Alessandro Pitì, Department of Electronics, Information and Bioengineering, Politecnico di Milano
Eleonora Bettenzoli, Italian Regulatory Authority for Electricity Gas and Water (AEEGSI); Marco De Min, AEEGSI
Luca Lo Schiavo, AEEGSI

The Energy Regulators Regional Association (ERRA) has recently awarded a paper about the Italian experience related to smart metering. The winning authors are Alessandro Pitì, Department of Electronics, Information and Bioengineering, Politecnico di Milano; Eleonora Bettenzoli, Italian Regulatory Authority for Electricity Gas and Water (AEEGSI); Marco De Min, AEEGSI and Luca Lo Schiavo, AEEGSI. ERRA is a voluntary organization comprising of independent energy regulatory bodies primarily from Europe, Asia, Africa, Middle East and the United States of America.

The Association’s main objective is to exchange information and experience among its members and to expand access to energy regulatory experience around the world. In 2014 the association established the “ERRA Regulatory Research Award” to encourage, reward and expand energy regulatory research and analysis and contribute to improve regulatory practices.


Aim of the winner paper is to share the Italian regulatory experience of the last decade concerning smart metering, providing guidelines to those countries which are going to evaluate the upgrade of their conventional metering infrastructure. Italy has been one of the first European country in switching to a smart metering system for more than 35 million low-voltage customers [1]. The migration towards a smart metering system can significantly improve and simplify the network management and, consequently, reduce the operational costs. Even energy thefts and frauds can be reduced thanks to anti-tamper sensors and remotely-read alarms. Moreover, increasing the number of measurements and reducing the time needed to make them available, it is also possible to activate new opportunities for other stakeholders of the electric value chain.

An important parameter that should be considered during a cost-benefit analysis is the original configuration of the power system in which a smart-metering revolution is under evaluation. The authors identified three main possible set-ups:

• Vertically-integrated system: all the activities along the value-chain are managed by a single integrated entity. 
• Unbundled system: in a liberalized retail market, different companies provide distribution and supply separately. 
• Distributed system: Final customers become active and can exploit self-consumption as well as exchange energy with the network participating in the energy market. 

According to the specific context each country can compare and choose the most convenient approach and identify the corresponding benefits.

In this view, the authors defined three main approaches:

•  distribution-oriented approach to increase efficiency of the electric network 
•  retail-oriented approach to foster retailers competition and introduce new business models 
• customer-oriented approach to promote customer awareness and energy-market participation 

These approaches can also be aggregated together in order to cover benefits for different stakeholders of the power system [2]. An aggregated approach could gather all the benefits for the distribution and metering services with the ones of energy retail or customers, while a comprehensive approach considers all the stakeholders.

The first generation of smart metering in Italy was essentially led by a distribution-oriented approach for cost-efficiency reasons and the first results were very promising [3]: the capital costs associated to the new infrastructure was covered in few years by a strong reduction of operational costs avoiding personnel intervention on-site for measurements reading and service management (activation/de-activation). The remote reading and management of the meters was handled only by distribution system operators (DSOs) once a month collecting three energy totalizers according to the Time-of-Use tariff mechanism (ToU): the energy consumed, sampled by a smart meter with an associated timestamp, is cheaper if consumed in predefined time interval of the day [4]. Thus, customers can modulate their electric consumption according to three infra-day price bands in order to save money. The telecommunications technology used by all the DSOs is the Power Line Communication (PLC) using CENELEC band A (dedicated to DSOs).

Close to the end-of –life period of the first generation smart meters, fixed in Italy at 15 years, AEEGSI published a decision reporting the functional requirements for a new generation [5] based on European Recommendation n. 2012/148/EU [6]. Thanks to the retail-market liberalization and the strong penetration of the distributed generation of the recent years, a comprehensive approach involving DSOs, retailers, and customers has been adopted. The major improvements regard the types of data collected and, above all, their granularity: instead of just three values of energy per month, second generation smart meters enable the reading of the daily energy curves with samples stored every 15 minutes. The curves are remotely read and made available to retailers within 24 hours after a validation process. New types of data such as the instantaneous active power, the events of outages and the weekly minimum and maximum voltage are now collected.

