AIMC Topic: Solar Energy

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Integrated forecasting and deep reinforcement learning for price-based self-scheduling of PV-BESS: Utility-scale evidence in Chile.

PloS one
Deep Reinforcement Learning (DRL) shows good performance for optimizing battery energy storage systems (BESS) coordinated operations with photovoltaic plants (PV), yet most studies rely on simulations. Bridging the gap to practical application requir...

Enhanced multi-horizon photovoltaic power forecasting: A novel approach integrating ICEEMDAN decomposition with hierarchical frequency neural networks.

PloS one
As a crucial renewable energy source, solar PV power generation drives environmental protection and energy transformation. However, existing forecasting models struggle to accurately capture the complex dynamics of photovoltaic (PV) power, primarily ...

Fusion of crayfish optimization algorithm and MNS-YOLO for solar cell defect detection.

PloS one
Inspection and diagnosis of construction projects involves health monitoring of buildings and related facilities, and the utilization of renewable energy sources, such as solar energy, is critical to the smooth operation of modern construction projec...

Short-term power prediction of photovoltaic power stations based on Kepler optimization algorithm and VMD-CNN-LSTM model.

PloS one
This study focuses on the short-term power prediction of photovoltaic power stations, aiming to address the intermittent and fluctuating problems of photovoltaic power generation, in order to improve the prediction accuracy and ensure the stable oper...

Explaining solar forecasts with generative AI: A two-stage framework combining transformers and LLMs.

PloS one
Accurate and interpretable solar power forecasting is critical for effectively integrating Photo-Voltaic (PV) systems into modern energy infrastructure. This paper introduces a novel two-stage hybrid framework that couples deep learning-based time se...

High-Throughput Molecular Design of Donors and Non-Fullerene Acceptors for Organic Solar Cells Based on Convolutional Neural Networks.

Journal of chemical information and modeling
Designing novel high-performance donor and acceptor molecules is essential for improving the power conversion efficiency (PCE) of organic solar cells (OSCs). However, conventional experimental methods for developing new materials are often time-consu...

An integrated genetic algorithm-machine learning approach for morphological optimization of high-rise residential districts in Yulin.

PloS one
The pursuit of global carbon neutrality necessitates addressing the dual challenge of enhancing solar energy utilization while improving thermal comfort in high-rise residential areas, particularly in Yulin, northern Shaanxi, China, where abundant so...

A Bottom-Up Approach Integrating Computer Vision with Material Flow Analysis to Estimate the Recycling Potential of Distributed Solar Panels Using Satellite Imagery.

Environmental science & technology
The rapid deployment of solar photovoltaic (PV) systems has created a growing challenge in managing end-of-life panels. While many studies project future recycling potential, they are often limited by the lack of data on existing distributed PV insta...

Predictive hybrid model of a grid-connected photovoltaic system with DC-DC converters under extreme altitude conditions at 3800 meters above sea level.

PloS one
This study aims to develop a predictive hybrid model for a grid-connected PV system with DC-DC optimizers, designed to operate in extreme altitude conditions at 3800 m above sea level. This approach seeks to address the "curse of dimensionality" by r...

Long-term solar radiation forecasting in India using EMD, EEMD, and advanced machine learning algorithms.

Environmental monitoring and assessment
Solar radiation plays a critical role in the carbon sequestration processes of terrestrial ecosystems, making it a key factor in environmental sustainability among various renewable energy sources. This study integrates two advanced signal processing...