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Edoardo Patti

Politecnico di Torino, Department of Control and Computer Engineering, Post-Doc

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Edoardo Patti received the B.Sc. and M.Sc. degree in Computer Engineering from University of Palermo in 2007 and Politecnico di Torino in 2010 respectively. Since January 2011 he is with the Department of Control and Computer Engineering at Politecnico di Torino as Ph.D. student first and then as Postdoctoral Research Fellow. During the Academic Year 2014/2015, he was Academic Visiting at the University of Manchester. He is also involved in various European funded projects focused on Smart City. His research interests concern: i) Ubiquitous Computing; ii) Internet of Things; iii) Smart Systems and Cities; iv) Software architectures with particular emphasis on Service Oriented Architectures for Ambient Intelligence and for enabling the interoperability across heterogeneous data-sources (both hardware and software); v) Software solutions for simulating and optimizing energy demand response; vi) Software solutions for energy data visualization for increasing user awareness.

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Papers by Edoardo Patti

A Cloud-based On-line Disaggregation Algorithm for Home Appliance Loads

In this work, we address the problem of providing fast and on-line households appliance load dete... more In this work, we address the problem of providing fast and on-line households appliance load detection in a non-intrusive way from aggregate electric energy consumption data. Enabling on-line load detection is a relevant research problem as it can unlock new grid services such as demand-side management and raises interactivity in energy awareness possibly leading to more green behaviours. To this purpose, we propose an On-line-NILM (Non-Intrusive Load Monitoring) machine learning algorithm combining two methodologies: i) Unsupervised event-based profiling and ii) Markov chain appliance load modelling. The event-based part performs event detection through contiguous and transient data segments, events clustering and matching. The resulting features are used to build household-specific appliance models from generic appliance models. Disaggregation is then performed on-line using an Additive Factorial Hidden Markov Model from the generated appliance model parameters. Our solution is implemented on the cloud and tested with public benchmark datasets. Accuracy results are presented and compared with literature solutions, showing that the proposed solution achieves on-line detection with comparable detection performance with respect to non on-line approaches.

A Distributed IoT Infrastructure to Test and Deploy Real-Time Demand Response in Smart Grids

by Edoardo Patti and Abouzar Estebsari

In this paper, we present a novel distributed framework for real time management and co-simulatio... more In this paper, we present a novel distributed framework for real time management and co-simulation of Demand Response (DR) in smart grids. Our solution provides a (near-) real-time co-simulation platform to validate new DR-policies exploiting Internet-of-Things approach performing software-in-the-loop. Hence, the behavior of real-world power systems can be emulated in a very realistic way and different DR-policies can be easily deployed and/or replaced in a plug-and-play fashion, without affecting the rest of the framework. In addition, our solution integrates real internet-connected smart devices deployed at customer premises and along the Smart Grid to retrieve energy information and send actuation commands. Thus, the framework is also ready to manage DR in a real-world Smart Grid. This is demonstrated on a realistic smart grid with a test case DR-policy.

A Novel Internet-of-Things Infrastructure to Support Self-Healing Distribution Systems

by Edoardo Patti and Abouzar Estebsari

In this paper, we present a novel distributed software infrastructure to foster new services in s... more In this paper, we present a novel distributed software infrastructure to foster new services in smart grids with particular emphasis on supporting self-healing distribution systems. This infrastructure exploits the rising Internet-of-Things paradigms to build and manage an interoperable peer-to-peer network of our prototype smart meters, also presented in this paper. The proposed three-phase smart meter, called 3-SMA, is a low cost and open-source Internet-connected device that provides features for self-configuration. In addition, it selectively run on-board-algorithms for smart grid management depending on its deployment on the distribution network. Finally, we present the experimental results of Hardware-In-the-Loop simulations we performed.

Fault Detection, Isolation and Restoration Test Platform Based on Smart Grid Architecture Model Using Internet-of-Things Approaches

by Edoardo Patti and Abouzar Estebsari

To systematically shift existing distribution outage management paradigms to smart and more effic... more To systematically shift existing distribution outage management paradigms to smart and more efficient schemes, we need to have an architectural overview of Smart Grids to reuse the assets as much as possible. Smart Grid Architecture Model offers a support to design such emerging use cases by representing interoperability aspects among component, function, communication, information, and business layers. To allow this kind of interoperability analysis for design and implementation of Fault Detection, Isolation and Restoration function in outage management systems, we develop an Internet-of-Things-based platform to perform real time co-simulations. Physical components of the grid are modeled in Opal-RT real time simulator, an automated Fault Detection, Isolation and Restoration algorithm is developed in MATLAB and an MQTT communication has been adopted. A 2-feeder MV network with a normally open switch for reconfiguration is modeled to realize the performance of the developed co-simulation platform.

Indoor Air-Temperature Forecast for Energy-Efficient Management in Smart Buildings

In the last few years, the reduction of energy consumption and pollution became mandatory. It bec... more In the last few years, the reduction of energy consumption and pollution became mandatory. It became also a common goal of many countries. Only in Europe, the building sector is responsible for the total 40% of energy consumption and 36% of CO2 pollution. Therefore, new control policies based on the forecast of buildings energy behaviors can be developed to reduce energy waste (i.e. policies for Demand Response and Demand Side Management). This paper discusses an innovative methodology for smart building indoor air-temperature forecasting. This methodology is based on a Non-linear Autoregressive neural network. This neural network has been trained and validated with a dataset consisting of six years indoor air-temperature values of a building demonstrator. In detail, we have studied three characterizing rooms and the whole building. Experimental results of energy prediction are presented and discussed.

