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 …

[HTML][HTML] Photovoltaic systems operation and maintenance: A review and future directions

H Abdulla, A Sleptchenko, A Nayfeh - Renewable and Sustainable Energy …, 2024‏ - Elsevier
The expansion of photovoltaic systems emphasizes the crucial requirement for effective
operations and maintenance, drawing insights from advanced maintenance approaches …

CNN-LSTM: An efficient hybrid deep learning architecture for predicting short-term photovoltaic power production

A Agga, A Abbou, M Labbadi, Y El Houm… - Electric Power Systems …, 2022‏ - Elsevier
Climate change is pushing an increasing number of nations to use green energy resources,
particularly solar power as an applicable substitute to traditional power sources. However …

[HTML][HTML] Short-term photovoltaic power forecasting using meta-learning and numerical weather prediction independent Long Short-Term Memory models

E Sarmas, E Spiliotis, E Stamatopoulos, V Marinakis… - Renewable Energy, 2023‏ - Elsevier
Short-term photovoltaic (PV) power forecasting is essential for integrating renewable energy
sources into the grid as it provides accurate and timely information on the expected output of …

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 …

Machine learning based solar photovoltaic power forecasting: A review and comparison

J Gaboitaolelwe, AM Zungeru, A Yahya… - IEEe …, 2023‏ - ieeexplore.ieee.org
The growing interest in renewable energy and the falling prices of solar panels place solar
electricity in a favourable position for adoption. However, the high-rate adoption of …

Time series forecasting of solar power generation for large-scale photovoltaic plants

H Sharadga, S Hajimirza, RS Balog - Renewable Energy, 2020‏ - Elsevier
Accurate solar power forecasting is essential for grid-connected photovoltaic (PV) systems
especially in case of fluctuating environmental conditions. The prediction of PV power output …

Short-term photovoltaic power forecasting based on long short term memory neural network and attention mechanism

H Zhou, Y Zhang, L Yang, Q Liu, K Yan, Y Du - Ieee Access, 2019‏ - ieeexplore.ieee.org
Photovoltaic power generation forecasting is an important topic in the field of sustainable
power system design, energy conversion management, and smart grid construction …

Review on forecasting of photovoltaic power generation based on machine learning and metaheuristic techniques

MN Akhter, S Mekhilef, H Mokhlis… - IET Renewable …, 2019‏ - Wiley Online Library
The modernisation of the world has significantly reduced the prime sources of energy such
as coal, diesel and gas. Thus, alternative energy sources based on renewable energy have …

Accurate photovoltaic power forecasting models using deep LSTM-RNN

M Abdel-Nasser, K Mahmoud - Neural computing and applications, 2019‏ - Springer
Photovoltaic (PV) is one of the most promising renewable energy sources. To ensure secure
operation and economic integration of PV in smart grids, accurate forecasting of PV power is …