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8 results for “Photovoltaic plants”
Dataset for Accuracy of Grid-Connected Photovoltaic Power Plant: A Novel Approach Using Hybrid Variational Mode Decomposition and CNN-LSTM Model
<p>This research paper introduces a deep learning hybrid model employing Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) for short-term photovoltaic (PV) solar energy forecasting.The proposed method integrates the Variational Mode Decomposition (VMD) algo-rithm with the CNN-LSTM model to predict PV power generation from a solar farm in Boussada, Algeria, from January 1, 2019, to December 31, 2020. The performance of the developed model is benchmarked against other deep learning models (VMD-CNN, VMD-LSTM, CNN-LSTM) across various time horizons (15, 30, and 60 minutes) to provide a comprehensive evaluation. Our findings exhibit greater performance of the developed model compared to other architectures, showcasing promising results in solar power forecasting. This research contributes to the main goal of enhancing EMS by providing accurate solar energy forecasts.</p>
The dataset of photovoltaic power plant distribution in China by 2020
<p>Photovoltaic (PV) technology, an efficient solution for mitigating the impacts of climate change, has been increasingly used across the world to replace fossil-fuel power to minimize greenhouse gas emissions. With the world's highest cumulative and fastest built PV capacity, China needs to assess the environmental and social impacts of these established photovoltaic (PV) power plants. However, a comprehensive map regarding the PV power plants' locations and extent remain scarce on the country scale. This study developed a workflow combining machine learning and visual interpretation methods with big satellite data to map PV power plants across China. We applied a pixel-based Random Forest (RF) model to classify the PV power plants from composite images in 2020 with 30-meter spatial resolution on Google Earth Engine (GEE). The result classification map was further improved by a visual interpretation approach. Eventually, we established a map of PV power plants in China by 2020, covering a total area of 2917 km<sup>2</sup>. We found that most PV power plants were sited on cropland, followed by barren land and grassland based on the derived national PV map. In addition, the installation of PV power plants has generally decreased the vegetation cover. This new dataset is expected to be conducive to policy management, environmental assessment, and further classification of PV power plants.</p>
Monthly production and open-circuit string voltage measurements after 10-year operation of three photovoltaic plants in Southern Spain affected by severe potential-induced degradation
<p>Data are formated in a spreadsheet file. Data are presented from three photovoltaic plants in Southern Spain (Córdoba province - Northern Andalucía) designed and installed by the same person, with the same photovoltaic module and the same model of inverter, deployed at the same time (end 2009). The plants are severely affected by potential-induced degradation (PID), so that secondary effects produce some by-pass diodes to activate, producing three families of open-circuit voltage (Voc) in the modules (~40V), (~26V) and (~12V) of a total of nominal Voc of 42,6V. </p> <p>Monthly production is shown along 11 years (2010-2021), and the measurements of the open-circuit voltage of the strings after 10 years of operation along with the voltage range of the modules of each string.</p> <p>Sheet 1: configuration of the architecture of the three photovoltaic plants and the features of the photovoltaic module installed.</p> <p>Sheet 2: energy production for 11 years of opetation. In the last years some recovery is shown in plant 1 and 2 because a repowering project.</p> <p>Sheet 3: partial climate data of the towns were the plants are located.</p> <p>Sheet 4: open-circuit voltages of the strings and number of modules in each string with open-circuit voltage in the ranges (~40V) and (<=26V) in plant 1, july-2018.</p> <p>Sheet 5: open-circuit voltages of the strings and number of modules in each string with open-circuit voltage in the ranges (~40V), (~26V) and (~12V) in plant 2, july-2020.</p>
Supplementary Material for "How do seasonal and technical factors affect generation efficiency of photovoltaic power plants?"
<p>Supplementary material for the paper "How do seasonal and technical factors affect generation efficiency of photovoltaic power plants?".</p><p>This supplementary information provides:</p><ul><li>Table S1. Monthly solar irradiation for each plants</li><li>Table S2. Summary of input and output factors, and efficiency scores</li><li>Table S3. Rainy season of the northern Kyushu region</li><li>Table S4. Summary of parameters for the regression model</li><li>Table S5. Average monthly solar irradiation for three cities</li><li>Figure S1. Regression line for each of the PV power plants</li></ul>
GIS files for photovoltaic plant localization
<p>List of files generated for research related to the location of photovoltaic plants.</p>
ANALYSIS OF THE PROBLEMS OF THE DEVELOPMENT OF PHOTOVOLTAIC SOLAR POWER PLANTS IN UZBEKISTAN
Open the record for dataset details and reuse information.
Supporting data for Loik et al. 2017 Wavelength-Selective Solar Photovoltaic Systems: Powering greenhouses for plant growth at the food-energy-water nexus. Earth's Future
Open the record for dataset details and reuse information.
Supplementary Information datasets: Evaporation Reduction and Energy Generation Potential using Floating Photovoltaic Power Plants on the Aswan High Dam Reservoir
<p>These files contain supplementary information regarding the "Evaporation Reduction and Energy Generation Potential using Floating Photovoltaic Power Plants on the Aswan High Dam Reservoir"</p>
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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