A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization

R Ahmed, V Sreeram, Y Mishra, MD Arif - Renewable and Sustainable …, 2020 - Elsevier
Integration of photovoltaics into power grids is difficult as solar energy is highly dependent
on climate and geography; often fluctuating erratically. This causes penetrations and voltage …

Advanced methods for photovoltaic output power forecasting: A review

A Mellit, A Massi Pavan, E Ogliari, S Leva, V Lughi - Applied Sciences, 2020 - mdpi.com
Forecasting is a crucial task for successfully integrating photovoltaic (PV) output power into
the grid. The design of accurate photovoltaic output forecasters remains a challenging issue …

Using machine learning in photovoltaics to create smarter and cleaner energy generation systems: A comprehensive review

A Sohani, H Sayyaadi, C Cornaro… - Journal of Cleaner …, 2022 - Elsevier
Photovoltaic (PV) technologies are expected to play an increasingly important role in future
energy production. In parallel, machine learning has gained prominence because of a …

Advancement of lithium-ion battery cells voltage equalization techniques: A review

UK Das, P Shrivastava, KS Tey, MYIB Idris… - … and Sustainable Energy …, 2020 - Elsevier
Recently, the use of electric batteries has reached great heights due to the invention of
electric vehicles (EVs). Many lithium-ion battery cells are usually connected in series to meet …

Ultra-short-term exogenous forecasting of photovoltaic power production using genetically optimized non-linear auto-regressive recurrent neural networks

MA Hassan, N Bailek, K Bouchouicha, SC Nwokolo - Renewable Energy, 2021 - Elsevier
Accurate and credible ultra-short-term photovoltaic (PV) power production prediction is very
important in short-term resource planning, electric power dispatching, and operational …

SolarNet: A hybrid reliable model based on convolutional neural network and variational mode decomposition for hourly photovoltaic power forecasting

D Korkmaz - Applied Energy, 2021 - Elsevier
Photovoltaic (PV) power generation has high uncertainties due to the randomness and
imbalance nature of solar energy and meteorological parameters. Hence, accurate PV …

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

Z **ao, 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 …

Completed review of various solar power forecasting techniques considering different viewpoints

YK Wu, CL Huang, QT Phan, YY Li - Energies, 2022 - mdpi.com
Solar power has rapidly become an increasingly important energy source in many countries
over recent years; however, the intermittent nature of photovoltaic (PV) power generation …

[HTML][HTML] A Multi-step ahead photovoltaic power forecasting model based on TimeGAN, Soft DTW-based K-medoids clustering, and a CNN-GRU hybrid neural network

Q Li, X Zhang, T Ma, D Liu, H Wang, W Hu - Energy Reports, 2022 - Elsevier
Accurate photovoltaic (PV) power generation forecasting is very important for making
economic and reliable power dispatching plans. This study proposes a multi-step ahead PV …

Ensemble approach of optimized artificial neural networks for solar photovoltaic power prediction

S Al-Dahidi, O Ayadi, M Alrbai, J Adeeb - IEEE Access, 2019 - ieeexplore.ieee.org
The use of data-driven ensemble approaches for the prediction of the solar Photovoltaic
(PV) power production is promising due to their capability of handling the intermittent nature …