IoT Software Infrastructure for Remote Monitoring of Patients with Chronic Metabolic Disorders

Novel Information and Communication Technologies , such as Internet-of-Things (IoT), middleware a... more Novel Information and Communication Technologies , such as Internet-of-Things (IoT), middleware and cloud computing, are providing innovative solutions ranging in different contexts. Smart health is one of these scenarios. Indeed, there is a rising interest in developing new healthcare services for remote patient assistance and monitoring. Among all, the main promised benefits consist on improving the patients' quality of life, speeding up therapeutic interventions and reducing hospitalizations' costs. This is also known as Telemedicine. In this paper, we present a novel distributed software infrastructure for remote monitoring of patients with chronic metabolic disorders: i) it collects and and makes available information coming from IoT devices, ii) it performs analysis to help medical diagnosis and iii) it promotes a bidirectional communication among the end-users (i.e. medical personnel and patients). In this paper, we also present our experimental results performed in a laboratory test environment to validate the proposed solution.

An Energy-autonomous Wireless Sensor Network Development Platform

Internet-of-things enabled applications are increasingly popular and are expected to spread even ... more Internet-of-things enabled applications are increasingly popular and are expected to spread even more in the next few years. Energy efficiency is fundamental to support the widespread use of such systems. This paper presents a practical framework for the development and the evaluation of low-power Wireless Sensor Networks equipped with energy harvesting, aiming at energy-autonomous applications. An experimental case study demonstrates the capabilities of the solution.

A Compact PV Panel Model for Cyber-PhysicalSystems in Smart Cities

One of the ambitious goals of the ‘‘Smart city’’paradigm is to design zero-energy buildings. Buil... more One of the ambitious goals of the ‘‘Smart city’’paradigm is to design zero-energy buildings. Buildings can beconsidered as connected cyber-physical systems that require theconstruction of sound methodologies inherited from the EDAresearch. In particular, aiming at autonomous buildings, theeffective design of renewable energy sources is a key aspect forwhich such methodologies have to be developed.In this work, we propose a modeling strategy for the earlyestimation of the performance of PV arrays. Although a plethoraof PV panel models there exists, most of these models suffer fromaccuracy/complexity tradeoffs. On one hand, building fast modelsforces to ignore either the correlation between temperature andirradiance, or the topology of panels, thus yielding inaccurateestimations. On the other hand, more accurate models are timeconsuming and require costly measurements or circuit analysis,that cannot be extracted from the sole datasheet.This paper proposes a compact semi-empirical model, suitable forreal time simulation and built solely from information derivedfrom the PV panel datasheet. The model is built by empiricallyfitting an expression of the panel operating point as a function of both irradiance and temperature, and of the adopted PV systemtopology. The accuracy and effectiveness of the proposed modelhave been validated w.r.t. the production traces of the PV systemsof a real world industrial building

GIS-Based Optimal Photovoltaic Panel Floorplanning for Residential Installations

Shading is a crucial issue for the placement of PV installations, as it heavily impacts power pro... more Shading is a crucial issue for the placement of PV installations, as it heavily impacts power production and the corresponding return of investment. Nonetheless, residential rooftop installations still rely on rule-of-thumb criteria and on gross estimates of the shading patterns, while more optimized approaches focus solely on the identification of suitable surfaces (e.g., roofs) in a larger geographic area (e.g., city or district). This work addresses the challenge of identifying an optimal (with respect to the overall energy production) placement of PV panels on a roof. The novel aspect of the proposed solution lies in the possibility of having a sparse, irregular placement of individual modules so as to better exploit the variance of solar data. The latter are represented in terms of the distribution of irradiance and temperature values over the roof, as elaborated from historical traces and Geographical Information System (GIS) data. Experimental results will prove the effectiveness of the algorithm through three real world case studies, and that the generated optimal solutions allow to increase power production by up to 28% with respect to rule-of-thumb solutions.

Forecasting short-term solar radiation for photovoltaic energy predictions

In the world, energy demand continues to grow incessantly. At the same time, there is a growing n... more In the world, energy demand continues to grow incessantly. At the same time, there is a growing need to reduce CO 2 emissions, greenhouse effects and pollution in our cities. A viable solution consists in producing energy by exploiting renewable sources, such as solar energy. However, for the efficient use of this energy, accurate estimation methods are needed. Indeed, applications like Demand/Response require prediction tools to estimate the generation profiles of renewable energy sources. This paper presents an innovative methodology for short-term (e.g. 15 minutes) forecasting of Global Horizontal Solar Irradiance (GHI). The proposed methodology is based on a Non-linear Autoregressive neural network. This neural network has been trained and validated with a dataset consisting of solar radiation samples collected for four years by a real weather station. Then GHI forecast, the output of the neural network, is given as input to our Photovoltaic simulator to predict energy production in short-term time periods. Finally, experimental results for both GHI forecast and Photovoltaic energy prediction are presented and discussed.

The Energy Center Initiative at Politecnico di Torino: Practical experiences on energy efficiency measures in the municipality of Torino

by Edoardo Patti and lorenzo bottaccioli

Urban districts should evolve towards a more sustainable infrastructure and greener energy carrie... more Urban districts should evolve towards a more sustainable infrastructure and greener energy carriers. The utmost challenge is the smart integration and control, within the existing infrastructure, of new information and energy technologies (such as sensors, appliances, electric and thermal power and storage devices) that are able to provide multi-services based on multi-actors and multi and interchangeable energy carriers. In recent years, the Municipality of Torino represents an experimental scenario, in which practical experiences in the below-areas have taken place through a number of projects: 1. energy efficiency in building; 2. smart
energy grids management and smart metering; 3. biowaste-to-energy: mixed urban/industrial waste management with enhanced energy recovery from biogas. This work provides an overview and update on the most interesting initiatives of smart energy management in the urban context of Torino, with an analysis and quantification of the advantages gained in terms of energy and environmental efficiency.

District data management, modelling and visualization via interoperability

Data management has been one of the most interesting research fields within the smart city framew... more Data management has been one of the most interesting research fields within the smart city framework over the last years, with the aim of optimizing energy saving at district level. This topic involves the creation of a 3D city model considering heterogeneous datasets, such as Building Information Models (BIMs), Geographical Information Systems (GISs) and System Information Models (SIMs), taking into account both buildings and the energy network. Through the creation of a common platform, the data sharing was allowed starting from the needs of the users, such as the public administrator, the building manager and the energy professional. For this reason, the development of a District Information Modelling (DIM) methodology for the data management, related to the energy saving and CO2 emission, is considered the focus of this paper. It also presents a specific tool developed for the comparison of energy data in a selected district: the Benchmarking Tool.

