Solar Energy Advances最新文献

{"title":"Performance evaluation of artificial neural network and hybrid artificial neural network based genetic algorithm models for global horizontal irradiance forecasting","authors":"A. Wahidna ,&nbsp;N. Sookia ,&nbsp;Y.K. Ramgolam","doi":"10.1016/j.seja.2024.100054","DOIUrl":"10.1016/j.seja.2024.100054","url":null,"abstract":"<div><p>The output of photovoltaic (PV) systems is highly dependent on Global Horizontal Irradiance (GHI). Thus, accurate prediction of GHI is essential to meet increasing energy demands, stabilise the electric grid system and mitigate climate change. The main objective of this study is to accurately model and forecast GHI at Albion, Mauritius for a time step of every 15 min using the Artificial Neural Network (ANN) and hybrid Artificial Neural Network based Genetic Algorithm (ANN-GA) techniques. Ground-based measurement (GBM) data, collected every 15 min for a winter month was checked for stationarity and normalised to enhance its quality. Only strongly correlated input variables were selected to minimise uncertainties in forecasts. Special emphasis is given to short-term forecasting with a relatively small dataset size. This work is repeated for 30 min and 1 h time scales. The study is further validated using satellite data for a different location (Curepipe) in Mauritius. The performance evaluation over different statistical metrics indicated that the ANN model has the best capabilities for GHI forecasting, regardless of the location. The highest quality forecasts from the ANN technique resulted in values of 0.9999 for correlation coefficient (r), 0.9999 for coefficient of determination (R²), 0.1537 W/m² for Mean Absolute Error (MAE), 0.0641 W/m² for Mean Square Error (MSE) and 0.2532 W/m² for Root Mean Square Error (RMSE). The best ANN technique outperformed the strongest hybrid ANN-GA technique for every measured performance indicator.</p></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"4 ","pages":"Article 100054"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667113124000044/pdfft?md5=956fc04634e2c27f53bacaef01e551c0&pid=1-s2.0-S2667113124000044-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139686182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mathematical modelling and technical analysis of an auxiliary system to reflect solar radiations for PV panels: Effect of mirror height on the system performance","authors":"Rahim Moltames,&nbsp;Younes Noorollahi,&nbsp;Hossein Yousefi","doi":"10.1016/j.seja.2024.100069","DOIUrl":"10.1016/j.seja.2024.100069","url":null,"abstract":"<div><p>The present study represents the design of a new auxiliary system to reflect solar radiations for PV panels. The goal is to choose the best mirror height for the proposed system, in which, despite the increase in the power production, the construction costs of the reflective system remain reasonable. Using a maximum PowerPoint Tracker System (MPPT), the sun is tracked to optimize solar radiation on the PV module. To analyze the energy aspects of the proposed system, an energy balance model with zero-dimensional characteristics was developed, owing to the uniform distribution of solar radiation and the thinness of the PV layers. In this model, the temperature distribution along the thickness of the panel layers is considered constant. Our simulation results indicate that the proposed system enables the production of approximately 2.9 times more electrical energy in comparison to conventional PVs without the concentrator, thereby demonstrating the energetic viability of the proposed system.</p></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"4 ","pages":"Article 100069"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667113124000196/pdfft?md5=d529f60781ab3098bfdc5f14e682d848&pid=1-s2.0-S2667113124000196-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142164202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimisation of the performance of a prototype instrument for measuring solar irradiation using artificial neural network","authors":"John Akolgo ,&nbsp;Gidphil Mensah ,&nbsp;Daniel Marfo ,&nbsp;Ebenezer Seesi ,&nbsp;Winfred Senyo Agbagah ,&nbsp;Francis Davis","doi":"10.1016/j.seja.2024.100065","DOIUrl":"10.1016/j.seja.2024.100065","url":null,"abstract":"<div><p>Accurate measurement of solar radiation is essential for understanding climate patterns, assessing solar energy potential, and predicting weather conditions. Over the years, solar radiation measuring instruments such as pyranometers and solarimeters have been used to achieve this objective. However, the high cost of these standard instruments makes the technology less accessible, especially to students and academic researchers in low-to-middle-income countries. A low-cost prototype solarimeter has been developed that operates using a mini solar PV panel and a microcontroller. During testing, it was found that as temperature increased the instrument had significant accuracy deviations. As such, this study seeks to optimise the performance of the prototype solarimeter using Artificial Neural Networks (ANNs), a powerful data-driven machine learning tool for optimisation. Solar radiation data was simultaneously collected using the prototype solarimeter and a standard solarimeter. Corresponding ambient temperature was also recorded for each solar radiation measurement. The data was used to train the ANN model to learn