Enabling the Growth of Distributed Renewable Energy with Granular Net Load Forecasting
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00374528" target="_blank" >RIV/68407700:21230/24:00374528 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Enabling the Growth of Distributed Renewable Energy with Granular Net Load Forecasting
Original language description
The paper discusses the advancement of distributed renewable energy systems through the implementation of detailed net load forecasting. It emphasizes the use of artificial intelligence, machine learning, and data science to predict energy demands and optimize the integration of renewable sources into the power grid. The study highlights the significance of precise forecasting in enhancing the efficiency and reliability of energy distribution, contributing to a sustainable energy future.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů