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 …

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 …

A day-ahead PV power forecasting method based on LSTM-RNN model and time correlation modification under partial daily pattern prediction framework

F Wang, Z Xuan, Z Zhen, K Li, T Wang, M Shi - Energy Conversion and …, 2020 - Elsevier
Photovoltaic (PV) power generation is an effective means to realize solar energy utilization.
Due to the natural characteristics of random fluctuations in solar energy, the applications of …

A review of deep learning for renewable energy forecasting

H Wang, Z Lei, X Zhang, B Zhou, J Peng - Energy Conversion and …, 2019 - Elsevier
As renewable energy becomes increasingly popular in the global electric energy grid,
improving the accuracy of renewable energy forecasting is critical to power system planning …

Time series forecasting for hourly photovoltaic power using conditional generative adversarial network and Bi-LSTM

X Huang, Q Li, Y Tai, Z Chen, J Liu, J Shi, W Liu - Energy, 2022 - Elsevier
More and more photovoltaic (PV) power generation is incorporated into the grid. However,
the intermittence and fluctuation of solar energy have brought huge challenges to the safe …

[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 …

A review on renewable energy and electricity requirement forecasting models for smart grid and buildings

T Ahmad, H Zhang, B Yan - Sustainable Cities and Society, 2020 - Elsevier
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 …

Day-ahead hourly photovoltaic power forecasting using attention-based CNN-LSTM neural network embedded with multiple relevant and target variables prediction …

J Qu, Z Qian, Y Pei - Energy, 2021 - Elsevier
Accurate forecasting of photovoltaic power plays a pivotal role in the integration, operation,
and scheduling of smart grid systems. Notably, volatility and intermittence of solar energy …

[HTML][HTML] Deep learning based forecasting of photovoltaic power generation by incorporating domain knowledge

X Luo, D Zhang, X Zhu - Energy, 2021 - Elsevier
Solar energy constitutes an effective supplement to traditional energy sources. However,
photovoltaic power generation (PVPG) is strongly weather-dependent, and thus highly …

Taxonomy research of artificial intelligence for deterministic solar power forecasting

H Wang, Y Liu, B Zhou, C Li, G Cao, N Voropai… - Energy Conversion and …, 2020 - Elsevier
With the world-wide deployment of solar energy for a sustainable and renewable future, the
stochastic and volatile nature of solar power pose significant challenges to the reliable …