IoT software infrastructure for Energy Management and Simulation in Smart Cities
Abstract:
This paper presents an IoT software infrastructure that enables energy management and simulation of new control policies in a city district. The proposed platform enables the interoperability and the correlation of (near-)real-time building energy profiles with environmental data from sensors as well as building and grid models. In a smart city context, this platform fulfills i) the integration of heterogeneous data sources at building and district level, and ii) the simulation of novel energy policies at district level aimed at the optimization of the energy usage accounting also for its impact on building comfort. The platform has been deployed in a real world district and a novel control policy for the heating distribution network has been developed and tested. Results are presented and discussed in the paper.
Existing System:
Another relevant impact of IoT is the ease of integration of heterogeneous data sources that can be exploited to develop smarter policies. In this way, sensor data can be integrated with Building Information Models (BIMs) [4], grid models and Geographical Information Systems (GISs) [5]. BIMs are 3D models with construction and energy characteristics and they allow detailed energy simulations, that can be used to evaluate the impact of thermal reshaping on indoor air temperature. From the other side, building simulations can be compared with temperatures provided by indoor sensors to tune energy models, that can be used to evaluate policy impact on buildings where environmental sensors are not deployed. In the last decade, several frameworks have been proposed to exploit IoT technologies at building and house level [6] [7] [8], and software solutions have been proposed to enable interoperability a various data formats and protocols [9] [10] [11]. However, the integration of district models with sensor data remains a challenge.
Proposed System:
In a Smart Grid context, Kim et al. [13] presented a datacentric middleware to allow decentralized monitoring and control, exploiting a publish/subscribe model [14], which is appropriate for delivering information but is not yet sufficient to have data access that is independent of this model. Indeed, the request/response communication approach is also needed to provide novel services that can easily retrieve data without having to wait for new events. In [15], a distributed software infrastructure for general purpose services in power systems is presented. The software architecture enables the interoperability across heterogeneous devices by creating a secure peer-to-per network. Differently from these solutions, the IoT platform presented in this paper aims at creating a virtual model of a city district for providing Smart City services. Hence, considering data coming from IoT devices deployed across the energy distribution networks is not yet enough. Indeed, such data have to be integrated and correlated together with information, often geo-referenced, about buildings.
Conclusion:
This work presented a novel IoT platform for city district data management and energy flow simulations. In particular, this platform is instrumental i) to integrate heterogeneous IoT devices for monitoring and management of a whole city district; ii) to share building and energy network resources, both for visualization and simulation of energy policies, at building and district level; and iii) to assess the quality of the energy model of buildings. The presented platform is designed and developed following the micro-service paradigm, and it is able to scale up reliably. Further, the use of shared open standards of the Web makes it easy to integrate into existing systems. The platform is ready to send actuation commands to the devices deployed in the district. For instance, we are currently testing it on the DH scheduling control system. In this case, scheduled on-off heating switching times are sent to IoT devices to control heat exchangers. The results of this experimentation are preliminary and will be discussed in future work.
References:
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