Metering data are collected and validated for billing purposes by DSOs before sending the results to the retailers. Thanks to the large amount of measurements acquired, retailers are enabled to offer more customized schemes of ToU prices, up to a Real-Time-Pricing (RTP) regime in which customers can pay energy according to the same price fluctuations established by the wholesale energy market in turn of a bill saving. Moreover, retailers could promote new prepaid contracts.

The Italian second generation smart meters can also send non-validated real-time measurements directly to the final customers thanks to a new communications chain. This is made possible thanks to dedicated devices, called “In-Home Devices” (IHDs). The technology used to send these data to the customer is left to the meter operator (which in Italy coincides with the DSO). The services that this metering data can enable have been investigated and can be grouped into four categories: customer awareness, advanced commercial offers, scheduling & control of the customer’s appliances and network ancillary services [7]. In order to ensure interoperability between the IHDs of different manufacturers, the Italian Electro technical Committee (CEI) has defined a new standard protocol [8]. Up to now the technologies identified are PLC using CENELEC band C (which is dedicated to the customer’s devices) and the radiofrequency 169 MHz. Other technologies are under study.

According to the recent European decision about privacy, both communications between the smart meter and IHDs and between the smart meters and the DSOs must ensure confidentiality, authenticity and integrity of the customer’s data.

Basing their analysis on the Italian experience, the authors tried to combine the specific power system configuration with the different approaches identified with the corresponding benefits (Fig. 1). Surely, a comprehensive approach is the most beneficial but difficult and costly to be approached at first. An aggregated approach can be initially faster and cheaper to adopt even though the European trend seems to prefer a more complete approach [9].





Figure 1: Benefits perceived by the three approaches for each power system set-up

References

[1] European Commission, Benchmarking smart metering deployment in the EU-27 with a focus on electricity, Brussels, Belgium: Report from the Commission, 2014

[2] Italian Authority of Electricity, Gas and Water (AEEGSI), Consultation paper 468/2016/E/eel: Sistemi di smart metering di seconda generazione per la misura di energia elettrica in bassa tensione e il rilascio dell'impronta energetica (energy footprint) al cliente finale. Benefici potenziali e orientamenti per il conseguente adeguamento regolatorio, Milan, Milan, 2016.


[3] European Commission, SWD(2014)188 - Country fiches for electricity smart metering accompanying the document: Benchmarking smart metering deployment in the EU-27 with a focus on electricity, Brussels, 2014.



[4] S. Maggiore, M. Gallanti, W. Grattieri and M. Benini, “Impact of the enforcement of a time-of-use tariff to residential customers in Italy,” 22nd International Conference on Electricity Distribution, pp. 10-13, 06 2013.


[5]  Italian Authority of Electricity, Gas and Water (AEEGSI), Consultation paper 416/2015/R/eel: Sistemi di smart metering di seconda generazione per la misura di energia elettrica in bassa tensione, Milan, 2015.


[6]  European Commission, Commission Recommendation of 9 March 2012 on preparations for the roll-out of smart metering systems, Official Journal of the European Union, 2012.


[7] International Electrotechnical Commission, TR 62746-2:2015 Systems interface between customer energy management system and the power management system - Part 2: Use cases and requirements, 2015.

[8] International Electrotechnical Commission, IEC 62056-7-5:2016. Electricity metering data exchange - The DLMS/COSEM suite - Part 7-5: Local data transmission profiles for Local Networks (LN), 2016.

[9] European Commission, “Directive 2009/72/EC concerning common rules for the internal market in electricity - Annex 1,” Official Journal of the European Union, 2009.

Promoting sustainable mobility behaviors by individualized eco-feedbacks based on automatic activity tracking

Francesca Mangili, Claudio Bonesana, IDSIA – Istituto dalle Molle di Studi sull’Intelligenza Artificiale – SUPSI - Manno (Switzerland)
Francesca Cellina, Insitute for Applied Sustainability to the Built Environment – SUPSI – Canobbio (Switzerland)
Dominik Bucher, Institute of Cartography and Geoinformation - ETH Zurich - Zurich (Switzerland)

Mobility data are used in several fields of research, most notably transport analysis and planning, e.g., to plan transport infrastructures of cities. They are also required to analyze energy consumption caused by mobility needs and to find ways to foster more sustainable mobility behaviors. Traditionally, accurate mobility data are recorded only on a small scale using very time consuming methods (e.g., travel diaries), while, on the large scale, only rather simple and inaccurate information can be collected (e.g., using personal interviews). Nowadays, the large diffusion of Smartphones and their capability of tracking users’ activities have opened the way to a new, unobtrusive way of collecting detailed mobility data on a large scale.

