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A Comprehensive Review on Ensemble Solar Power Forecasting Algorithms. [PDF]
J Electr Eng Technol, 2023 With increasing demand for energy, the penetration of alternative sources such as renewable energy in power grids has increased. Solar energy is one of the most common and well-known sources of energy in existing networks.
Rahimi N +10 more
europepmc +2 more sources
Machine learning-based energy management and power forecasting in grid-connected microgrids with multiple distributed energy sources. [PDF]
Sci RepThe growing integration of renewable energy sources into grid-connected microgrids has created new challenges in power generation forecasting and energy management. This paper explores the use of advanced machine learning algorithms, specifically Support
R Singh A +4 more
europepmc +2 more sources
Transfer learning strategies for solar power forecasting under data scarcity. [PDF]
Sci Rep, 2022 Accurately forecasting solar plants production is critical for balancing supply and demand and for scheduling distribution networks operation in the context of inclusive smart cities and energy communities.
Sarmas E +4 more
europepmc +2 more sources
Machine Learning Based Solar Photovoltaic Power Forecasting: A Review and Comparison
IEEE Access, 2023 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 intermittent renewable energy introduces challenges and the potential to ...
Jwaone Gaboitaolelwe +5 more
semanticscholar +3 more sources
Wind Power Forecasting Considering Data Privacy Protection: A Federated Deep Reinforcement Learning Approach [PDF]
Applied Energy, 2022 In a modern power system with an increasing proportion of renewable energy, wind power prediction is crucial to the arrangement of power grid dispatching plans due to the volatility of wind power.
Yang Li +4 more
semanticscholar +1 more source
Solar Photovoltaic Power Forecasting [PDF]
Journal of Electrical and Computer Engineering, 2020 The management of clean energy is usually the key for environmental, economic, and sustainable developments. In the meantime, the energy management system (EMS) ensures the clean energy which includes many sources grouped in a small power plant such as microgrid (MG). In this case, the forecasting methods are used for helping the EMS and allow the high
Abdelhakim El hendouzi +1 more
openaire +3 more sources
Wind power forecasting – A data-driven method along with gated recurrent neural network
, 2021 Effective wind power prediction will facilitate the world’s long-term goal in sustainable development. However, a drawback of wind as an energy source lies in its high variability, resulting in a challenging study in wind power forecasting. To solve this
Adam Kisvari, Zi Lin, Xiaolei Liu
semanticscholar +1 more source
An Interpretable Probabilistic Model for Short-Term Solar Power Forecasting Using Natural Gradient Boosting [PDF]
Applied Energy, 2021 —PV power forecasting models are predominantly based on machine learning algorithms which do not provide any insight into or explanation about their predictions (black boxes).
Georgios Mitrentsis, H. Lens
semanticscholar +1 more source
Energy Science & Engineering, 2022 Solar photovoltaic (PV) power is emerging as one of the most viable renewable energy sources. The recent enhancements in the integration of renewable energy sources into the power grid create a dire need for reliable solar power forecasting techniques ...
Jatin Sharma +7 more
semanticscholar +1 more source
, 2021 The wind power generation depends on wind speed and its derivatives like: wind speed and direction. With consideration of stochastic nature of wind power, this work addresses three main issues: first, it discusses the state of art of energy forecasting with emphasis on wind power forecasting. It provides an overview of different variables on which wind
Sumit, Saroha, +2 more
openaire +3 more sources