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Gaussian processes in power systems: Techniques, applications, and future works
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DOI：10.1016/j.apenergy.2025.126995.png)
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Abstract
En 中文
• A structured overview of Gaussian Process (GP) fundamentals and software ecosystems is provided. • Applications of GP in power systems, including load and renewable energy forecasting, power system static and dynamic modeling, risk assessment, and decision-making, are systematically reviewed. • Key challenges in applying GP to power systems, including issues of scalability and robustness, are thoroughly discussed. • Future research directions are outlined to facilitate the integration of GP with advanced data driven methods in energy systems.
Keywords:
Gaussian process
Power system dynamics learning
Power system optimization and control
Renewable energy and load forecasting
Risk assessment
Static power flow learning
Uncertainty quantification
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