The availability of new possibilities for automatic mobility tracking inspired our GoEco! project (http://www.goeco-project.ch), which aims at investigating if ITC-based eco-feedback and social interactions (social comparison and peer pressure) can be effective in fostering long term changes in personal mobility behavior and reduction of car use. To this purpose we created a ‘living lab’ experiment, which is a field study involving real-life users in complex, real-world settings. Figure 1 summarizes the organization of the living lab experiment. About 400 volunteers in Canton Ticino and Zurich areas were involved in a one year long collective challenge that, by means of a Smartphone app, leveraged eco-feedback and game elements to persuade them to modify their mobility behavior. The GoEco! app tracked their routes, provided them with feedback on their mobility styles (kilometers travelled, mean of transport used, energy consumption and CO2 emission) and suggested them meaningful low-impact, alternative modal options. Building on individual achievement and competitive game mechanics, the GoEco! app also invited them to define personal goals and targets for change and to take part in individual mobility challenges, providing them with weekly feedback on their progress, virtual rewards for good performances and possibilities to compare their achievements with the other participants.

Figure 1 Design of the GoEco! experiment. 

The first challenge faced in GoEco!, was, therefore, to find a way to automatically track the movements of a large number of varied users. Many mobility tracking apps exists, e.g., fitness apps, which can track users efficiently (low power consumption) and rather accurately. However, none of them can distinguish the mean of transport used with a degree of detail sufficient for assessing the ecological impact of the monitored activities. Therefore, we created the GoEco! Tracker app building upon the existing fitness app Moves® (https://moves-app.com/). The information provided by Moves® is combined with GIS information about public transport services and processed by a classifier distinguishing between 13 transport modes (Moves® itself only distinguishes between foot, bike and motorized transport). The classifier accounts for the different mobility patterns of individual users at two levels: i) it accounts for the different use each participant can make of the same means of transport (e.g., the average distances traveled by car can differ between users in large cities and users in small towns); ii) it accounts for the routines of the different users by identifying systematic itineraries. The classifier learns online and continuously updated with the new activities collected for each user.

The second challenge we faced was to provide simple and meaningful eco-feedback to the users: we aimed both at making users aware of their mobility patterns and the consequences they entail, and at providing them with targeted information on more sustainable travel alternatives available. To this purpose, we first identified each user’s ‘systematic mobility patterns’ and then we identified the corresponding “potential for change”, by selecting the most sustainable travel alternatives available for the specific systematic itinerary (Figure 2). In order to identify feasible alternatives, we developed an algorithm for the identification of systematic loops starting and ending at the user home place, and removed conflicting mean of transport from the suggested solution (e.g., one cannot take the car if he/she firstly left home by bike).

Figure 2 A user’s systematic itinerary and the corresponding alternative for change. 

The third challenge was to design and implement gamification elements that could induce behavioral change, favoring achievement of the individual ‘potentials for change’. To this purpose, we relied on: i) customized, individual goal setting; ii) weekly challenges targeting a variety of travel purposes and times of the day; iii) a badge system rewarding particularly sustainable choices automatically detected by the app; iv) a leader board comparing weekly performances of all the participants.

Notwithstanding high dropout levels among the participants, the project has allowed monitoring around one hundred users for a long time period, collecting a big amount of mobility data which are currently being analyzed. Preliminary results have shown a moderate effect of the intervention in Ticino. No significant effect is observed instead in Zurich, probably due to larger availability of public transport in that area and, therefore, more sustainable initial mobility patterns of the participants. The main limitation to drawing clear and strong conclusions from the study is due to the large dropout rate observed, which considerably reduced our sample size. We believe that this is due to the too large effort required to the participants, as they were asked to confirm the correctness of all the activities detected by the tracker.