data patterns and to predict accurate solar radiation in spite of the ambient temperature. Results of the study revealed that temperature has a negative correlation (–0.7381) with accuracy, such that an increase in temperature reduces the accuracy of the prototype solarimeter. Increased temperature caused an accuracy deviation of about 27.16 %. The ANN model successfully predicts accurate solar radiation measurement with an R-squared of 0.974, RMSE of 49.24 W/m², and an accuracy of 86.32 % which represents a 13.39 % improvement in the performance of the prototype solarimeter. This study's novelty stands in its attempt to use machine learning to address the temperature sensitivity of a PV-based solar irradiance instrument. The results revealed here exposes the potency of deep learning models for optimising engineering systems.</p></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"4 ","pages":"Article 100065"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667113124000159/pdfft?md5=3756c9ddb39c1677b51f70cb8388209a&pid=1-s2.0-S2667113124000159-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142151035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing the reliability of probabilistic PV power forecasts using conformal prediction","authors":"Yvet Renkema ,&nbsp;Lennard Visser ,&nbsp;Tarek AlSkaif","doi":"10.1016/j.seja.2024.100059","DOIUrl":"https://doi.org/10.1016/j.seja.2024.100059","url":null,"abstract":"<div><p>The increasing integration of renewable energy, particularly solar photovoltaic (PV) power, presents challenges for power system operation. Accurate forecasts of renewable energy are both financially beneficial for electricity suppliers and necessary for grid operators to optimize operation and avoid grid imbalances. This paper proposes a forecasting framework to implement conformal prediction (CP) on top of point prediction models, which predict the PV power on a day-ahead basis, to quantify the uncertainty of those predictions. Simple and multiple linear regression, along with random forest regression, are used to construct the point predictions based on weather forecasts. Several variants of CP, including weighted CP, CP with k-nearest neighbors (KNN), CP with Mondrian binning, and conformal predictive systems, are built to transform the point predictions into rigorous uncertainty intervals or cumulative distribution functions to enhance reliability. The framework’s performance is evaluated using large datasets of weather predictions and PV power output in the Netherlands. Results indicate that CP combined with KNN and/or Mondrian binning after a linear regressor outperforms the corresponding linear quantile regressor. CP with KNN and Mondrian binning after using random forest regression demonstrates the most accurate probabilistic PV power forecasts, improving the weighted interval score by 14% compared to multiple linear quantile regression.</p></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"4 ","pages":"Article 100059"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667113124000093/pdfft?md5=e50bf24db2d7c7366a78de1ce2cf9e6d&pid=1-s2.0-S2667113124000093-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140604951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of solar district heating and renovation of buildings as measures for decarbonization of heat supply in rural areas","authors":"Jan Kelch,&nbsp;Oleg Kusyy,&nbsp;Johannes Zipplies,&nbsp;Janybek Orozaliev,&nbsp;Klaus Vajen","doi":"10.1016/j.seja.2024.100060","DOIUrl":"10.1016/j.seja.2024.100060","url":null,"abstract":"<div><p>In this study two different decarbonization strategies for rural heat supply are compared on the example of 180 buildings located in a small village in Germany with about 860 inhabitants and typically mainly old buildings, partly in half-timbered construction. The comparison shows that erection of a solar district heating system with solar fraction of about 67 % leads to similar heating costs as an energy efficient renovation followed by installation of decentralized air source heat pumps for most of the buildings. Both concepts aim to achieve a heat supply that is free from the local use of fossil fuels. While the solar district heating system can probably be realized within a few years and therefore achieves the full CO₂ savings promptly, this would take decades for the implementation of energy efficient renovation and heat pumps due to low renovation rate. Reaching climate-neutrality for the heat supply could thus be accelerated significantly by the construction of a solar district heating system. Moreover, the two decarbonization approaches do not appear to be fundamentally mutually exclusive: subsequent steady renovation of connected buildings will either increase solar share in heat supply or enable connection of new consumers at similar solar coverage rate. However, it should be also noted that with solar district heating alone, not always the same thermal comfort as with reinforced building renovation is achieved.