Prescient building Operation utilizing Real Time data for Energy Dynamic Optimization

Project Details

Description

Solutions are needed to address building operation inefficiencies holistically, considering the energy consumption, fossil fuel dependency and CO2 footprint, but also the wellbeing and economy dimensions. The PRELUDE project is focused on balancing these aspects of building operation, minimizing energy consumption based on a free-running strategy, maximizing self-consumption and RES utilization, while maintaining comfortable and healthy conditions. The approach is technology-neutral, scalable from individual building to district level and can be applied across any location, typology and smartness level. In PRELUDE, residential buildings will operate dynamically, capable of demand response and flexibility, regardless of pre-existing infrastructure. In line with the need to increase renovation rates and RES penetration in the residential building stock and enabled by powerful assessment and prediction tools, PRELUDE will provide the user (occupant/ tenant, owner/ managerand service provider) with clear and pertinent technoeconomic information to make the actions and the right investments at the right time.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement N° 958345.
Call identifier: LC-EEB-07-2020.
Short titlePRELUDE
AcronymPRELUDE
StatusActive
Effective start/end date01/12/202031/05/2024

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 11 - Sustainable Cities and Communities
  • SDG 12 - Responsible Consumption and Production
  • SDG 13 - Climate Action

Keywords

  • building self assessment
  • decision support system
  • data acquisition
  • predictive maintenance
  • smart heat meters
  • big data
  • energy optimization

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