Overall, this project has provided useful insights on the opportunity offered by Smartphone-based tracking as well as on the limitations of the current technologies. We believe that, in order to make Smartphone based tracking a viable solution for real word, large-scale mobility monitoring, very little or no interaction with the user should be requested. The reasons are twofold: users tend to leave the project if it implies an effort for a long period of time; any interaction with the users will potentially influence their behavior. Such result can only be achieved by unobtrusive automatic tracking, and Smartphones can definitely be applied to this goal. However, as all information has to be automatically inferred, with no or little validation by the user, very accurate tracking systems and algorithms are needed. Currently, the accuracy in the collection and segmentation of mobility data can be very high, but it too strongly depends on the quality of the specific device owned by the user. On the other side, further research is required for a reliable identification of the means of transport, which is a fundamental requirement for the successful use of Smartphones in mobility data collection. Finally, although a plethora of data mining methods exists for knowledge extraction from complex data, lot of work has still to be done for structuring and analyzing mobility data collected by Smartphones, so to extract high level, interpretable information, both at the individual and aggregated levels, to be directly exploited in transport and land planning and policymaking.

A privacy-friendly Gaming Framework in Smart Electricity and Water Grids

Giacomo Verticale, Dept. of Electronics, Information and Bioengineering, Politecnico di Milano, Italy
Cristina Rottondi, Dalle Molle Institute for Artificial Intelligence, Lugano, Switzerland

Serious game-based approaches aimed at stimulating, increasing, or modifying users' activities have recently attracted increasing interest. Such approaches can be categorized as serious games or gamified interactions. 

A subcategory of serious games, the so called persuasive games, are specifically designed with the scope of changing people's attitudes and behaviors in a desirable direction (e.g. towards a more sustainable lifestyle, or to increase votes for a political party). Such games include e.g. advertising games, health-related games and social/political advocacy games.

The empirical evidence of the effectiveness of these game-based approaches has been demonstrated in several studies, which have highlighted that one of the main reasons for their successfulness is the tendency of people towards positive imitation. Therefore, in smart power grids, utilities may incorporate gamification as a building block of more complex behavioral demand response approaches to perform peak shaving.

Regrettably, online gaming raises numerous privacy concerns about the possibly improper usage of data gathered from the players. The relevance of such issues is even more pronounced when gaming data are combined with data related to electricity, water or gas consumption, from which sensitive information about users' habits and lifestyles can be inferred.

To overcome the above mentioned privacy concerns, we propose a cryptographic framework (see Figure 1) for an online gaming portal operated by a third-party entity. The framework leverages a smart metering architecture in which the users have access to their own high-frequency consumption data and can use them as input data to a multi-party secure protocol.

The envisioned application scenario is a smart electricity or water grid where the utility adopts a gamified mechanism to influence the consumption patterns of the users in order to indirectly shape their aggregate load (e.g. for peak shaving or load flattening scopes).

More in detail, the framework enables gamified interactions in which players are grouped in teams and are challenged to maintain the team-aggregated consumption below a threshold defined by the utility. Team competitions with the aim of achieving the lowest aggregate consumption are also supported.






The framework includes:

• a suite of privacy-friendly protocols relying on Shamir Secret Sharing (SSS) scheme, which enable the members of a team to compute their overall resource consumption without communicating individual meter readings, and to compare it to those of other teams without learning the exact consumption amounts. Additionally, the protocol impedes that the game platform learns the meter readings of the players (either individual or aggregated) and their challenge objectives; 
• a verification protocol relying on Pedersen Commitments which can be run by the utility to detect whether users have reported false or altered results to the game platform; 
• a secure, persistent storage of authenticated commitments based on the blockchain technology. 

The security of the proposed framework has been evaluated in [1] assuming that the entities behave according to the honest-but-curious adversarial model. The numerical assessment of the computational load and exchanged data volumes required by the protocol shows that the framework can scale up to several thousands of players.


[1] Rottondi, Cristina, and Giacomo Verticale. "A Privacy-Friendly Gaming Framework in Smart Electricity and Water Grids." IEEE Access 5 (2017): 14221-14233.




Finally, we feature the interview to prof. Andrea Rizzoli (Dalle Molle Institute for Artificial Intelligence, Lugano, Switzerland) summarizing the outcomes of the FP7 European Project “SmartH2O”, which focuses on smart systems for water management. 

ICT SOLUTIONS TO ENHANCE URBAN WATER MANAGEMENT

Prof. Andrea Rizzoli (Dalle Molle Institute for Artificial Intelligence, Lugano, Switzerland)

Upcoming Events

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