Building energy modelling and monitoring by integration of IoT devices and Building Information Models

by Edoardo Patti and lorenzo bottaccioli

In recent years, the research about energy waste and CO2 emission reduction has gained a strong m... more In recent years, the research about energy waste and CO2 emission reduction has gained a strong momentum, also pushed by European and national funding initiatives. The main purpose of this large effort is to reduce the effects of greenhouse emission, climate change to head for a sustainable society. In this scenario, Information and Communication Technologies (ICT) play a key role. From one side, advances in physical and environmental information sensing, communication and processing, enabled the monitoring of energy behaviour of buildings in real-time. The access to this information has been made easy and ubiquitous thank to Internet-of-Things (IoT) devices and protocols. From the other side, the creation of digital repositories of buildings and districts (i.e. Building Information Models-BIM) enabled the development of complex and rich energy models that can be used for simulation and prediction purposes. As such, an opportunity is emerging of mixing these two information categories to either create better models and to detect unwanted or inefficient energy behaviours. In this paper, we present a software architecture for management and simulation of energy behaviours in buildings that integrates heterogeneous data such as BIM, IoT, GIS (Geographical Information System) and meteorological services. This integration allows: i) (near-) real-time visualisation of energy consumption information in the building context and ii) building performance evaluation through energy modelling and simulation exploiting data from the field and real weather conditions. Finally, we discuss the experimental results obtained in a real-world case-study.

A cloud-based smart metering infrastructure for distribution grid services and automation

by Edoardo Patti, Abouzar Estebsari, and Marco Pau

The evolution of the power systems towards the smart grid paradigm is strictly dependent on the m... more The evolution of the power systems towards the smart grid paradigm is strictly dependent on the modernization of distribution grids. To achieve this target, new infrastructures, technologies and applications are increasingly required. This paper presents a smart metering infrastructure that unlocks a large set of possible services aimed at the automation and management of distribution grids. The proposed architecture is based on a cloud solution, which allows the communication with the smart meters from one side and provides the needed interfaces to the distribution grid services on the other one. While a large number of applications can be designed on top of the cloud, in this paper the focus will be on a real-time distributed state estimation algorithm that enables the automatic reconfiguration of the grid. The paper will present the key role of the cloud solution for obtaining scalability, interoperability and flexibility, and for enabling the integration of different services for the automation of the distribution system. The distributed state estimation algorithm and the automatic network reconfiguration will be presented as an example of coordinated operation of different distribution grid services through the cloud.

GIS-based Software Infrastructure to Model PV Generation in Fine-grained Spatio-temporal Domain

by Edoardo Patti and lorenzo bottaccioli

Nowadays, we are moving forward to more sustainable societies, where a crucial issue consists on ... more Nowadays, we are moving forward to more sustainable societies, where a crucial issue consists on reducing footprint and greenhouse emissions. This transition can be achieved by increasing the penetration of distributed renewable energy sources together with a smarter use of energy. To achieve it, new tools are needed to plan the deployment of such renewable systems by modelling variability and uncertainty of their generation profiles. In this paper, we present a distributed software infrastructure for modelling and simulating energy production of Photovoltaic (PV) systems in urban context. In its core, it performs simulations in a spatio-temporal domain exploiting Geographic Information Systems together with meteorological data to estimate Photo-voltaic generation profiles in real operating conditions. This solution provides results in real-sky conditions with different time-intervals: i) yearly, ii) monthly and iii) sub-hourly. To evaluate the accuracy of our simulations, we tested the proposed software infrastructure in a real world case study. Finally, experimental results are presented and compared with real energy production data collected from PV systems deployed in the case study area.

A Flexible Distributed Infrastructure for Real-Time Co-Simulations in Smart Grids

Due to the increasing penetration of distributed generation, storage, electric vehicles and new I... more Due to the increasing penetration of distributed generation, storage, electric vehicles and new ICT technologies, distribution networks are evolving towards the Smart Grid paradigm. For this reason, new control strategies, algorithms and technologies need to be tested and validated before their actual field implementation. In this paper we present a novel modular distributed infrastructure, based on real-time simulation, for multipurpose Smart Grid studies. The different components of the infrastructure are described and the system is applied to a case study based on a real urban district located in northern Italy. The presented infrastructure is shown to be flexible and useful for different and multidisciplinary Smart Grid studies.

A Participatory Design Approach for Energy-Aware Mobile App for Smart Home Monitoring

It is generally recognized that our behaviours affect the environment. However, it is difficult t... more It is generally recognized that our behaviours affect the environment. However, it is difficult to correlate behaviour of an individual person to large-scale problems. This is usually due to insufficient ergonomy of available tools. The main cause is that most of user-awareness tools available are technology-centered instead of user-centered. In this paper, we present a participatory design approach we followed to design and develop an energy-aware mobile application for user-awareness on energy consumption for Smart Home monitoring. To engage end-users from the early design stages, we conduct two on-line surveys and a focus group involving about 630 people. Results allowed on identifying functional requirements and guidelines for mobile app design. The purpose of this research is to increase user-awareness on energy consumption using tools and methods required by users themselves. Furthermore in this paper, we present the technological choices that drove our implementation of an energy-aware application based on prosumers' requirements.

