A review of deep learning for renewable energy forecasting
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 …
improving the accuracy of renewable energy forecasting is critical to power system planning …
A review on renewable energy and electricity requirement forecasting models for smart grid and buildings
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 …
pollution. Growing load requirement, global warming, and energy crisis need energy …
Prediction of solar energy guided by pearson correlation using machine learning
Solar energy forecasting represents a key element in increasing the competitiveness of solar
power plants in the energy market and reducing the dependence on fossil fuels in economic …
power plants in the energy market and reducing the dependence on fossil fuels in economic …
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 …
and scheduling of smart grid systems. Notably, volatility and intermittence of solar energy …
A hybrid deep learning model for short-term PV power forecasting
P Li, K Zhou, X Lu, S Yang - Applied Energy, 2020 - Elsevier
The integration of PV power brings great economic and environmental benefits. However,
the high penetration of PV power may challenge the planning and operation of the existing …
the high penetration of PV power may challenge the planning and operation of the existing …
[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 …
photovoltaic power generation (PVPG) is strongly weather-dependent, and thus highly …
A comparison of day-ahead photovoltaic power forecasting models based on deep learning neural network
K Wang, X Qi, H Liu - Applied Energy, 2019 - Elsevier
Accurate photovoltaic power forecasting is of great help to the operation of photovoltaic
power generation system. However, due to the instability, intermittence, and randomness of …
power generation system. However, due to the instability, intermittence, and randomness of …
Solar photovoltaic power forecasting: A review
KJ Iheanetu - Sustainability, 2022 - mdpi.com
The recent global warming effect has brought into focus different solutions for combating
climate change. The generation of climate-friendly renewable energy alternatives has been …
climate change. The generation of climate-friendly renewable energy alternatives has been …
Solar photovoltaic generation forecasting methods: A review
S Sobri, S Koohi-Kamali, NA Rahim - Energy conversion and management, 2018 - Elsevier
Solar photovoltaic plants are widely integrated into most countries worldwide. Due to the
ever-growing utilization of solar photovoltaic plants, either via grid-connection or stand …
ever-growing utilization of solar photovoltaic plants, either via grid-connection or stand …
A review on modeling of solar photovoltaic systems using artificial neural networks, fuzzy logic, genetic algorithm and hybrid models
The uncertainty associated with modeling and performance prediction of solar photovoltaic
systems could be easily and efficiently solved by artificial intelligence techniques. During the …
systems could be easily and efficiently solved by artificial intelligence techniques. During the …