Improved informer PV power short-term prediction model based on weather ty** and AHA-VMD-MPE
S Cui, S Lyu, Y Ma, K Wang - Energy, 2024 - Elsevier
Precise prediction of PV power in the short term is crucial for maintaining power system
stability and balance. However, the performance of conventional time series prediction …
stability and balance. However, the performance of conventional time series prediction …
Towards energy efficiency: A comprehensive review of deep learning-based photovoltaic power forecasting strategies
Time series forecasting still awaits a transformative breakthrough like that happened in
computer vision and natural language processing. The absence of extensive, domain …
computer vision and natural language processing. The absence of extensive, domain …
Spatio-temporal interpretable neural network for solar irradiation prediction using transformer
Deep learning models have been increasingly applied in the field of solar radiation
prediction. However, the characteristics of a deep learning black box model restrict its …
prediction. However, the characteristics of a deep learning black box model restrict its …
[HTML][HTML] A Hybrid Machine Learning Approach: Analyzing Energy Potential and Designing Solar Fault Detection for an AIoT-Based Solar–Hydrogen System in a …
This research aims to optimize the solar–hydrogen energy system at Kangwon National
University's Samcheok campus by leveraging the integration of artificial intelligence (AI), the …
University's Samcheok campus by leveraging the integration of artificial intelligence (AI), the …
[HTML][HTML] Advanced feature engineering in microgrid PV forecasting: A fast computing and data-driven hybrid modeling framework
This study introduces an innovative framework designed to forecast the fluctuating short-
term generation of photovoltaic (PV) energy in isolated microgrids. The framework relies …
term generation of photovoltaic (PV) energy in isolated microgrids. The framework relies …
[HTML][HTML] Application of three Transformer neural networks for short-term photovoltaic power prediction: A case study
In order to solve the potential safety hazards caused by the fluctuation of photovoltaic (PV)
power generation, it is necessary to predict it in advance and take countermeasures as soon …
power generation, it is necessary to predict it in advance and take countermeasures as soon …
Harnessing AI for solar energy: Emergence of transformer models
This review emphasizes the critical need for accurate integration of solar energy into power
grids. It meticulously examines the advancements in transformer models for solar …
grids. It meticulously examines the advancements in transformer models for solar …
A complementary fused method using GRU and XGBoost models for long-term solar energy hourly forecasting
Solar photovoltaic (PV) energy plays a vital role in global renewable energy generation.
Accurate and reliable solar energy forecasting is the key to improving energy scheduling …
Accurate and reliable solar energy forecasting is the key to improving energy scheduling …
A novel model to estimate regional differences in time-series solar and wind forecast predictability across small regions: A case study in South Korea
Forecasting techniques for solar and wind energy are essential for controlling their variability
and are being heavily researched. However, regional differences in predictability in these …
and are being heavily researched. However, regional differences in predictability in these …
Overview of Day-ahead Solar Power Forecasts Based on Weather Classifications and a Case Study in Taiwan
Solar power forecasting is essential for optimizing energy management and ensuring stable
grid operations. Accurately forecasting solar irradiance is a key factor to improve solar power …
grid operations. Accurately forecasting solar irradiance is a key factor to improve solar power …