Explainable AI and optimized solar power generation
This paper proposes a model called X-LSTM-EO, which integrates explainable artificial intelligence (XAI), long short-term memory (LSTM), and
Time Series Prediction of Solar Power Generation
The proposed model decomposes solar power generation time series data collected in Turkey and incorporates irradiance and seasonal features as
Solar Power Generation Prediction using Machine Learning Model
The Solar power generation forecasting prototype is a functional model that integrates hardware, data processing, machine learning algorithms and user interface to demonstrate the concept of solar
Research on short-term photovoltaic power generation
To achieve rapid and accurate online prediction, we propose a method that combines Principal Component Analysis (PCA) with a multi-strategy
Modelling, simulation, and measurement of solar power generation:
The development of a solar power generation model, multiple differential models, simulation and experimentation with a pilot solar rig served as alternate model for the prediction of
Predict the Power Production of a solar panel farm from
Goal: predict the hourly power production of a photovoltaic power
[2303.07875] Solar Power Prediction Using Machine Learning
This paper presents a machine learning-based approach for predicting solar power generation with high accuracy using a 99% AUC (Area Under the Curve) metric. The approach
Predicting Solar Power Generation from Weather Data
1 Motivation into the future using local time-series weather observation data. Specifically, we will use data from the National Solar Radiation Database (NSRDB)1, which conveniently i cludes both
Climate model shows large-scale wind and solar farms in the
Energy generation by wind and solar farms could reduce carbon emissions and thus mitigate anthropogenic climate change. But is this its only benefit? Li et al. conducted experiments
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