POLITECNICO DI TORINO TRIBUTE and DIMMER DIMMER The

POLITECNICO DI TORINO TRIBUTE and DIMMER

DIMMER - The context • One of the major challenges in today’s economy concerns the reduction in energy usage and CO 2 footprint in existing public buildings and spaces without significant construction works • The concept of Smart City – The main idea is to make an intensive use of ICT to improve efficiency of energy utilization, renewable energy integration and comfort in cities through • • Smart grid (electricity/thermal) Smart mobility Smart communities Smart energy systems

DIMMER - Challenges • Challenges – Heterogeneous types of buildings • Special attention is paid to historical buildings, which are typically less energy efficient and impose tight deployment constraints to avoid damage by extensive retrofitting – Heterogeneous information systems and data sources – Promote pervasive usage of ICT through new business models • What we need: – Integration technologies – Information sharing – Interactive means (audio / video / AR / 3 D virtual models)

DIMMER – Smart City Information System • • • Smart devices Data collection system Information repository/models (e. g. BIM) Decision support system User awareness, profiling and social behavior analysis

DIMMER – From BIM to DIM • Bring information models from building level to district level – Building models – Distribution network models • Real time interaction/visualization – A/R – Q/R codes – Virtual district models

BUILDING LEVEL BIM PEOPLE LEVEL DISTRIC LEVEL Manchester DIM AR Turin

DIMMER - Outcome • District Information Model and Management for Energy Reduction – Monitor energy consumption, envirnomental parameters and energy production – Actuate energy relevant parameters at buildings (e. g. fan coils, lighting) and district level (water temperature in district heating) – Represent buildings and network in a virtual model with real-time data visualization – Optimize energy efficiency and promote local energy balancing exploting renewable energy – Promote user awareness through A/R – Social behavior analysis

Business Model Users Awareness EE Engine WEB QRCode Cost Algorithm BIM Simulation and Visualization Grid Ontology DB - Interoperability Middleware WSN DIM

District Heating Smart District Smart building Data cloud web-based Weather conditions Smart building Data are available by tablet and smart phone in AR using QR Code ENERGY BALANCING Smart building public private Smart building People move from house to work/school and vice versa Sensor node

TRIBUTE • As of today, building energy performance simulation tends to show large discrepancies with real energy performances during the building lifetime. – Building energy performance simulation tool tend to have difficulties in estimating these performances, while being very efficient during the building design phase. • TRIBUTE aims at proposing a novel approach for monitoring and assessing the building energy performance, at providing a comprehensive energy optimization at building level and a continuous estimation of the building state of health. • It will be based on adaptive and predictive techniques, while taking into account the inhabitant habits and needs. – Relying on this monitoring tool, a continuous energy flow optimization for the building will be proposed, to insure the best usage of available renewable energy sources. Inhabitant requirements and all type of energies will be included in the optimization scheme.

TRIBUTE • Based on a wireless sensor networks, building energy consumption will be monitored while external sensors, such as temperature and irradiance sensor will help establishing a prediction of renewable energy production. • The TRIBUTE smart sensor network (temperature, CO 2, occupancy, humidity, noise, and thermography) will be the base for the development of a selfadaptive building/occupancy building model that includes the inhabitant’s behaviour.

TRIBUTE • Deployed and demonstrated on three validation sites, in different climates and with different building use, the Haut. Bois system will help inhabitants to bring their house in line with European directives and will lead to recommendations for new certification standards. • As a summary, thanks to its adaptive behaviour, Haut. Bois will bring a reliable energy assessment in a reduced time and a building optimization tool, in which inhabitants will play a pivotal role.

TRIBUTE - Approach

TRIBUTE – Poli. TO Role • We can contribute to: – Design of the smart sensor network (make it energy-efficient and autonomous) – Design of middleware and web services for interoperation of heterogeneous sensors – Eventually contribute on predictive and adaptive model, especially for prediction of energy consumption, exploiting experience in embedded system energy estimation

TRIBUTE – Poli. TO Role • Runtime adaptation of monitoring parameters and sensor network configuration such as sample rate, number of active sensors based on the model needs – This has the purpose of improving energy efficiency and autonomy of the wireless sensor nodes, to avoid frequent battery replacement • Development of techniques to provide unlimited autonomy to wireless networks based on energy harvesters (e. g. PV cells) – This will increase the efficiency of monitoring and limit management costs • Development of middleware and web services to expose monitored parameters independently from HW characteristics (interoperability)