A Data-Driven Forecasting Strategy to Predict Continuous Hourly Energy Demand in Smart Buildings

A Data-Driven Forecasting Strategy to Predict Continuous Hourly Energy Demand in Smart Buildings

Smart buildings seek to have a balance between energy consumption and occupant comfort. To make this possible, smart buildings need to be able to foresee sudden changes in the building’s energy consumption. With the help of forecasting models, building energy management systems, which are a fundamen...

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Bibliographic Details
Main Authors: Deyslen Mariano-Hernández, Luis Hernández-Callejo, Martín Solís, Angel Zorita-Lamadrid, Oscar Duque-Perez, Luis Gonzalez-Morales, Felix Santos-García
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Applied Sciences
Subjects:
forecasting models
energy consumption
multi-step forecasting
short-term forecasting
smart building
Online Access:https://www.mdpi.com/2076-3417/11/17/7886

Internet

https://www.mdpi.com/2076-3417/11/17/7886

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