SMPCBCSG

"Stochastic Model Predictive Control, Energy Efficient Building Control, Smart Grid"

 Coordinatore EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZURICH 

 Organization address address: Raemistrasse 101
city: ZUERICH
postcode: 8092

contact info
Titolo: Prof.
Nome: Manfred
Cognome: Morari
Email: send email
Telefono: +41 44 632 76 26
Fax: +41 44 632 1211

 Nazionalità Coordinatore Switzerland [CH]
 Totale costo 178˙233 €
 EC contributo 178˙233 €
 Programma FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call FP7-PEOPLE-2011-IOF
 Funding Scheme MC-IOF
 Anno di inizio 2014
 Periodo (anno-mese-giorno) 2014-03-01   -   2016-02-29

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZURICH

 Organization address address: Raemistrasse 101
city: ZUERICH
postcode: 8092

contact info
Titolo: Prof.
Nome: Manfred
Cognome: Morari
Email: send email
Telefono: +41 44 632 76 26
Fax: +41 44 632 1211

CH (ZUERICH) coordinator 178˙233.60

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

efficient    storage    berkeley    predictions    supervision    tractable    additional    buildings    power    prof    stochastic    energy    formulation    mpc   

 Obiettivo del progetto (Objective)

'Energy efficient building control can have a major impact on reducing the overall energy consumption since a large part of today's energy is consumed in buildings. The use of model predictive control (MPC) together with weather and occupancy predictions is a promising approach to realize significant energy savings.

The control of power grids is of major concern due to the increasing number of renewable energy sources which introduce additional variability. This can be mitigated against by making use of additional storage, e.g. by leveraging the thermal energy storage of buildings.

These areas demand for advanced and novel control solutions, which can handle uncertainty, large-scale systems, distributed systems, and predictions of the future system behavior. The aim is to use recent advances in random convex programming, couple these to MPC and develop a novel stochastic MPC formulation that is tractable for large-scale systems.

The key objectives of this project are: - Development of stochastic MPC strategies, which address the above challenges. - Development, implementation and testing of a new energy efficient control strategy for buildings on a test-bed at UC Berkeley. - Formulation of tractable dynamic power flow problems involving a stochastic formulation and including buildings as additional storage in the formulation.

The project is designed as a structured two-year program, where the first year is carried out at the University of California, Berkeley under supervision of Prof. Tomlin and the second year is carried out at the Swiss Federal Institute of Technology Zurich under supervision of Prof. Morari.

The project will provide the fellow with excellent opportunities to further develop her competences and skills. Furthermore, it will strengthen the collaboration and establish a research network between the two hosts and contribute to Europe's excellence and competitiveness.'

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PREDICTING INFANTS (2014)

Infants predicting own and others’ actions: the neurocognitive development of action prediction

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GASTIME (2012)

GAS SEEPS AND SUBMARINE SLIDES IN THE EASTERN MEDITERRANEAN: TOWARD COMPREHENSIVE GEOHAZARD PREVENTION

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FLUMVI (2013)

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