Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities
The energy industry is at a crossroads. Digital technological developments have the
potential to change our energy supply, trade, and consumption dramatically. The new …
potential to change our energy supply, trade, and consumption dramatically. The new …
Deep learning models for solar irradiance forecasting: A comprehensive review
P Kumari, D Toshniwal - Journal of Cleaner Production, 2021 - Elsevier
The growing human population in this modern society hugely depends on the energy to
fulfill their day-to-day needs and activities. Renewable energy sources, especially solar …
fulfill their day-to-day needs and activities. Renewable energy sources, especially solar …
A review of very short-term wind and solar power forecasting
R Tawn, J Browell - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
Installed capacities of wind and solar power have grown rapidly over recent years, and the
pool of literature on very short-term (minutes-to hours-ahead) wind and solar forecasting has …
pool of literature on very short-term (minutes-to hours-ahead) wind and solar forecasting has …
A review on renewable energy and electricity requirement forecasting models for smart grid and buildings
The benefits of renewable energy are that it is sustainable and is low in environmental
pollution. Growing load requirement, global warming, and energy crisis need energy …
pollution. Growing load requirement, global warming, and energy crisis need energy …
Short-term photovoltaic power forecasting based on long short term memory neural network and attention mechanism
Photovoltaic power generation forecasting is an important topic in the field of sustainable
power system design, energy conversion management, and smart grid construction …
power system design, energy conversion management, and smart grid construction …
A survey of data fusion in smart city applications
The advancement of various research sectors such as Internet of Things (IoT), Machine
Learning, Data Mining, Big Data, and Communication Technology has shed some light in …
Learning, Data Mining, Big Data, and Communication Technology has shed some light in …
Deep learning-based forecasting approach in smart grids with microclustering and bidirectional LSTM network
Uncertainty modeling of renewable energy sources, load demand, electricity price, etc.
create a high volume of data in smart grids. Accordingly, in this article, a precise forecasting …
create a high volume of data in smart grids. Accordingly, in this article, a precise forecasting …
[HTML][HTML] An ensemble method to forecast 24-h ahead solar irradiance using wavelet decomposition and BiLSTM deep learning network
In recent years, the penetration of solar power at residential and utility levels has progressed
exponentially. However, due to its stochastic nature, the prediction of solar global horizontal …
exponentially. However, due to its stochastic nature, the prediction of solar global horizontal …
A comprehensive review and analysis of solar forecasting techniques
In the last two decades, renewable energy has been paid immeasurable attention to toward
the attainment of electricity requirements for domestic, industrial, and agriculture sectors …
the attainment of electricity requirements for domestic, industrial, and agriculture sectors …
Probabilistic solar irradiation forecasting based on variational Bayesian inference with secure federated learning
The irradiation forecasting technology is important for the effective utilization of solar power.
Existing irradiation forecasting methods have achieved excellent performance with a …
Existing irradiation forecasting methods have achieved excellent performance with a …