Evaluating the most significant input parameters for forecasting global solar radiation of different sequences based on Informer
C Jiang, Q Zhu - Applied Energy, 2023 - Elsevier
The number of existing global solar radiation (GSR) observation stations is limited, and it is
challenging to meet the demand for scientific research and production. Different forecasting …
challenging to meet the demand for scientific research and production. Different forecasting …
[HTML][HTML] Solar radiation prediction based on convolution neural network and long short-term memory
T Zhu, Y Guo, Z Li, C Wang - Energies, 2021 - mdpi.com
Photovoltaic power generation is highly valued and has developed rapidly throughout the
world. However, the fluctuation of solar irradiance affects the stability of the photovoltaic …
world. However, the fluctuation of solar irradiance affects the stability of the photovoltaic …
A novel recurrent neural network approach in forecasting short term solar irradiance
Forecasting solar irradiance is of utmost importance in supplying renewable energy
efficiently and timely. This paper aims to experiment five variants of recurrent neural …
efficiently and timely. This paper aims to experiment five variants of recurrent neural …
Short-term solar irradiance forecasting using deep learning techniques: a comprehensive case study
Reliable estimation of solar irradiance is required for many solar energy applications such
as photovoltaics, water heating, cooking, solar microgrids, etc. Deep Learning techniques …
as photovoltaics, water heating, cooking, solar microgrids, etc. Deep Learning techniques …
Hourly forecasting of solar irradiance based on CEEMDAN and multi-strategy CNN-LSTM neural networks
Accurate and reliable solar irradiance forecasting can bring significant benefits for managing
electricity generation and distributing modern smart grid. However, the characteristics of …
electricity generation and distributing modern smart grid. However, the characteristics of …
[HTML][HTML] Optimizing artificial neural networks for the accurate prediction of global solar radiation: A performance comparison with conventional methods
Obtaining precise solar radiation data is the first stage in determining the availability of solar
energy. It is also regarded as one of the major inputs for a variety of solar applications. Due …
energy. It is also regarded as one of the major inputs for a variety of solar applications. Due …
Hourly solar irradiance forecasting based on encoder–decoder model using series decomposition and dynamic error compensation
J Tong, L Xie, S Fang, W Yang, K Zhang - Energy Conversion and …, 2022 - Elsevier
Accurate solar irradiance prediction is crucial for harnessing solar energy resources.
However, the pattern of irradiance sequence is intricate due to its nonlinear and non …
However, the pattern of irradiance sequence is intricate due to its nonlinear and non …
Deep learning and statistical methods for short-and long-term solar irradiance forecasting for Islamabad
The growing threat of global climate change stemming from the huge carbon footprint left
behind by fossil fuels has prompted interest in exploring and utilizing renewable energy …
behind by fossil fuels has prompted interest in exploring and utilizing renewable energy …
A novel soft computing model (Gaussian process regression with K-fold cross validation) for daily and monthly solar radiation forecasting (Part: I)
The main objective of this paper is to present Gaussian Process Regression (GPR) as a new
accurate soft computing model to predict daily and monthly solar radiation at Mashhad city …
accurate soft computing model to predict daily and monthly solar radiation at Mashhad city …
Development of a hybrid computational intelligent model for daily global solar radiation prediction
Providing an accurate and reliable solar radiation prediction is highly significant for optimal
design and management of thermal and solar photovoltaic systems. It is massively essential …
design and management of thermal and solar photovoltaic systems. It is massively essential …