[HTML][HTML] Review on the application of photovoltaic forecasting using machine learning for very short-to long-term forecasting

PNL Mohamad Radzi, MN Akhter, S Mekhilef… - Sustainability, 2023 - mdpi.com
Advancements in renewable energy technology have significantly reduced the consumer
dependence on conventional energy sources for power generation. Solar energy has …

Accurate one step and multistep forecasting of very short-term PV power using LSTM-TCN model

T Limouni, R Yaagoubi, K Bouziane, K Guissi… - Renewable Energy, 2023 - Elsevier
Accurate PV power forecasting is becoming a mandatory task to integrate the PV plant into
the electrical grid, scheduling and guaranteeing the safety of the power grid. In this paper, a …

[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 …

Photovoltaic systems and sustainable communities: New social models for ecological transition. The impact of incentive policies in profitability analyses

I D'Adamo, M Mammetti, D Ottaviani, I Ozturk - Renewable Energy, 2023 - Elsevier
The issue of energy independence and sustainability are two major challenges in energy
decision-making models. Prosumer development and sustainable community models are …

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] A deep LSTM network for the Spanish electricity consumption forecasting

JF Torres, F Martínez-Álvarez, A Troncoso - Neural Computing and …, 2022 - Springer
Nowadays, electricity is a basic commodity necessary for the well-being of any modern
society. Due to the growth in electricity consumption in recent years, mainly in large cities …

[HTML][HTML] Advances in Short-Term Solar Forecasting: A Review and Benchmark of Machine Learning Methods and Relevant Data Sources

F Pandžić, T Capuder - Energies, 2023 - mdpi.com
Solar forecasting is becoming increasingly important due to the exponential growth in total
global solar capacity each year. More photovoltaic (PV) penetration in the grid poses …

A hybrid photovoltaic/wind power prediction model based on Time2Vec, WDCNN and BiLSTM

D Geng, B Wang, Q Gao - Energy conversion and management, 2023 - Elsevier
Accurate prediction of photovoltaic (PV)/wind power is an effective solution for the grid
stability, reasonable dispatching and power supply reliability. Nowadays, various deep …

[HTML][HTML] Metaheuristic-based hyperparameter tuning for recurrent deep learning: application to the prediction of solar energy generation

C Stoean, M Zivkovic, A Bozovic, N Bacanin… - Axioms, 2023 - mdpi.com
As solar energy generation has become more and more important for the economies of
numerous countries in the last couple of decades, it is highly important to build accurate …

Short-term photovoltaic power forecasting based on signal decomposition and machine learning optimization

Y Zhou, J Wang, Z Li, H Lu - Energy Conversion and Management, 2022 - Elsevier
Owing to the continuous increase in the proportion of solar generation accounting for the
total global generation, real-time management of solar power has become indispensable …