PVInGrid: A Distributed Infrastructure for evaluating the integration of Photovoltaic systems in Smart Grid

by Edoardo Patti and lorenzo bottaccioli

Planning and developing the future Smart City is becoming mandatory due to the need of moving for... more Planning and developing the future Smart City is becoming mandatory due to the need of moving forward to a more sustainable society. To foster this transition an accurate simulation of energy production from renewable sources, such as Photovoltaic Panels (PV), is necessary to evaluate the impact on the grid. In this paper, we present a distributed infrastructure that simulates the PV production and evaluates the integration of such systems in the grid considering data provided by smart-meters. The proposed solution is able to model the behaviour of PV systems solution exploiting GIS representation of rooftops and real meteorological data. Finally, such information is used to feed a real-time distribution network simulator.

Information Modeling for Virtual and Augmented Reality

The authors combine building information modeling (BIM) data with ambient information from device... more The authors combine building information modeling (BIM) data with ambient information from devices deployed in smart buildings. Their Android-based application can then offer environmental building information integrated with BIM data in an augmented and virtual reality environment. Today's buildings are equipped with various types of sensor nodes—either wired or wirelessly connected to a home or building network—for monitoring and management purposes. These devices provide ambient information about environmental and energy-related parameters to increase awareness in building occupants and managers, and to facilitate feedback actions or plan interventions. Nevertheless, how to enable interoperability across devices adopting heterogeneous communication protocols or standards is the object of intensive research. Service-oriented middleware technologies attempt to address this issue. 1,2 In the context of smart buildings, effectively engaging users and exploiting so much potential information requires contextualizing physical data from sensors by combining it with other types of ambient information, such as building characteristics, topology, and infrastructures. To this end, building and energy managers can exploit building information modeling (BIM), 3 a methodology that provides an accurate virtual model, usually in 3D, of a building and its infrastructures. This model is created, updated, and consulted during the design, development, and management of the building itself. Here, we present a methodology and an associated Android-based mobile application that integrates sensor data with building models, allowing end users (that is, technicians and building and energy managers) to navigate in a virtual or augmented building environment and access context-related physical environmental parameters such as temperature, humidity, and energy consumption. The values of these parameters can be easily correlated with other building characteristics and infrastructural properties, such as gas, electricity, or heating networks. Our methodology leverages a distributed software architecture composed of underlying middleware services to access sensor data in a hardware-independent way and combine it with BIM models interactively. Our work's main aims are to • collect environmental information from heterogeneous devices via a distributed software architecture; • combine BIM structural data with real-time information to improve building maintenance; • improve the visualization of such integrated information in a virtual and augmented reality environment; • move BIM from desktop computers to mobile devices by providing an innovative, portable tool for building and energy managers; • provide end users with a tool for interacting with the building to access heterogeneous data available from multiple pervasive sources; and • increase user awareness about energy consumption and environmental conditions. Augmented reality (AR) has been defined as the link between the real world and virtual reality (VR), 4 which in turn is a completely artificial environment for simulating reality. Each real object intrinsically provides a significant amount of information that sometimes is not immediately perceived by users. AR aims to make such information visible by overlapping digital reality with physical objects. The recent evolution of smart buildings provides new horizons for VR and AR application development, which could make building management easier and increase user awareness about energy consumption. Our proposed Android application exploits both AR and VR to provide building information, overcoming limits related to 2D visualization. Indeed, it presents a 3D environment in which real-time building information, coming from pervasive devices, is combined with structural and architectural data provided by BIM.

A novel integrated real-time simulation platform for assessing photovoltaic penetration impacts in smart grids

For future planning and development of smart grids, it is important to evaluate the impacts of PV... more For future planning and development of smart grids, it is important to evaluate the impacts of PV distributed generation, especially in densely populated urban areas. In this paper we present an integrated platform, constituted by two main components: a PV simulator and a real-time distribution network simulator. The first simulates real-sky solar radiation of rooftops and estimates the PV energy production; the second simulates the behaviour of the network when generation and consumption are provided at the di↵erent buses. The platform is tested on a case study based on real data for a district of the city of Turin, Italy.

A Cloud-based On-line Disaggregation Algorithm for Home Appliance Loads

In this work, we address the problem of providing fast and on-line households appliance load dete... more In this work, we address the problem of providing fast and on-line households appliance load detection in a non-intrusive way from aggregate electric energy consumption data. Enabling on-line load detection is a relevant research problem as it can unlock new grid services such as demand-side management and raises interactivity in energy awareness possibly leading to more green behaviours. To this purpose, we propose an On-line-NILM (Non-Intrusive Load Monitoring) machine learning algorithm combining two methodologies: i) Unsupervised event-based profiling and ii) Markov chain appliance load modelling. The event-based part performs event detection through contiguous and transient data segments, events clustering and matching. The resulting features are used to build household-specific appliance models from generic appliance models. Disaggregation is then performed on-line using an Additive Factorial Hidden Markov Model from the generated appliance model parameters. Our solution is implemented on the cloud and tested with public benchmark datasets. Accuracy results are presented and compared with literature solutions, showing that the proposed solution achieves on-line detection with comparable detection performance with respect to non on-line approaches.

A Distributed IoT Infrastructure to Test and Deploy Real-Time Demand Response in Smart Grids

by Edoardo Patti and Abouzar Estebsari

In this paper, we present a novel distributed framework for real time management and co-simulatio... more In this paper, we present a novel distributed framework for real time management and co-simulation of Demand Response (DR) in smart grids. Our solution provides a (near-) real-time co-simulation platform to validate new DR-policies exploiting Internet-of-Things approach performing software-in-the-loop. Hence, the behavior of real-world power systems can be emulated in a very realistic way and different DR-policies can be easily deployed and/or replaced in a plug-and-play fashion, without affecting the rest of the framework. In addition, our solution integrates real internet-connected smart devices deployed at customer premises and along the Smart Grid to retrieve energy information and send actuation commands. Thus, the framework is also ready to manage DR in a real-world Smart Grid. This is demonstrated on a realistic smart grid with a test case DR-policy.

