The application of Information and Communications Technologies (ICT) is a key element to increase the energy efficiency of buildings and districts. With ICTs it is possible to monitor the entire energy transfer between producer and consumer, to profile end users and to promote their awareness with regards to their energy consumption. For instance, advanced visualization technologies, such as Augmented Reality, can provide a real-time feedback to users about their energy use behaviors. Moreover, statistical analyses on population energy profiles will allow energy providers to better schedule the energy distribution at different timings, to increase demand response. Finally, environmental conditions and user feedback data will have a direct role to lead the autonomous control of energy use at the district, building, or even at the apartment level. Unfortunately, to build a coherent information system is often more difficult than to collect and analyze data. Indeed, the main components of such infrastructure are usually difficult to integrate together, because they can be realized with heterogeneous technologies. Furthermore, data format is often specific to each platform and often it is not portable. Moreover, data can be stored using different technologies and it can be maintained in different locations. In this scenario, the lack of an unifying paradigm is a major issue and enabling the interoperability between heterogeneous technologies is the key challenge. The proposed District Information Model Cloud (DIMCloud) is a distributed infrastructure, which targets to make a cloud digital archive for energy management in the district. The whole DIMCloud exploits a service-oriented middleware approach to enable the interoperability across heterogeneous hardware and software technologies. It aims to collect environmental information coming from pervasive and heterogeneous systems deployed in buildings and energy distribution networks in the district. Internet-of-things devices play a key role in this framework, enabling the collection of fine-grained environmental information. To be effective in the specific application, a number of requirements must be accounted for, such as network reliability and self-configuration, wireless transmission range, band regulations compliancy and low energy consumption. In addition, DIMCloud shares georeferenced structural characteristics and parameters about both buildings (BIM) and energy distribution networks providing also their virtual models. It offers a web query interface, where data of a specific district, building or device can be retrieved, and experimental low-energy sensor networks. Subsequently, data is provided encoded in JSON, a human-readable semistructured data format. Finally, this information can be accessed and exploited to: i) profile the energy consumption from the district point of view down to the single building; ii) design more efficient control policies; iii) increase energy user awareness.

DIMCloud – a distributed infrastructure for district energy management / Brundu, FRANCESCO GAVINO; Patti, Edoardo; Acquaviva, Andrea; Grosso, Michelangelo; Gaetano, Rasconà; Davide, Lena; Salvatore, Rinaudo; Ronzino, Amos; Osello, Anna; Macii, Enrico. - STAMPA. - (2014). ((Intervento presentato al convegno European Technology Platform on Smart Systems Integration (EPoSS 2014) tenutosi a Torino, Italy nel September, 24-26th 2014 [10.1007/978-3-319-19656-5_45].

DIMCloud – a distributed infrastructure for district energy management

BRUNDU, FRANCESCO GAVINO;PATTI, EDOARDO;ACQUAVIVA, ANDREA;GROSSO, MICHELANGELO;RONZINO, AMOS;OSELLO, Anna;MACII, Enrico
2014

Abstract

The application of Information and Communications Technologies (ICT) is a key element to increase the energy efficiency of buildings and districts. With ICTs it is possible to monitor the entire energy transfer between producer and consumer, to profile end users and to promote their awareness with regards to their energy consumption. For instance, advanced visualization technologies, such as Augmented Reality, can provide a real-time feedback to users about their energy use behaviors. Moreover, statistical analyses on population energy profiles will allow energy providers to better schedule the energy distribution at different timings, to increase demand response. Finally, environmental conditions and user feedback data will have a direct role to lead the autonomous control of energy use at the district, building, or even at the apartment level. Unfortunately, to build a coherent information system is often more difficult than to collect and analyze data. Indeed, the main components of such infrastructure are usually difficult to integrate together, because they can be realized with heterogeneous technologies. Furthermore, data format is often specific to each platform and often it is not portable. Moreover, data can be stored using different technologies and it can be maintained in different locations. In this scenario, the lack of an unifying paradigm is a major issue and enabling the interoperability between heterogeneous technologies is the key challenge. The proposed District Information Model Cloud (DIMCloud) is a distributed infrastructure, which targets to make a cloud digital archive for energy management in the district. The whole DIMCloud exploits a service-oriented middleware approach to enable the interoperability across heterogeneous hardware and software technologies. It aims to collect environmental information coming from pervasive and heterogeneous systems deployed in buildings and energy distribution networks in the district. Internet-of-things devices play a key role in this framework, enabling the collection of fine-grained environmental information. To be effective in the specific application, a number of requirements must be accounted for, such as network reliability and self-configuration, wireless transmission range, band regulations compliancy and low energy consumption. In addition, DIMCloud shares georeferenced structural characteristics and parameters about both buildings (BIM) and energy distribution networks providing also their virtual models. It offers a web query interface, where data of a specific district, building or device can be retrieved, and experimental low-energy sensor networks. Subsequently, data is provided encoded in JSON, a human-readable semistructured data format. Finally, this information can be accessed and exploited to: i) profile the energy consumption from the district point of view down to the single building; ii) design more efficient control policies; iii) increase energy user awareness.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2565756
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