</p></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"4 ","pages":"Article 100060"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266711312400010X/pdfft?md5=e097ad514ad30d676a76ab75029062d0&pid=1-s2.0-S266711312400010X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141401702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analytical model of light current-voltage characteristics of a solar cell based on experimental data","authors":"Volodymyr Chernenko ,&nbsp;Petro Yahanov ,&nbsp;Demyd Pekur ,&nbsp;Roman Korkishko ,&nbsp;Vasyl Kornaga ,&nbsp;Viktor Sorokin","doi":"10.1016/j.seja.2024.100073","DOIUrl":"10.1016/j.seja.2024.100073","url":null,"abstract":"<div><div>In this work, a modified experimental method for calculating the parameters of the one-exponential equation of the light current-voltage characteristic of solar cells has been developed using approximation and verification of experimental data. This approach allowed us to create a more accurate mathematical model of such characteristics. It has been confirmed that the approximation equation of the open circuit voltage versus short circuit current contains the necessary data to establish the numerical values of the p-n junction parameters: the imperfection factor and the saturation current of the one-exponential model of the light current-voltage characteristics of a solar cell. A comparison between the experimentally measured results and those predicted by the mathematical model results allowed not only to correctly determine the values of the parameters of the one-exponential equation of light current-voltage characteristics, but also to identify instrumental and computational errors in the experimental studies. An expression for calculating the series resistance based on verified current and voltage values at the point of maximum power was derived. In cases where the current or voltage values at the maximum power point are questionable, the determination of the series resistance value is possible using numerical methods for solving the equation of the single-exponential model in a narrow range of the light current-voltage characteristic curve in the vicinity of the maximum power point. The use of algorithms in maximum power point tracking systems that more reliably determine its coordinates increases the efficiency of these systems and the output power delivered to the load.</div></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"4 ","pages":"Article 100073"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Life cycle and damage assessment of the third generation fractal texturing solar panels","authors":"Siavash Gitifar ,&nbsp;Alireza Aslani ,&nbsp;Rahim Zahedi","doi":"10.1016/j.seja.2024.100066","DOIUrl":"10.1016/j.seja.2024.100066","url":null,"abstract":"<div><p>The photovoltaic (PV) sector has undergone both major expansion and evolution over the last decades, and currently, the technologies already marketed or still in the laboratory/research phase are numerous and very different. Likewise, in order to assess the energy and environmental impacts of these devices, life cycle assessment (LCA) studies related to these systems are always increasing. In this paper, utilizing the LCA method and SimaPro software, a comparative analysis has been done between conventional solar panels and fractal glass texture panels. In addition, a sensitivity analysis has been performed on the fractal feature of the panel and its role in environmental impacts and damages. The results show that for the three main environmental impacts, this new technology has 1 % less negative impacts in all three aspects of human health, ecosystems and resources compared to the conventional PV panels.</p></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"4 ","pages":"Article 100066"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667113124000160/pdfft?md5=9e7b5211bfdc831d71839f9267e15d67&pid=1-s2.0-S2667113124000160-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142173601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How to cool a warming world? – The potential of photovoltaic green cooling with natural refrigerants in sunbelt countries","authors":"Paul Kohlenbach ,&nbsp;Uli Jakob ,&nbsp;Philipp Munzinger ,&nbsp;Anja Werntges","doi":"10.1016/j.seja.2024.100070","DOIUrl":"10.1016/j.seja.2024.100070","url":null,"abstract":"<div><div>The study investigates the economic feasibility of photovoltaic-powered air-conditioning (AC) systems in thirteen different sunbelt countries. Two different technical solutions have been analysed: (i) hybrid (partially PV powered, grid-connected) and (ii) off-grid (fully PV powered, no grid connection). These two solutions have been studied for three different locations in each country, namely minimum, average and maximum annual global solar irradiation on the horizontal. Lastly, each solution and location has been examined for application in the residential and commercial sector. All solar-based air-conditioning scenarios use high efficiency AC appliances with R290 as refrigerant (Global Warming Potential – GWP of 1) and have been compared against a base-case scenario using AC units with moderate efficiency AC appliances with conventional R410a refrigerant (GWP of 2088) and 100 % grid electricity supply. The scope of the study is to identify the economic potential of solar PV cooling technologies. Levelized Cost of Electricity (LCOE) and Net Present Value (NPV) have been calculated for each scenario as part of the comparative analysis. It was found that hybrid photovoltaic-based air-conditioning for a residential house has a financial advantage over grid-based air-conditioning in eleven out of thirteen countries investigated. Exceptions are Ghana and Vietnam. Off-grid photovoltaic-based air-conditioning for residential houses is only economically feasible in five out of thirteen countries, namely Costa Rica, Iran, Grenada, Philippines and Thailand. Hybrid photovoltaic-based air-conditioning for a small commercial building has a financial advantage over grid-based air-conditioning in ten of thirteen countries, except in Colombia, Ghana and Iran. Off-grid photovoltaic-based air-conditioning for a small commercial building is only feasible in China, Grenada, Kenya and Philippines.