A Novel Internet-of-Things Infrastructure to Support Self-Healing Distribution Systems

by Edoardo Patti and Abouzar Estebsari

In this paper, we present a novel distributed software infrastructure to foster new services in s... more In this paper, we present a novel distributed software infrastructure to foster new services in smart grids with particular emphasis on supporting self-healing distribution systems. This infrastructure exploits the rising Internet-of-Things paradigms to build and manage an interoperable peer-to-peer network of our prototype smart meters, also presented in this paper. The proposed three-phase smart meter, called 3-SMA, is a low cost and open-source Internet-connected device that provides features for self-configuration. In addition, it selectively run on-board-algorithms for smart grid management depending on its deployment on the distribution network. Finally, we present the experimental results of Hardware-In-the-Loop simulations we performed.

Fault Detection, Isolation and Restoration Test Platform Based on Smart Grid Architecture Model Using Internet-of-Things Approaches

by Edoardo Patti and Abouzar Estebsari

To systematically shift existing distribution outage management paradigms to smart and more effic... more To systematically shift existing distribution outage management paradigms to smart and more efficient schemes, we need to have an architectural overview of Smart Grids to reuse the assets as much as possible. Smart Grid Architecture Model offers a support to design such emerging use cases by representing interoperability aspects among component, function, communication, information, and business layers. To allow this kind of interoperability analysis for design and implementation of Fault Detection, Isolation and Restoration function in outage management systems, we develop an Internet-of-Things-based platform to perform real time co-simulations. Physical components of the grid are modeled in Opal-RT real time simulator, an automated Fault Detection, Isolation and Restoration algorithm is developed in MATLAB and an MQTT communication has been adopted. A 2-feeder MV network with a normally open switch for reconfiguration is modeled to realize the performance of the developed co-simulation platform.

Indoor Air-Temperature Forecast for Energy-Efficient Management in Smart Buildings

In the last few years, the reduction of energy consumption and pollution became mandatory. It bec... more In the last few years, the reduction of energy consumption and pollution became mandatory. It became also a common goal of many countries. Only in Europe, the building sector is responsible for the total 40% of energy consumption and 36% of CO2 pollution. Therefore, new control policies based on the forecast of buildings energy behaviors can be developed to reduce energy waste (i.e. policies for Demand Response and Demand Side Management). This paper discusses an innovative methodology for smart building indoor air-temperature forecasting. This methodology is based on a Non-linear Autoregressive neural network. This neural network has been trained and validated with a dataset consisting of six years indoor air-temperature values of a building demonstrator. In detail, we have studied three characterizing rooms and the whole building. Experimental results of energy prediction are presented and discussed.

IoT Software Infrastructure for Remote Monitoring of Patients with Chronic Metabolic Disorders

Novel Information and Communication Technologies , such as Internet-of-Things (IoT), middleware a... more Novel Information and Communication Technologies , such as Internet-of-Things (IoT), middleware and cloud computing, are providing innovative solutions ranging in different contexts. Smart health is one of these scenarios. Indeed, there is a rising interest in developing new healthcare services for remote patient assistance and monitoring. Among all, the main promised benefits consist on improving the patients' quality of life, speeding up therapeutic interventions and reducing hospitalizations' costs. This is also known as Telemedicine. In this paper, we present a novel distributed software infrastructure for remote monitoring of patients with chronic metabolic disorders: i) it collects and and makes available information coming from IoT devices, ii) it performs analysis to help medical diagnosis and iii) it promotes a bidirectional communication among the end-users (i.e. medical personnel and patients). In this paper, we also present our experimental results performed in a laboratory test environment to validate the proposed solution.

An Energy-autonomous Wireless Sensor Network Development Platform

Internet-of-things enabled applications are increasingly popular and are expected to spread even ... more Internet-of-things enabled applications are increasingly popular and are expected to spread even more in the next few years. Energy efficiency is fundamental to support the widespread use of such systems. This paper presents a practical framework for the development and the evaluation of low-power Wireless Sensor Networks equipped with energy harvesting, aiming at energy-autonomous applications. An experimental case study demonstrates the capabilities of the solution.

A Compact PV Panel Model for Cyber-PhysicalSystems in Smart Cities

One of the ambitious goals of the ‘‘Smart city’’paradigm is to design zero-energy buildings. Buil... more One of the ambitious goals of the ‘‘Smart city’’paradigm is to design zero-energy buildings. Buildings can beconsidered as connected cyber-physical systems that require theconstruction of sound methodologies inherited from the EDAresearch. In particular, aiming at autonomous buildings, theeffective design of renewable energy sources is a key aspect forwhich such methodologies have to be developed.In this work, we propose a modeling strategy for the earlyestimation of the performance of PV arrays. Although a plethoraof PV panel models there exists, most of these models suffer fromaccuracy/complexity tradeoffs. On one hand, building fast modelsforces to ignore either the correlation between temperature andirradiance, or the topology of panels, thus yielding inaccurateestimations. On the other hand, more accurate models are timeconsuming and require costly measurements or circuit analysis,that cannot be extracted from the sole datasheet.This paper proposes a compact semi-empirical model, suitable forreal time simulation and built solely from information derivedfrom the PV panel datasheet. The model is built by empiricallyfitting an expression of the panel operating point as a function of both irradiance and temperature, and of the adopted PV systemtopology. The accuracy and effectiveness of the proposed modelhave been validated w.r.t. the production traces of the PV systemsof a real world industrial building

GIS-Based Optimal Photovoltaic Panel Floorplanning for Residential Installations

Shading is a crucial issue for the placement of PV installations, as it heavily impacts power pro... more Shading is a crucial issue for the placement of PV installations, as it heavily impacts power production and the corresponding return of investment. Nonetheless, residential rooftop installations still rely on rule-of-thumb criteria and on gross estimates of the shading patterns, while more optimized approaches focus solely on the identification of suitable surfaces (e.g., roofs) in a larger geographic area (e.g., city or district). This work addresses the challenge of identifying an optimal (with respect to the overall energy production) placement of PV panels on a roof. The novel aspect of the proposed solution lies in the possibility of having a sparse, irregular placement of individual modules so as to better exploit the variance of solar data. The latter are represented in terms of the distribution of irradiance and temperature values over the roof, as elaborated from historical traces and Geographical Information System (GIS) data. Experimental results will prove the effectiveness of the algorithm through three real world case studies, and that the generated optimal solutions allow to increase power production by up to 28% with respect to rule-of-thumb solutions.

