progetto Predict

ADAPTIVE ENERGY EFFICIENCY PLATFORM FOR THE REDUCTION OF CONSUMPTION IN NON-RESIDENTIAL BUILDINGS

Energy efficiency in buildings is one of the most important challenges for energy savings in the EU and, at the same time, offers a business opportunity in the Green Economy context.In particular, energy demand in non-residential buildings is growing fast, and it is crucial to reduce the consumption to achieve considerable impact on the energy consumption in the EU.

THE PROJECT

The saving potential depends on several factors and, in general, the higher the saving the higher the cost of the efficiency intervention.

Higher saving requires substantial structural improvements (e.g. external envelope, window renewal, new HVAC equipment of renewable energy source installation). They require high investment (CAPEX) which may not be affordable or may require a long payback period.

Valuable savings can be achieved with less expensive operational optimisation anyway. According to literature operational optimisation may produce 10-12% savings.

PREDICT project will deliver and demonstrate an intelligent energy management platform to reduce building energy consumption in an enduring and reliable way.

PREDICT proactively supports managers to reach the efficiency objectives by providing automatic and semi-automatic tool for energy optimization and self-analysis and predictive control.

PREDICT discovers, fine tune and actuate data driven “personalized” optimization energy usage strategies taking into account, and interacting with, the many influencing elements in the context of the building (building usage, weather conditions, occupants’ behaviors, variable energy costs,…) and targeting the building life cycle.

To meet the technical challenge, PREDICT provides a comprehensive approach to energy auditing, usage optimisation and control over the long period and supports building management decision making driven by data and real performance assessment.

CONSORTIUM

An established research group with a renowned academic and industrial profile.

  • algoWatt SpA (IT)
  • IEsolutions (IT)
  • Collaboration with University of Genoa – DITEN (Department of Telecommunication, Naval and Electric Engineering) (IT)
  • H2BOAT (IT)

SYNOPSIS

COORDINATOR

algoWatt SpA

PROGRAMME

POR 2014-2020 Regione Liguria Asse 1 “RICERCA E INNOVAZIONE “Azione 1.2.4 “Supporto alla realizzazione di progetti complessi di attività di ricerca e sviluppo

START DATE

February 2017

DURATION

24 months

GALLERY