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1. Segmentation Algorithms for Ground-Based Infrared Cloud Images

   https://doi.org/10.1109/ISGTEurope52324.2021.9639922  

   Terren-Serrano, Guillermo; Martinez-Ramon, Manel (October 2021, 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe))

   The increasing number of Photovoltaic (PV) systems connected to the power grid are vulnerable to the projection of shadows from moving clouds. Global Solar Irradiance (GSI) forecasting allows smart grids to optimize the energy dispatch, preventing energy shortages caused by occlusion of the sun. This investigation compares the performances of machine learning algorithms (not requiring labelled images for training) for realtime segmentation of clouds in images acquired using a ground-based infrared sky imager. Real-time segmentation is utilized to extract cloud features using only the pixels in which clouds are detected. 

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2. 3D Solar Harvesting and Energy Generation via Multilayers of Transparent Porphyrin and Iron Oxide Thin Films

   https://doi.org/10.3390/en16073173  

   Lin, Jou; Lyu, Mengyao; Shi, Donglu (April 2023, Energies)

   Photovoltaic solar cells have been extensively used for various applications and are considered one of the most efficient green energy sources. However, their 2D surface area solar harvesting has limitations, and there is an increasing need to explore the possibility of multiple layer solar harvest for enhanced energy density. To address this, we have developed spectral-selective transparent thin films based on porphyrin and iron oxide compounds that allow solar light to penetrate multiple layers, significantly increasing solar harvesting surface area and energy density. These thin films are designed as photovoltaic (PV) and photothermal (PT) panels that can convert photons into either electricity or thermal energy for various green energy applications, such as smart building skins and solar desalination. The advantages of this 3D solar harvesting system include enlarged solar light collecting surface area and increased energy density. The multilayer system transforms the current 2D to 3D solar harvesting, enabling efficient energy generation. This review discusses recent developments in the synthesis and characterization of PV and PT transparent thin films for solar harvesting and energy generation using multilayers. Major applications of the 3D solar harvesting system are reviewed, including thermal energy generation, multilayered DSSC PV system, and solar desalination. Some preliminary data on transparent multilayer DSSC PVs are presented. 

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3. Analysis of Pricing Trends and Grid Parity of Photovoltaic Systems

   Nguyen, B.; Hosseini, Z. S.; Gao, D. W. (October 2018, 2018 CIGRE US National Committee (USNC) Grid of the Future (GOTF) Conference)

   As an alternative, cleaner energy source, solar power is becoming a much bigger player in how electricity is generated and consumed. To assess how economically-viable solar power is in comparison to other forms of electricity, factors such as the return on investment (ROI) can be calculated. In addition, based on the average lifetime of an average photovoltaic (PV) system, energy purchase reduction, and revenue that can be generated by selling excess electricity back to the power grid, the economic viability of solar energy can be determined. The capital and commissioning cost of a PV system will continue to be a major factor in how viable a PV system will be. Thus, observing the trend in PV system costs over the past years will yield a point of grid parity, when solar becomes competitive with existing forms of energy generation, and show the most beneficial time frame for the customer to install the PV system. This paper seeks to provide some insight on how economic using solar energy can be. 

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4. A moment in the sun: solar nowcasting from multispectral satellite data using self-supervised learning

   https://doi.org/10.1145/3538637.3538854  

   Bansal, Akansha Singh; Bansal, Trapit; Irwin, David (June 2022, Proceedings of the Thirteenth ACM International Conference on Future Energy Systems (e-Energy))

   Solar energy is now the cheapest form of electricity in history. Unfortunately, significantly increasing the electric grid's fraction of solar energy remains challenging due to its variability, which makes balancing electricity's supply and demand more difficult. While thermal generators' ramp rate---the maximum rate at which they can change their energy generation---is finite, solar energy's ramp rate is essentially infinite. Thus, accurate near-term solar forecasting, or nowcasting, is important to provide advance warnings to adjust thermal generator output in response to variations in solar generation to ensure a balanced supply and demand. To address the problem, this paper develops a general model for solar nowcasting from abundant and readily available multispectral satellite data using self-supervised learning. Specifically, we develop deep auto-regressive models using convolutional neural networks (CNN) and long short-term memory networks (LSTM) that are globally trained across multiple locations to predict raw future observations of the spatio-temporal spectral data collected by the recently launched GOES-R series of satellites. Our model estimates a location's near-term future solar irradiance based on satellite observations, which we feed to a regression model trained on smaller site-specific solar data to provide near-term solar photovoltaic (PV) forecasts that account for site-specific characteristics. We evaluate our approach for different coverage areas and forecast horizons across 25 solar sites and show that it yields errors close to that of a model using ground-truth observations. 

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5. PV to Vehicle, PV to Grid, Vehicle to Grid, and Grid to Vehicle Micro Grid System Using Level Three Charging Station

   https://doi.org/10.1109/GreenTech52845.2022.9772041  

   Balal, Afshin; Giesselmann, Michael (March 2022, 2022 IEEE Green Technologies Conference (GreenTech))

   This paper makes use of electric vehicles (EVs) that are simultaneously connected to the Photovoltaic Cells (PV) and the power grid. In micro-grids, batteries of the electric vehicles (EVs) used as a source of power to feed the power grid in the peak demands of electricity. EVs can help regulation of the power grid by storing excess solar energy and returning it to the grid during high demand hours. This paper proposes a new architecture of micro-grids by using a rooftop solar system, Battery Electric Vehicles (BEVs), grid connected inverters, a boost converter, a bidirectional half-bridge converter, output filter, including L, LC, or LCL, and transformers. The main parts of this micro-grid are illustrated and modeled, as well as a simulation of their operation. In addition, simulation results explore the charging and discharging scenarios of the BEVs. 

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