Forecasting short-term solar radiation for photovoltaic energy predictions

In the world, energy demand continues to grow incessantly. At the same time, there is a growing n... more In the world, energy demand continues to grow incessantly. At the same time, there is a growing need to reduce CO 2 emissions, greenhouse effects and pollution in our cities. A viable solution consists in producing energy by exploiting renewable sources, such as solar energy. However, for the efficient use of this energy, accurate estimation methods are needed. Indeed, applications like Demand/Response require prediction tools to estimate the generation profiles of renewable energy sources. This paper presents an innovative methodology for short-term (e.g. 15 minutes) forecasting of Global Horizontal Solar Irradiance (GHI). The proposed methodology is based on a Non-linear Autoregressive neural network. This neural network has been trained and validated with a dataset consisting of solar radiation samples collected for four years by a real weather station. Then GHI forecast, the output of the neural network, is given as input to our Photovoltaic simulator to predict energy production in short-term time periods. Finally, experimental results for both GHI forecast and Photovoltaic energy prediction are presented and discussed.

The Energy Center Initiative at Politecnico di Torino: Practical experiences on energy efficiency measures in the municipality of Torino

by Edoardo Patti and lorenzo bottaccioli

Urban districts should evolve towards a more sustainable infrastructure and greener energy carrie... more Urban districts should evolve towards a more sustainable infrastructure and greener energy carriers. The utmost challenge is the smart integration and control, within the existing infrastructure, of new information and energy technologies (such as sensors, appliances, electric and thermal power and storage devices) that are able to provide multi-services based on multi-actors and multi and interchangeable energy carriers. In recent years, the Municipality of Torino represents an experimental scenario, in which practical experiences in the below-areas have taken place through a number of projects: 1. energy efficiency in building; 2. smart
energy grids management and smart metering; 3. biowaste-to-energy: mixed urban/industrial waste management with enhanced energy recovery from biogas. This work provides an overview and update on the most interesting initiatives of smart energy management in the urban context of Torino, with an analysis and quantification of the advantages gained in terms of energy and environmental efficiency.

District data management, modelling and visualization via interoperability

Data management has been one of the most interesting research fields within the smart city framew... more Data management has been one of the most interesting research fields within the smart city framework over the last years, with the aim of optimizing energy saving at district level. This topic involves the creation of a 3D city model considering heterogeneous datasets, such as Building Information Models (BIMs), Geographical Information Systems (GISs) and System Information Models (SIMs), taking into account both buildings and the energy network. Through the creation of a common platform, the data sharing was allowed starting from the needs of the users, such as the public administrator, the building manager and the energy professional. For this reason, the development of a District Information Modelling (DIM) methodology for the data management, related to the energy saving and CO2 emission, is considered the focus of this paper. It also presents a specific tool developed for the comparison of energy data in a selected district: the Benchmarking Tool.

Building energy modelling and monitoring by integration of IoT devices and Building Information Models

by Edoardo Patti and lorenzo bottaccioli

In recent years, the research about energy waste and CO2 emission reduction has gained a strong m... more In recent years, the research about energy waste and CO2 emission reduction has gained a strong momentum, also pushed by European and national funding initiatives. The main purpose of this large effort is to reduce the effects of greenhouse emission, climate change to head for a sustainable society. In this scenario, Information and Communication Technologies (ICT) play a key role. From one side, advances in physical and environmental information sensing, communication and processing, enabled the monitoring of energy behaviour of buildings in real-time. The access to this information has been made easy and ubiquitous thank to Internet-of-Things (IoT) devices and protocols. From the other side, the creation of digital repositories of buildings and districts (i.e. Building Information Models-BIM) enabled the development of complex and rich energy models that can be used for simulation and prediction purposes. As such, an opportunity is emerging of mixing these two information categories to either create better models and to detect unwanted or inefficient energy behaviours. In this paper, we present a software architecture for management and simulation of energy behaviours in buildings that integrates heterogeneous data such as BIM, IoT, GIS (Geographical Information System) and meteorological services. This integration allows: i) (near-) real-time visualisation of energy consumption information in the building context and ii) building performance evaluation through energy modelling and simulation exploiting data from the field and real weather conditions. Finally, we discuss the experimental results obtained in a real-world case-study.

A cloud-based smart metering infrastructure for distribution grid services and automation

by Edoardo Patti, Abouzar Estebsari, and Marco Pau

The evolution of the power systems towards the smart grid paradigm is strictly dependent on the m... more The evolution of the power systems towards the smart grid paradigm is strictly dependent on the modernization of distribution grids. To achieve this target, new infrastructures, technologies and applications are increasingly required. This paper presents a smart metering infrastructure that unlocks a large set of possible services aimed at the automation and management of distribution grids. The proposed architecture is based on a cloud solution, which allows the communication with the smart meters from one side and provides the needed interfaces to the distribution grid services on the other one. While a large number of applications can be designed on top of the cloud, in this paper the focus will be on a real-time distributed state estimation algorithm that enables the automatic reconfiguration of the grid. The paper will present the key role of the cloud solution for obtaining scalability, interoperability and flexibility, and for enabling the integration of different services for the automation of the distribution system. The distributed state estimation algorithm and the automatic network reconfiguration will be presented as an example of coordinated operation of different distribution grid services through the cloud.

