[HTML][HTML] Building energy simulation and its application for building performance optimization: A review of methods, tools, and case studies

Y Pan, M Zhu, Y Lv, Y Yang, Y Liang, R Yin… - Advances in Applied …, 2023 - Elsevier
As one of the most important and advanced technology for carbon-mitigation in the building
sector, building performance simulation (BPS) has played an increasingly important role …

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 …

Prediction of energy production level in large PV plants through AUTO-encoder based neural-network (AUTO-NN) with restricted Boltzmann feature extraction

G Ramesh, J Logeshwaran, T Kiruthiga, J Lloret - Future Internet, 2023 - mdpi.com
In general, reliable PV generation prediction is required to increase complete control quality
and avoid potential damage. Accurate forecasting of direct solar radiation trends in PV …

[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 …

Multi-timescale photovoltaic power forecasting using an improved Stacking ensemble algorithm based LSTM-Informer model

Y Cao, G Liu, D Luo, DP Bavirisetti, G **ao - Energy, 2023 - Elsevier
As more and more photovoltaic (PV) systems are integrated into the grid, the intelligent
operation of the grid system is facing significant challenges. Therefore, accurately …

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 …

Dual stream network with attention mechanism for photovoltaic power forecasting

ZA Khan, T Hussain, SW Baik - Applied Energy, 2023 - Elsevier
The operations of renewable power generation systems highly depend on precise
Photovoltaic (PV) power forecasting, providing significant economic, and environmental …

[HTML][HTML] Machine learning for forecasting a photovoltaic (PV) generation system

C Scott, M Ahsan, A Albarbar - Energy, 2023 - Elsevier
To mitigate the carbon print of buildings, they should have on-site renewable energy
generation systems to supply energy for the buildings without relying on the national grid …

An analysis of case studies for advancing photovoltaic power forecasting through multi-scale fusion techniques

M Guermoui, A Fezzani, Z Mohamed, A Rabehi… - Scientific Reports, 2024 - nature.com
Integration renewable energy sources into current power generation systems necessitates
accurate forecasting to optimize and preserve supply–demand restrictions in the electrical …

Short-term photovoltaic power forecasting using an LSTM neural network and synthetic weather forecast

MS Hossain, H Mahmood - Ieee Access, 2020 - ieeexplore.ieee.org
In this paper, a forecasting algorithm is proposed to predict photovoltaic (PV) power
generation using a long short term memory (LSTM) neural network (NN). A synthetic …