA) method, with landfilling as the reference scenario. The results obtained showed a high global warming potential (GWP) as well as acidification for MR owing to the additional burden of transportation and industrial processes associated with MR. For CR, the use of chemicals and subsequent landfilling resulted in approximately 4.7 times higher terrestrial eco-toxicity than was observed for the landfilling scenario. Further, the GWP of TR was approximately 1.5 times higher than that of CR owing to its high energy consumption. However, its environmental burden was generally lower than that of MR and CR. The results of this study, which capture the current situation of EoL PV panels in South Korea, can be employed to facilitate the establishment of regulations that ensure sustainable management in this regard. Full article
(This article belongs to the Section Environmental Sustainability and Applications)
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19 pages, 1888 KiB  
Article
Optimal Scheduling of Extreme Operating Conditions in Islanded Microgrid Based on Model Predictive Control
by Shi Su, Pengfei Ma, Qingyang Xie, Jie Liu, Xiangtao Zhuan and Lei Shang
Electronics 2025, 14(1), 206; https://doi.org/10.3390/electronics14010206 - 6 Jan 2025
Viewed by 419
Abstract
To address the optimal scheduling of islanded microgrids under extreme operating conditions, this paper proposes a demand response (DR) economic optimization scheduling strategy based on model predictive control (MPC). The strategy improves the utilization of photovoltaic (PV) and energy storage systems while ensuring [...] Read more.
To address the optimal scheduling of islanded microgrids under extreme operating conditions, this paper proposes a demand response (DR) economic optimization scheduling strategy based on model predictive control (MPC). The strategy improves the utilization of photovoltaic (PV) and energy storage systems while ensuring stable power supply to critical loads through a dynamic load shedding approach based on load priority and power system constraints. By incorporating time-of-use electricity pricing and load importance assessment, an innovative demand response incentive policy is designed to optimize consumer behavior and reduce grid load pressure. Experimental results demonstrate that the DR-MPC-based method reduces operating costs and increases renewable energy utilization compared to traditional methods. This approach is broadly applicable to pre-emptive load shedding and energy storage optimization in islanded microgrids during emergencies and is expected to be extended to the optimal scheduling of microgrid clusters in the future. Full article
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