GIS-based Software Infrastructure to Model PV Generation in Fine-grained Spatio-temporal Domain

by Edoardo Patti and lorenzo bottaccioli

Nowadays, we are moving forward to more sustainable societies, where a crucial issue consists on ... more Nowadays, we are moving forward to more sustainable societies, where a crucial issue consists on reducing footprint and greenhouse emissions. This transition can be achieved by increasing the penetration of distributed renewable energy sources together with a smarter use of energy. To achieve it, new tools are needed to plan the deployment of such renewable systems by modelling variability and uncertainty of their generation profiles. In this paper, we present a distributed software infrastructure for modelling and simulating energy production of Photovoltaic (PV) systems in urban context. In its core, it performs simulations in a spatio-temporal domain exploiting Geographic Information Systems together with meteorological data to estimate Photo-voltaic generation profiles in real operating conditions. This solution provides results in real-sky conditions with different time-intervals: i) yearly, ii) monthly and iii) sub-hourly. To evaluate the accuracy of our simulations, we tested the proposed software infrastructure in a real world case study. Finally, experimental results are presented and compared with real energy production data collected from PV systems deployed in the case study area.

A Flexible Distributed Infrastructure for Real-Time Co-Simulations in Smart Grids

Due to the increasing penetration of distributed generation, storage, electric vehicles and new I... more Due to the increasing penetration of distributed generation, storage, electric vehicles and new ICT technologies, distribution networks are evolving towards the Smart Grid paradigm. For this reason, new control strategies, algorithms and technologies need to be tested and validated before their actual field implementation. In this paper we present a novel modular distributed infrastructure, based on real-time simulation, for multipurpose Smart Grid studies. The different components of the infrastructure are described and the system is applied to a case study based on a real urban district located in northern Italy. The presented infrastructure is shown to be flexible and useful for different and multidisciplinary Smart Grid studies.

A Participatory Design Approach for Energy-Aware Mobile App for Smart Home Monitoring

It is generally recognized that our behaviours affect the environment. However, it is difficult t... more It is generally recognized that our behaviours affect the environment. However, it is difficult to correlate behaviour of an individual person to large-scale problems. This is usually due to insufficient ergonomy of available tools. The main cause is that most of user-awareness tools available are technology-centered instead of user-centered. In this paper, we present a participatory design approach we followed to design and develop an energy-aware mobile application for user-awareness on energy consumption for Smart Home monitoring. To engage end-users from the early design stages, we conduct two on-line surveys and a focus group involving about 630 people. Results allowed on identifying functional requirements and guidelines for mobile app design. The purpose of this research is to increase user-awareness on energy consumption using tools and methods required by users themselves. Furthermore in this paper, we present the technological choices that drove our implementation of an energy-aware application based on prosumers' requirements.

PVInGrid: A Distributed Infrastructure for evaluating the integration of Photovoltaic systems in Smart Grid

by Edoardo Patti and lorenzo bottaccioli

Planning and developing the future Smart City is becoming mandatory due to the need of moving for... more Planning and developing the future Smart City is becoming mandatory due to the need of moving forward to a more sustainable society. To foster this transition an accurate simulation of energy production from renewable sources, such as Photovoltaic Panels (PV), is necessary to evaluate the impact on the grid. In this paper, we present a distributed infrastructure that simulates the PV production and evaluates the integration of such systems in the grid considering data provided by smart-meters. The proposed solution is able to model the behaviour of PV systems solution exploiting GIS representation of rooftops and real meteorological data. Finally, such information is used to feed a real-time distribution network simulator.

Information Modeling for Virtual and Augmented Reality

The authors combine building information modeling (BIM) data with ambient information from device... more The authors combine building information modeling (BIM) data with ambient information from devices deployed in smart buildings. Their Android-based application can then offer environmental building information integrated with BIM data in an augmented and virtual reality environment. Today's buildings are equipped with various types of sensor nodes—either wired or wirelessly connected to a home or building network—for monitoring and management purposes. These devices provide ambient information about environmental and energy-related parameters to increase awareness in building occupants and managers, and to facilitate feedback actions or plan interventions. Nevertheless, how to enable interoperability across devices adopting heterogeneous communication protocols or standards is the object of intensive research. Service-oriented middleware technologies attempt to address this issue. 1,2 In the context of smart buildings, effectively engaging users and exploiting so much potential information requires contextualizing physical data from sensors by combining it with other types of ambient information, such as building characteristics, topology, and infrastructures. To this end, building and energy managers can exploit building information modeling (BIM), 3 a methodology that provides an accurate virtual model, usually in 3D, of a building and its infrastructures. This model is created, updated, and consulted during the design, development, and management of the building itself. Here, we present a methodology and an associated Android-based mobile application that integrates sensor data with building models, allowing end users (that is, technicians and building and energy managers) to navigate in a virtual or augmented building environment and access context-related physical environmental parameters such as temperature, humidity, and energy consumption. The values of these parameters can be easily correlated with other building characteristics and infrastructural properties, such as gas, electricity, or heating networks. Our methodology leverages a distributed software architecture composed of underlying middleware services to access sensor data in a hardware-independent way and combine it with BIM models interactively. Our work's main aims are to • collect environmental information from heterogeneous devices via a distributed software architecture; • combine BIM structural data with real-time information to improve building maintenance; • improve the visualization of such integrated information in a virtual and augmented reality environment; • move BIM from desktop computers to mobile devices by providing an innovative, portable tool for building and energy managers; • provide end users with a tool for interacting with the building to access heterogeneous data available from multiple pervasive sources; and • increase user awareness about energy consumption and environmental conditions. Augmented reality (AR) has been defined as the link between the real world and virtual reality (VR), 4 which in turn is a completely artificial environment for simulating reality. Each real object intrinsically provides a significant amount of information that sometimes is not immediately perceived by users. AR aims to make such information visible by overlapping digital reality with physical objects. The recent evolution of smart buildings provides new horizons for VR and AR application development, which could make building management easier and increase user awareness about energy consumption. Our proposed Android application exploits both AR and VR to provide building information, overcoming limits related to 2D visualization. Indeed, it presents a 3D environment in which real-time building information, coming from pervasive devices, is combined with structural and architectural data provided by BIM.

