Global Organization
This paper proposes a model called X-LSTM-EO, which integrates explainable artificial intelligence (XAI), long short-term memory (LSTM), and equilibrium optimizer (EO) to …
In this section, we cover the various models and techniques for anomaly detection in the power generation for the two power plants and assess the internal and …
Solar power generation is expanding globally as a result of growing energy demands and depleting fossil fuel reserves, which are presently the primary sources of power generation. In the realm of ...
Environment induced dust on solar panel hampers power generation at large. This paper focuses on CNN based approach to detect dust on solar panel and predicted the …
The real-time testing of the AI-based drone system involved a comprehensive …
Consequently, such sites offer challenges for the solar panels such as increased temperature, humidity and high dust levels that negatively affect their power generation …
Detecting and replacing defective photovoltaic modules is essential as they directly impact power generation efficiency.
This study aims to present deep learning algorithms for electrical demand prediction and solar PV power generation forecasting. Therefore, we proposed a novel multi …
The rapid industrial growth in solar energy is gaining increasing interest in renewable power from smart grids and plants. Anomaly detection in photovoltaic (PV) systems …
The photovoltaic power generation is commonly used renewable power generation in the world but the solar cells performance decreases with increasing of panel …
Significant fluctuations in temperature and solar radiation can have a substantial effect on energy production . Due to of the nature of these variables, PV power generation may become unstable with causing a …
The real-time testing of the AI-based drone system involved a comprehensive study of two different solar power generation systems, one on the ground and one on the roof. …
Cracks are evaluated in several works in literature. They are found to reduce …
Solar PV power generation involves converting sunlight into electricity using solar panels. Solar panels, typically made of silicon cells, capture photons from sunlight and …
Accurate solar power generation forecasting is paramount for optimizing renewable energy systems and ensuring sustainability in our evolving energy landscape. This …
Based on this, this paper proposes a PV power generation anomaly detection method based on Quantile Regression Recurrent Neural Network (QRRNN). First, the characteristics of solar …
Cracks are evaluated in several works in literature. They are found to reduce the power generation of a PV system and give rise to other defects like hot spots and Potential …
We provide an enhanced model called autoencoder LSTM in our suggested framework, which is critical in forecasting three critical solar power generation parameters: …
Energies 2022, 15, 1082 2 of 17 inverter shutdown, shading, and inverter maximum power point [8]. Extrinsic components do not emerge by the PV and still undermine its power generation.
As the energy problem becomes tenser, solar energy is used and researched increasingly. Traditional solar power generation photovoltaic panels have low power …
The world''s energy consumption is outpacing supply due to population growth and technological advancements. For future energy demands, it is critical to progress toward a …
121 the power generation of a solar installation. The method doesn''t need any sensor 122 apparatus for fault/anomaly detection. Instead, it exclusively needs the assembly output 123 of …
Consequently, such sites offer challenges for the solar panels such as …