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Reglamento de confort térmico de edificios mediante control predictivo basado en modelos: aumento del confort y reducción de los costes de explotación

Resumen

Tipo:
Oferta Tecnológica
Referencia:
TOCH20151126001
Publicado:
14/12/2015
Caducidad:
14/12/2016
Resumen:
Un centro privado suizo de I+D aplicada está estudiando el reglamento de instalaciones térmicas en edificios con algoritmos de control predictivo basados en modelos para controlar el rendimiento térmico de edificios y reducir los costes de explotación, mejorando el confort térmico del usuario. Se buscan investigadores especializados en calefacción/refrigeración urbana o que dispongan o preparen centros de ensayo con el fin de desplegar nuevas técnicas de optimización de energía en edificios para desarrollar el algoritmo y trabajar en la definición de confort.

Details

Tittle:
Building thermal comfort regulation using model predictive control: improved comfort for lower exploitation costs.
Summary:
A Swiss private applied R-Y-D center is studying thermal regulation in buildings, with model predictive control (MPC) algorithms to control the thermal behaviour of buildings to lower exploitation costs while improving user thermal comfort, e.g. for building retrofitting. Research partners involved in district heating/cooling or who own or prepare test sites for deployment of new building/district energy optimization techniques are sought to develop the algorithm, work on the comfort definition.
Description:
Reducing energy expenditure related to heating/cooling and ventilation (HVAC) activities while maintaining user comfort in buildings is a challenge. In order to achieve this task a novel algorithm need to be put in place. The later rely on model predictive control (MPC) and aim at regulating HVAC systems.

The core of the algorithm is an objective function that finds the optimal trade-off between:
· Energetic expenditure (or cost)
· User comfort

The objective function outputs the set-points of the controllable technical systems responsible of the thermal comfort regulation.
It is to be noted, that the objective function calls two distinct self-adaptive models:
1) The building thermal model: used to predict the building´s thermal behaviour
2) The technical system model: used to predict the energy (cost) related to the comfort regulation

The algorithmic knowledge was developed and strengthened under various National and European projects performed with a Swiss company.

The development and research goals are the following:
· Assess the algorithm under a wide range of scenarios
· Improve the algorithm robustness
· Work on the comfort definition used in the MPC
· Extending the work to district level (district heating/cooling)
· Include storage (daily / seasonal)

The sought research partners should thus either:
· be involved in district heating/cooling
· own or prepare test sites for the deployment of novel building/district energy optimization techniques
· be involved in heat storage

Advantages and Innovations:
Reducing energy expenditure and costs associated to HVAC activities is critical. Performing a deep retrofit is often beyond the available budget. In these conditions, replacing the existing regulator by a smart (model predictive controller) based controller is an interesting solution. Indeed, it only requires the installation of a reduced set of sensors and commissioning time is also reduced given the self-training capabilities of the used algorithms.

In summary the advantages of the proposed solution are:
· No complicated commissioning (configuration) is required (self training)
· User comfort is guaranteed
· Energy / cost is minimized
· No deep retrofit is required
· Minimal set of sensors to be installed
Stage of Development:
Field tested/evaluated
IPs:
Patents granted
CommeR Statunts Regarding IPR Status:
Patent granted EU.

Partner sought

Type and Role of Partner Sought:
The partner should have activity in the field of district heating, heat storage or building automation.

The tasks to be performed by the partner sought:
Provide relevant data to help the algorithmic development and enhancement. Deploy the control algorithms on test site and validate the results with the help of the R-Y-D center.

Client

Type and Size of Client:
R&D Institution
Already Engaged in Trans-National Cooperation:
No
Languages Spoken:
English
French
German

Keywords

Technology Keywords:
04001001 Almacenamiento de calor
004008 Energy efficiency
02006004 Installations related to construction (energy, lighting, …)
04002013 Redes inteligentes