A novel integrated real-time simulation platform for assessing photovoltaic penetration impacts in smart grids

For future planning and development of smart grids, it is important to evaluate the impacts of PV... more For future planning and development of smart grids, it is important to evaluate the impacts of PV distributed generation, especially in densely populated urban areas. In this paper we present an integrated platform, constituted by two main components: a PV simulator and a real-time distribution network simulator. The first simulates real-sky solar radiation of rooftops and estimates the PV energy production; the second simulates the behaviour of the network when generation and consumption are provided at the di↵erent buses. The platform is tested on a case study based on real data for a district of the city of Turin, Italy.

Design and Implementation of a Multi-Standard Event-Driven Energy Management System For Smart Buildings

by Iman Khajenasiri, Edoardo Patti, and Andrea Acquaviva

This paper presents the design and implementation of a multi-standard energy management system, w... more This paper presents the design and implementation of a multi-standard energy management system, which leverages heterogeneous devices to convert existing buildings into Smart Buildings. Its main purpose is to increase the energy efficiency of buildings providing user awareness to promote green behaviors. The proposed solution has been designed to enable interoperability across different standards and protocols in order to develop applications with which end users can interact with the system. Finally, a web portal and a smartphone application to give feedback and to view environmental information are presented

Towards a Software Infrastructure for District Energy Management

by Andrea Acquaviva and Edoardo Patti

2014 12th IEEE International Conference on Embedded and Ubiquitous Computing, 2014

Nowadays ICT is becoming a key factor to enhance the energy optimization in our cities. At distri... more Nowadays ICT is becoming a key factor to enhance the energy optimization in our cities. At district level, real-time information can be accessed to monitor and control the energy distribution network. Moreover, the fine grain monitoring and control done at building level can provide additional information to develop more efficient control policies for energy distribution in the district. In this paper we present a distributed software infrastructure for district energy management, which aims to provide a digital archive of the city in which energetic information is available. Such information is considered as the input for a decision system, which aims to increase the energy efficiency by promoting local balancing and shaving peak loads. As case study, we integrated in our proposed cloud the heating distribution network in Turin and we present exploitable options based on real-world environmental data to increase the energy efficiency and minimize the peak request.

Event-Driven User-Centric Middleware for Energy-Efficient Buildings and Public Spaces

by Andrea Acquaviva and Edoardo Patti

IEEE Systems Journal, 2014

ABSTRACT In this paper, the design of an event-driven user-centric middleware for monitoring and ... more ABSTRACT In this paper, the design of an event-driven user-centric middleware for monitoring and managing energy consumption in public buildings and spaces is presented. The main purpose is to increase energy efficiency in buildings and public spaces, thus reducing consumption. To achieve this, the proposed service-oriented middleware has been designed to be event based, also exploiting the user behavior patterns of people who live and work in buildings. Furthermore, it allows an easy integration of heterogeneous technologies in order to enable a hardware-independent interoperability between them. Moreover, a heating ventilation and air conditioning (HVAC) control strategy has been developed, and the whole infrastructure has been deployed in a real-world case study consisting of a historical building. Finally, the results will be presented and discussed.

Energy saving in existing buildings by an intelligent use of interoperable ICTs

by Giovanni Fracastoro, Anna Osello, Edoardo Patti, Anna Pellegrino, Andrea Acquaviva, and david erba

Energy Efficiency, 2013

ABSTRACT In this paper, we report a methodology, developed in the context of Smart Energy Efficie... more ABSTRACT In this paper, we report a methodology, developed in the context of Smart Energy Efficient Middleware for Public Spaces European Project, aimed at exploiting ICT monitoring and control services to reduce energy usage and CO2 footprint in existing buildings. The approach does not require significant construction work as it is based on commercial-off-the-shelf devices and, where present, it exploits and integrates existing building management systems with new sensors and actuator networks. To make this possible, the proposed approach leverages upon the following main contributions: (a) to develop an integrated building automation and control system, (b) to implement a middleware for the energy-efficient buildings domain, (c) to provide a multi-dimensional building information modelling-based visualisation, and (d) to raise people’s awareness about energy efficiency. The research approach adopted in the project started with the selection, as case studies, of representative test and reference rooms in modern and historical buildings chosen for having different requirements and constraints in term of sensing and control technologies. Then, according to the features of the selected rooms, the strategies to reduce the energy consumptions were defined, taking into account the potential savings related to lighting, heating, ventilation, and air conditioning (HVAC) systems and other device loads (PC, printers, etc.). The strategies include both the control of building services and devices and the monitoring of environmental conditions and energy consumption. In the paper, the energy savings estimated through simulation, for both HVAC and lighting, are presented to highlight the potential of the designed system. After the implementation of the system in the demonstrator, results will be compared with the monitored data.

A New Distributed Framework for Integration of District Energy Data from Heterogeneous Devices

by Enrico Macii, Salvatore Rinaudo, Edoardo Patti, Francesco G Brundu, and Andrea Acquaviva

Design, Automation & Test in Europe Conference & Exhibition (DATE), 2015, 2015

The introduction of "smart" low-cost sensing (and actuating) devices enabled the recent diffusion... more 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.

Enable sensor networks interoperability in smart public spaces through a service oriented approach

by Andrea Acquaviva and Edoardo Patti

5th IEEE International Workshop on Advances in Sensors and Interfaces IWASI, 2013

In this work, the design of a service-oriented infrastructure for monitoring and managing energy ... more In this work, the design of a service-oriented infrastructure for monitoring and managing energy consumption in public buildings and spaces is presented. The main focus concerns the development of software layers enabling the interoperability between heterogeneous wireless sensor and actuator nodes aimed at monitoring the energy consumption, controlling environmental parameters such as illuminance and temperature to take advantage of natural resources and relative humidity to ensure the best possible comfort conditions with the most efficient use of energy.

Distributed Software Infrastructure for General Purpose Services in Smart Grid

by angeliki lydia antonia (angelina) A L A syrri and Edoardo Patti

IEEE Transactions on Smart Grid, 2014