A survey on deep learning methods for power load and renewable energy forecasting in smart microgrids
Microgrids have recently emerged as a building block for smart grids combining distributed
renewable energy sources (RESs), energy storage devices, and load management …
renewable energy sources (RESs), energy storage devices, and load management …
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 …
Peer-to-peer energy trading mechanism based on blockchain and machine learning for sustainable electrical power supply in smart grid
It is expected that peer to peer energy trading will constitute a significant share of research in
upcoming generation power systems due to the rising demand of energy in smart …
upcoming generation power systems due to the rising demand of energy in smart …
[HTML][HTML] A review on deep learning models for forecasting time series data of solar irradiance and photovoltaic power
RA Rajagukguk, RAA Ramadhan, HJ Lee - Energies, 2020 - mdpi.com
Presently, deep learning models are an alternative solution for predicting solar energy
because of their accuracy. The present study reviews deep learning models for handling …
because of their accuracy. The present study reviews deep learning models for handling …
[HTML][HTML] A systematic review of machine learning techniques related to local energy communities
In recent years, digitalisation has rendered machine learning a key tool for improving
processes in several sectors, as in the case of electrical power systems. Machine learning …
processes in several sectors, as in the case of electrical power systems. Machine learning …
A review on global solar radiation prediction with machine learning models in a comprehensive perspective
Y Zhou, Y Liu, D Wang, X Liu, Y Wang - Energy Conversion and …, 2021 - Elsevier
Global solar radiation information is the basis for many solar energy utilizations as well as
for economic and environmental considerations. However, because solar-radiation …
for economic and environmental considerations. However, because solar-radiation …
Load forecasting techniques for power system: Research challenges and survey
The main and pivot part of electric companies is the load forecasting. Decision-makers and
think tank of power sectors should forecast the future need of electricity with large accuracy …
think tank of power sectors should forecast the future need of electricity with large accuracy …
[HTML][HTML] A survey of machine learning models in renewable energy predictions
The use of renewable energy to reduce the effects of climate change and global warming
has become an increasing trend. In order to improve the prediction ability of renewable …
has become an increasing trend. In order to improve the prediction ability of renewable …
[HTML][HTML] Solar power forecasting using CNN-LSTM hybrid model
Photovoltaic (PV) technology converts solar energy into electrical energy, and the PV
industry is an essential renewable energy industry. However, the amount of power …
industry is an essential renewable energy industry. However, the amount of power …
Towards intelligent building energy management: AI-based framework for power consumption and generation forecasting
Due to global warming and climate changes, buildings including residential and commercial
are significant contributors to energy consumption. To this end, net zero energy building …
are significant contributors to energy consumption. To this end, net zero energy building …