A systematic review of statistical and machine learning methods for electrical power forecasting with reported mape score
Electric power forecasting plays a substantial role in the administration and balance of
current power systems. For this reason, accurate predictions of service demands are needed …
current power systems. For this reason, accurate predictions of service demands are needed …
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 …
An integrated framework of gated recurrent unit based on improved sine cosine algorithm for photovoltaic power forecasting
H Ma, C Zhang, T Peng, MS Nazir, Y Li - Energy, 2022 - Elsevier
Accurate prediction of photovoltaic power is of great significance to the storage and
utilization of solar power. In this research, a deep learning model for photovoltaic power …
utilization of solar power. In this research, a deep learning model for photovoltaic power …
A framework of using machine learning approaches for short-term solar power forecasting
Various machine learning approaches are widely applied for short-term solar power
forecasting, which is highly demanded for renewable energy integration and power system …
forecasting, which is highly demanded for renewable energy integration and power system …
Deep neural networks for multivariate prediction of photovoltaic power time series
The large-scale penetration of renewable energy sources is forcing the transition towards
the future electricity networks modeled on the smart grid paradigm, where energy clusters …
the future electricity networks modeled on the smart grid paradigm, where energy clusters …
Machine learning algorithms in forecasting of photovoltaic power generation
Due to the intrinsic intermittency and stochastic nature of solar power, accurate forecasting
of the photovoltaic (PV) generation is crucial for the operation and planning of PV-intensive …
of the photovoltaic (PV) generation is crucial for the operation and planning of PV-intensive …
Research Progress of Photovoltaic Power Prediction Technology Based on Artificial Intelligence Methods.
D Zhou, Y Liu, X Wang, F Wang, Y Jia - Energy Engineering, 2024 - search.ebscohost.com
With the increasing proportion of renewable energy in China's energy structure, among
which photovoltaic power generation is also develo** rapidly. As the photovoltaic (PV) …
which photovoltaic power generation is also develo** rapidly. As the photovoltaic (PV) …
[HTML][HTML] A comparative study of machine learning approaches for an accurate predictive modeling of solar energy generation
AK Chaaban, N Alfadl - Energy Reports, 2024 - Elsevier
Solar energy prediction poses a challenging task that necessitates robust models and
precise data to accurately forecast solar energy yield, especially in grid areas with high …
precise data to accurately forecast solar energy yield, especially in grid areas with high …
Cloud cover forecast based on correlation analysis on satellite images for short-term photovoltaic power forecasting
Y Son, Y Yoon, J Cho, S Choi - Sustainability, 2022 - mdpi.com
Photovoltaic power generation must be predicted to counter the system instability caused by
an increasing number of photovoltaic power-plant connections. In this study, a method for …
an increasing number of photovoltaic power-plant connections. In this study, a method for …
Machine learning modeling of horizontal photovoltaics using weather and location data
Solar energy is a key renewable energy source; however, its intermittent nature and
potential for use in distributed systems make power prediction an important aspect of grid …
potential for use in distributed systems make power prediction an important aspect of grid …