A state of art review on estimation of solar radiation with various models
Solar radiation is free, and very useful input for most sectors such as heat, health, tourism,
agriculture, and energy production, and it plays a critical role in the sustainability of …
agriculture, and energy production, and it plays a critical role in the sustainability of …
A review of state-of-the-art and short-term forecasting models for solar pv power generation
WC Tsai, CS Tu, CM Hong, WM Lin - Energies, 2023 - mdpi.com
Accurately predicting the power produced during solar power generation can greatly reduce
the impact of the randomness and volatility of power generation on the stability of the power …
the impact of the randomness and volatility of power generation on the stability of the power …
[HTML][HTML] Advancing short-term solar irradiance forecasting accuracy through a hybrid deep learning approach with Bayesian optimization
The optimization of solar energy integration into the power grid relies heavily on accurate
forecasting of solar irradiance. In this study, a new approach for short-term solar irradiance …
forecasting of solar irradiance. In this study, a new approach for short-term solar irradiance …
Improving soil moisture prediction with deep learning and machine learning models
Reliable soil moisture (SM) data is critical for effective water resources management, yet its
accurate measurement and prediction remain challenging. This study was conducted to …
accurate measurement and prediction remain challenging. This study was conducted to …
An efficient and robust fingerprint based localization method for multi floor indoor environment
Fingerprint-based indoor localization is one of the most promising solutions for various
Intelligent Internet of Things (IIoT) systems. However, recent studies show that the key …
Intelligent Internet of Things (IIoT) systems. However, recent studies show that the key …
A short-term probabilistic photovoltaic power prediction method based on feature selection and improved LSTM neural network
R Liu, J Wei, G Sun, SM Muyeen, S Lin, F Li - Electric Power Systems …, 2022 - Elsevier
With the increase of solar photovoltaic (PV) penetration in power system, the impact of
random fluctuation of PV power on the secure operation of power grid becomes more and …
random fluctuation of PV power on the secure operation of power grid becomes more and …
Simulating soil hydrologic dynamics using crop growth and machine learning models
Accurate measurement of crop evapotranspiration (ETc) and soil moisture content (SMC) is
critical for different purposes, including develo** irrigation scheduling practices that …
critical for different purposes, including develo** irrigation scheduling practices that …
Solar and wind energy forecasting for green and intelligent migration of traditional energy sources
Fossil-fuel-based power generation leads to higher energy costs and environmental
impacts. Solar and wind energy are abundant important renewable energy sources (RES) …
impacts. Solar and wind energy are abundant important renewable energy sources (RES) …
A New Insight for Daily Solar Radiation Prediction by Meteorological Data Using an Advanced Artificial Intelligence Algorithm: Deep Extreme Learning Machine …
Reliable and precise estimation of solar energy as one of the green, clean, renewable and
inexhaustible types of energies can play a vital role in energy management, especially in …
inexhaustible types of energies can play a vital role in energy management, especially in …
A novel hybrid intelligent approach for solar photovoltaic power prediction considering UV index and cloud cover
The power generation from photovoltaic plants depends on varying meteorological
conditions. These meteorological conditions such as solar irradiance, temperature, and wind …
conditions. These meteorological conditions such as solar irradiance, temperature, and wind …