DIMCloud: a distributed framework for district energy simulation and management

To optimize energy consumption, it is needed to monitor real-time data and simulate all energy flows. In a city district context, energy consumption data usually come from many sources and encoded in different formats. However, few models have been proposed to trace the energy behavior of city districts and handle related data. In this article, we introduce DIMCloud, a model for heterogeneous data management and integration at district level, in a pervasive computing context. Our model, by means of an ontology, is able to register the relationships between different data sources of the district and to disclose the sources locations using a publish-subscribe design pattern. Furthermore, data sources are published as Web Services, abstracting the underlying hardware from the user’s point-of-view

A new distributed framework for integration of district energy data from heterogeneous devices

The introduction of ”smart” low-cost sensing (and actuating) devices enabled the recent diffusion of technological products within the ”Internet of Things” paradigm. In a city district context, such devices are crucial for visualization and simulation of energy consumption trends, to increase the energy distribution network efficiency and promote user awareness. Nevertheless, to unlock the potential of this technology, many challenges have to be faced at district level due to the current lack of interoperability between heterogeneous data sources. In this work, we introduce an original infrastructure model, which efficiently manage and integrate district energy data

IoT software infrastructure for Energy Management and Simulation in Smart Cities

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

Distributed service infrastructure for monitoring, management and simulation in Smart Cities

World’s energy consumption concentrates within our cities, due to an irreversible urbanisation process. At the same time, insufficient and uncoordinated efforts try to cope with the challenges of urban energy efficiency optimisation. New tailored control policies should be designed for our energy distribution networks. However, to address this task it is necessary to model different entities of our cities (e.g. buildings and energy distribution networks). For instance, in the case of district heating optimisation, the physical model of the district thermal behaviour takes as inputs building energy profiles and signatures, together with information about the district heating network (i.e. network topology and structural attributes). A good description of the actual district entities is instrumental to correctly design and simulate new energy optimisation policies. In addition, novel policies can only be monitored and validated by retrieving information on the actual district energy consumption. This information is extracted by deploying distributed online technologies directly on the eld, to sense and actuate control commands on energy network endpoints. Recently, the introduction of Internet-of-Things technologies generated new business opportunities for the different competitors in the Smart City market. Following the patterns described in the Adjacent Possible theory for innovation, they enabled the deployment of fine-grained monitoring and control policies for public and private spaces (e.g. buildings). The pervasive nature of IoT technologies allows for a new vision of computing, where devices collect data and fade in the background of our environments, and ambient intelligence unifies user awareness on energy consumption and comfort impact of energy optimisation policies. IoT technologies are increasingly adopted because they are versatile and cheap. Thanks to their network capabilities they can be integrated into comprehensive infrastructures. In the last decades, the Smart City community presented different solutions to provide smart environments, mostly used to build energy-aware houses. Some of the challenges which need to be addressed are related to technology interoperability. Indeed, most of the technologies that have been introduced in the market are difficult to integrate due to proprietary communication protocols and data formats. In addition, the extension of current solutions to the district level is not feasible, because they do not consider additional data sources (e.g. Geographical Information Systems) which are needed for the optimal modelling of city districts. Recent literature approaches the definition of an infrastructure for energy management at the district level. Currently, state-of-art does not include such an infrastructure. This work proposes a city district IoT-enabled software infrastructure for energy monitoring, management and simulation. Its purpose is to collect, process and analyse heterogeneous kinds of data. This infrastructure integrates and correlates historical energy consumption with structural features of the different entities of the district (e.g. buildings or energy distribution networks). IoT devices are first-class citizens and they are integrated by using open standards of the Web (i.e. Web Services). The different information models, of the entities which belong to the district, are exposed as a single and consistent District Information Model (DIM). The main challenges addressed by this infrastructure are: • The transparent integration of heterogeneous IoT devices and district level information sources; • The definition of a uniform Web Service-oriented interface across all components of the infrastructure. The contribution of this infrastructure to the state-of-art consists of: • A single platform to integrate and correlate all the different components be- tween each other and with environmental sensors of a city district information model; • A framework for district energy management and optimisation policies simulation. To assess the relevance of the presented infrastructure, two applications which exploit the transparent integration of district information are presented. These two applications retrieve structural and parametric data from the different information models (e.g. geographical maps or building models). Information is then presented to different stakeholders for building benchmarking or energy consumption monitoring of the district. In addition, we designed a case study to test the simulation capabilities of the infrastructure. In this case study, it is depicted how to develop a novel energy peak smoothing policy for a district heating network, and how to validate it both at the district and at the building level. At the district level, it is possible to estimate the reduction of primary energy usage for the energy provider, while at building level the simulation framework assesses the comfort impact for the building’s inhabitants