</div></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"4 ","pages":"Article 100070"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142356737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Annual relative performance degradation in photovoltaic solar plants","authors":"Alberto Boretti ,&nbsp;Stefania Castelletto","doi":"10.1016/j.seja.2024.100074","DOIUrl":"10.1016/j.seja.2024.100074","url":null,"abstract":"<div><div>This study aims to assess annual relative performance degradation σ to be used in the computations of the Levelised Cost of Energy (LCOE) of new plants based on the standard year for weather and solar resource. The assessment is based on the experimental data of power generation, weather, and resource for different years, and simulations of power generation by using the National Renewable Energy Laboratory (NREL) System Advisor Model (SAM) software. The raw data of power generation for 53 different plants spanning about one decade show a σ assessed at &lt;0.29 %. This makes it reasonable to assume in SAM σ = 0 % to σ = 0.29 %. This is less than the default σ = 0.5 % currently used in SAM based on limited outdated data. The updated performance degradation factor diminished to σ = 0–0.29 % reduces the computed LCOE for typical new projects in the United States from 2.86 to 2.74–2.80 ¢/kWh. Correction of the σ trends for interannual variability of weather and resource is unnecessary, providing enough years of operation are covered, given the inaccuracies in the model and the supporting data, the mitigation by management of the performance changes, and the complex phenomena correlated to the change of weather and irradiance affecting the power output in different directions. The reduced σ is the result of a significant product improvement over the last decades, especially for large power plants, compared to the plant which provided data for the prior correlation of performance degradation, and much better management and maintenance of the plants.</div></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"4 ","pages":"Article 100074"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Turning weakness into strength - A feasibility analysis and comparison of datacenter deployment in hot and cold climates","authors":"Michael Chrysostomou ,&nbsp;Nicholas Christofides ,&nbsp;Stelios Ioannou","doi":"10.1016/j.seja.2024.100068","DOIUrl":"10.1016/j.seja.2024.100068","url":null,"abstract":"<div><p>Datacenters are major components of the Information and Communication Technologies (ICT) responsible for storing, processing and transmitting enormous amounts of data every second. The significance and importance of datacenters in the world economy can be identified from studies which report that in 2023, datacenter infrastructures consumed a total of 4 % of global electricity and contributed 3–5% of global carbon emissions, whereas between the years of 2017–2021, datacenters added $2.1 trillion to the U.S. Gross Domestic Product (GDP). A big portion of energy supplied in datacenters is consumed by the required cooling systems hence companies do not favor developments in hot climate countries. However, due to environmental and climate change concerns along with the steep increase of energy production costs in recent years made the industry look for alternatives. This work includes an in-depth feasibility and comparative study of datacenter construction and operation in hot and cold European countries and addresses the environmental impact of photovoltaics integration in the electrical supply system. The study considers cost parameters (land, operating expenses, photovoltaic system, etc.), the net present cost and levelized cost of energy which are different for each European country under investigation. Furthermore, for every country under consideration, the PV generation was simulated using the PVsyst software which includes multiple meteorological databases, whereas the feasibility analysis was simulated using the HOMER Pro software which integrates components, resources and economic calculations. An elaborate analysis of the results knocks down the common belief that datacenters have lower operational and running expenses in cold climates because of lower cooling requirements. On the contrary, this study shows that hot climates with high solar radiation levels may favor the operation of datacenters by providing 45 % higher green energy and 35 % lower CO₂ emissions, whereas the cooling cost is only 5 % higher. In addition, the break-even period for the photovoltaic system in Southern European countries with hot climates is 3–4 times faster.</p></div>","PeriodicalId":101174,"journal":{"name":"Solar Energy Advances","volume":"4 ","pages":"Article 100068"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667113124000184/pdfft?md5=b0f0a0c88f49c47d2f5f04d961744b25&pid=1-s2.0-S2667113124000184-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142173602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}