[HTML][HTML] Forecasting: theory and practice

F Petropoulos, D Apiletti, V Assimakopoulos… - International Journal of …, 2022 - Elsevier
Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

[HTML][HTML] A review and taxonomy of wind and solar energy forecasting methods based on deep learning

G Alkhayat, R Mehmood - Energy and AI, 2021 - Elsevier
Renewable energy is essential for planet sustainability. Renewable energy output
forecasting has a significant impact on making decisions related to operating and managing …

Deep learning neural networks for short-term photovoltaic power forecasting

A Mellit, AM Pavan, V Lughi - Renewable Energy, 2021 - Elsevier
Accurate short-term forecasting of photovoltaic (PV) power is indispensable for controlling
and designing smart energy management systems for microgrids. In this paper, different …

A comprehensive review on sustainable energy management systems for optimal operation of future-generation of solar microgrids

S Tajjour, SS Chandel - Sustainable Energy Technologies and …, 2023 - Elsevier
Conventional microgrids face a number of challenges due to intermittency of renewable
energy resources and the lack of any effective energy management system. Thus, there is a …

[HTML][HTML] Solar photovoltaic power forecasting: A review

KJ Iheanetu - Sustainability, 2022 - mdpi.com
The recent global warming effect has brought into focus different solutions for combating
climate change. The generation of climate-friendly renewable energy alternatives has been …

[HTML][HTML] A survey of machine learning models in renewable energy predictions

JP Lai, YM Chang, CH Chen, PF Pai - Applied Sciences, 2020 - mdpi.com
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 …

Deep learning in smart grid technology: A review of recent advancements and future prospects

M Massaoudi, H Abu-Rub, SS Refaat, I Chihi… - IEEE …, 2021 - ieeexplore.ieee.org
The current electric power system witnesses a significant transition into Smart Grids (SG) as
a promising landscape for high grid reliability and efficient energy management. This …

Accurate solar PV power prediction interval method based on frequency-domain decomposition and LSTM model

L Wang, M Mao, J Xie, Z Liao, H Zhang, H Li - Energy, 2023 - Elsevier
The stability operation and real-time control of the integrated energy system with distributed
energy resources determines the higher and higher requirements for the accuracy of solar …

[HTML][HTML] Trends and gaps in photovoltaic power forecasting with machine learning

A Alcañiz, D Grzebyk, H Ziar, O Isabella - Energy Reports, 2023 - Elsevier
The share of solar energy in the electricity mix increases year after year. Knowing the
production of photovoltaic (PV) power at each instant of time is crucial for its integration into …

A novel method based on time series ensemble model for hourly photovoltaic power prediction

Z Xiao, X Huang, J Liu, C Li, Y Tai - Energy, 2023 - Elsevier
Photovoltaic (PV) power generation technology is more and more widely used in smart
grids. Accurate prediction of PV power is very important for managing and planning of the …