La gestione dei dati attraverso dei proxy ed un middleware

none4noBIM - GIS - AR per il FM (Facility Management) raccoglie in un libro ben tre anni di ricerca sia teorica sia pratica basata su un peculiare metodo di lavoro, quello interdisciplinare, che fonda le sue origini nell'essenziale concetto per cui conoscere è la premessa per gestire. Il mondo delle costruzioni è costantemente alla ricerca di nuovi modi per aumentare l'efficienza e la produttività e questo volume è stato realizzato proprio con questo obiettivo. A partire dai concetti essenziali del Building Information Model/Modelling, del Geographic Information System e della Augmented Reality (realtà aumentata) come strumenti e metodi a servizio del Facility Management BIM - GIS - AR per il FM riporta gli argomenti trattati da diversi autori, sotto forma di domanda e risposta, nell'ambito di tali tre aree tematiche. Facility Management - BIM - GIS - AR per ottimizzare i processi [readmore]Questa struttura ha lo scopo di aiutare il lettore a individuare facilmente quelle di proprio interesse e di trovare, al tempo stesso, la soluzione a problematiche specifiche. Il libro si conclude con un capitolo dedicato al tema dell'interoperabilità per porre l'accento su come non sia sufficiente avere a disposizione degli strumenti interoperabili utili allo scambio dei dati, piuttosto come sia essenziale che ogni professionista che debba utilizzare questi dati abbia la consapevolezza di poterlo fare e possieda le competenze per farlo. Il libro dedicato al Facility Management con BIM, GIS e AR si rivolge ai docenti che desiderano proporre nuovi argomenti di studio; agli studenti delle Facoltà di Ingegneria e di Architettura appassionati di tecnologia digitale; ai ricercatori, ai professionisti e agli operatori del mondo dell'edilizia che vogliono innovare il proprio modo di operare; ai gestori e/o proprietari di grandi patrimoni immobiliari, e in generale a tutte quelle persone che nel lavoro collaborativo basato sul concetto di interoperabilità possono trovare o vogliono cercare delle opportunità per ottimizzare dei processi.noneBRUNDU, FRANCESCO GAVINO; PATTI, EDOARDO; ACQUAVIVA, ANDREA; MACII, EnricoBRUNDU, FRANCESCO GAVINO; PATTI, EDOARDO; ACQUAVIVA, ANDREA; MACII, Enric

Optimization of the thermal profiles of buildings connected with a large district heating network.

Thermal storage is very important in modern district heating networks in order to increase the share of waste heat and heat produced through renewable sources and cogeneration. The role of thermal storage is even more important in the case of Mediterranean areas, where climate and user behavior cause high peak requests in the morning. Nevertheless the installation of large storage volumes is not always feasible, especially in dense urban areas, therefore alternative options are investigated. One of these options is virtual storage. This consists in proposing changes to the thermal request profiles of some of the connected buildings, in order to obtain a peak shaving, which is an effect similar to that obtained using storage. To perform such approach there are two crucial elements: 1) an advanced ICT solution able provide real time information about the thermal request of the buildings and the thermodynamic conditions at the thermal substations; 2) a detailed thermo fluid-dynamic model of the district heating network able to simulate the temperature evolution along the network as the function of time. Using physical models it is possible to examine the effects, obtained by modifying the thermal request of users, on the total load of the thermal plants feeding the network. In particular, the model is applied to the analysis of changes in the start-up time of the buildings as well as possible pauses during the day. The start-up strategy should not produce significant effects on the building temperatures, so that acceptable comfort standard can be guaranteed. This is checked using a compact model of the buildings which parameters are obtained through data measured at the thermal substations. These changes in the request profiles usually involve a larger heat request. Nevertheless, peak shaving is accompanied by a reduction in heat generation of boilers and an increase in the thermal production of efficient systems, such as cogeneration units. This results in a significant reduction in the primary energy consumption. The goal of the analysis is to find the optimal start-up strategy in order to minimize the primary energy consumption at the thermal plants. An application to the Turin district heating network, which is the largest network in Italy, is presented. In particular, a subnetwork connecting the main transport network to about 100 buildings located in the central area of the town is considered. The analysis if performed in selected days where the optimization was conducted the day before on the basis of weather forecasts and then applied to the network. Despite the changes in the request profiles could be applied only to a limited number of buildings, the analysis show that the peak request can be reduced. Simulations performed considering the application of changes to a larger number of buildings show that reduction in the primary energy consumptions of the order of 1.25% can be obtained

Optimization of the thermal profiles of buildings connected with a large district heating network

Thermal storage is very important in modern district heating networks in order to increase the share of waste heat and heat produced through renewable sources and cogeneration. The role of thermal storage is even more important in the case of Mediterranean areas, where climate and user behavior cause high peak requests in the morning. Nevertheless the installation of large storage volumes is not always feasible, especially in dense urban areas, therefore alternative options are investigated. One of these options is virtual storage. This consists in proposing changes to the thermal request profiles of some of the connected buildings, in order to obtain a peak shaving, which is an effect similar to that obtained using storage. To perform such approach there are two crucial elements: 1) an advanced ICT solution able provide real time information about the thermal request of the buildings and the thermodynamic conditions at the thermal substations; 2) a detailed thermo fluid-dynamic model of the district heating network able to simulate the temperature evolution along the network as the function of time. Using physical models it is possible to examine the effects, obtained by modifying the thermal request of users, on the total load of the thermal plants feeding the network. In particular, the model is applied to the analysis of changes in the start-up time of the buildings as well as possible pauses during the day. The start-up strategy should not produce significant effects on the building temperatures, so that acceptable comfort standard can be guaranteed. This is checked using a compact model of the buildings which parameters are obtained through data measured at the thermal substations. These changes in the request profiles usually involve a larger heat request. Nevertheless, peak shaving is accompanied by a reduction in heat generation of boilers and an increase in the thermal production of efficient systems, such as cogeneration units. This results in a significant reduction in the primary energy consumption. The goal of the analysis is to find the optimal start-up strategy in order to minimize the primary energy consumption at the thermal plants. An application to the Turin district heating network, which is the largest network in Italy, is presented. In particular, a subnetwork connecting the main transport network to about 100 buildings located in the central area of the town is considered. The analysis if performed in selected days where the optimization was conducted the day before on the basis of weather forecasts and then applied to the network. Despite the changes in the request profiles could be applied only to a limited number of buildings, the analysis show that the peak request can be reduced. Simulations performed considering the application of changes to a larger number of buildings show that reduction in the primary energy consumptions of the order of 1.25% can be obtained