Browsing by Subject "Net load forecasting"
Now showing items 1-4 of 4
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Conference Object
Direct Against Indirect Short-Term Net Load Forecasting Using Machine Learning Principles for Renewable Microgrids
(IEEE Xplore, 2023)Net load forecasting (NLF) is a key component for the efficient operation and management of microgrids at high shares of renewables. Depending on the forecasting strategy followed, NLF is classified as direct or indirect. ...
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Article
Direct Short-Term Net Load Forecasting Based on Machine Learning Principles for Solar-Integrated Microgrids
(IEEE, 2023)Accurate net load forecasting is a cost-effective technique, crucial for the planning, stability, reliability, and integration of variable solar photovoltaic (PV) systems in modern power systems. This work presents a direct ...
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Article
Direct short-term net load forecasting in renewable integrated microgrids using machine learning: a comparative assessment
(Elsevier, 2024)Modern microgrids require accurate net load forecasting (NLF) for optimal operation and management at high shares of renewable energy sources. Machine learning (ML) principles can be used to develop precise and reliable ...
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Article
Short-term electric net load forecasting for solar-integrated distribution systems based on Bayesian neural networks and statistical post-processing
(Elsevier, 2023)The increasing integration of variable renewable technologies at distribution feeders, mainly solar photovoltaic (PV) systems, presents new challenges to grid operators for accurately forecasting demand. This renders the ...