Homes with integrated state of the art technology are considered Smart Homes. A smart home has special systems which enable remote control via remote computer or smart phones. These modern integrated services are supported by electrical power infrastructures called Smart Grids, which provides a stable electrical power environment to support all functionalities, with intelligent power systems that provide increased power quality. Inside a Smart home, a legacy metering system called Smart Meters are installed offering new functionalities such as remote readings of power consumption, and different time usage of tariffs.Preliminary research has already indicated vulnerability attacks on smart meters which affect the security and privacy in smart meters. Security issues in this system include vulnerabilities and privacy issues includes information leakage in real-time consumption data that is recorded by the smart meters.Enhancing both security and privacy in the smart meters are the main purpose of this thesis. The principle goal of this research is to provide more understanding about the smart meters from a security and privacy perspective. This thesis investigates issues and problems in smart meters and proposes a secure communication protocol in the application layer, in addition to a proof-of-concept of the final solution. In this research we introduce the solution by means of two scenarios, we highlight the effects of an attack on the smart meters on levels of simulation and theory. The first scenario is to "take control over the smart meter to access the data consumptions in the smart meters". The proposed solution of using the Smart Phone as a third part to protect the smart meters has been evaluated using a network simulation tool. The result shows that the data captured by attacking node is encrypted and can't be used for any useful operation. In the second scenario, "monitoring the data consumptions to harm the user's privacy", in other words, stealing the user's devices. The proposed solution is using the home electrical power routing to moderate the home's load signature in order to hide appliance usage information. Data clusters are implemented as a proof of concept to evaluate the data. The results show that there is only 99.5 % correct clustered data with good quality.

Giving feedback to households about their energy consumption has been seen by many as a necessity in order for households to reduce their energy consumption and lower their carbon footprint. Many studies have been made on how smart meters, that give feedback on the total consumption, are used and their effect on the consumption. However, fewer studies have been done on how disaggregated feedback is understood and acted upon. Smappee is an energy feedback system that monitors the household’s consumption and is able to detect appliances’ consumption with only 3 physical clamps at the incoming current, using non-intrusive load monitoring (NILM). NILM differentiate appliances based on their electrical signature which is generated by turning an appliance on and off. The users get the feedback through a smartphone application. This study attempts to answer the question “How do users understand and act upon disaggregated feedback in Smappee?” by doing a qualitative study based on contextual interviews made on 15 users of Smappee. The results of the interviews are then compared with previous studies within the field of smart meters and a conceptual model is being described of how users understand Smappee. The results show that disaggregated feedback in Smappee is perceived as too difficult to acquire. Users thought it was too hard to find which appliances represented in Smappee correspond to which physical appliances in the household. However, the users used the real-time total consumption in order to make an estimation of how much certain appliances consumed. This indicates that users are interested in disaggregated feedback if it is easily accessible. Users have, in general, a good understanding of how Smappee detects appliances. They understand that Smappee is measuring the incoming current and makes assumptions based on the increases and decreases. They did not use the disaggregated feedback, even though they understood how it worked. / Att ge feedback till hushåll om deras energikonsumtion har setts, av många, som en nödvändighet för att hushåll ska kunna reducera sin energikonsumtion och minska sina koldioxidutsläpp. Flera studier har gjorts om hur smarta mätare, som ger feedback om totalkonsumtionen, används och deras effekt på förbrukningen. Men färre studier har gjorts om hur uppdelad feedback förstås och hur användare agerar på detta. Smappee är ett energifeedbacksystem som mäter hushålls konsumtion och är kapabel att detektera apparaters konsumtion med endast 3 klamrar på den inkommande strömmen, genom att använda “non-intrusive load monitoring (NILM). NILM skiljer på apparater baserat på deras elektriska signatur som genereras av att sätta på och slå av apparater. Användarna får feedbacken i en Smartphone-applikation. Denna studie försöker besvara frågan: “Hur förstår och agerar användare på uppdelad feedback i Smappee?” genom att genomföra en kvalitativ studie baserad på kontextuella intervjuer genomförda med 15 användare av Smappee. Resultatet från intervjuerna är sedan jämförda med tidigare studier inom området smarta mätare och en konceptuell model beskrivs om hur användare förstår sig på Smappee. Resultatet visar att uppdelad feedback i Smappee uppfattas för svår att använda. Användarna upplevde att det var för svårt att finna vilken apparat i Smappee som korresponderar till en viss fysisk apparat i hushållet. Dock använde användarna realtidskonsumtionen för att skapa en uppskattning om hur mycket vissa apparater konsumerade. Detta indikerar att användarna hade ett intresse i uppdelad feedback om det var tillgängligt på ett lättare sätt. Användare har, i allmänhet, en god förståelse om hur Smappee detekterar apparater. De förstår att Smappee mäter inkommande ström och gör antaganden baserat på ökningar och minskningar. De använde inte uppdelad feedback även om de förstod hur det fungerade.

Thesis advisor: Scott Fulford / Can smart metering program and time-of-use (TOU) prices help reduce energy consumption in New York City? Being able to track electricity consumption levels and to modify consumer usage patterns are important for policy makers to efficiently manage the energy markets. Unfortunately, no reliable and up-to-date data have been brought to bear on this question. I study the effects of time-of-use (TOU) prices and smart metering for the residents of Shanghai and I investigate further what can policy makers do in order to adapt and transfer this successful DSM experience from Shanghai to the residential sector in New York City. The primary objective of my study is to characterize the realistic short-term and long-term potential for the smart metering program in New York City given my empirical findings that the smart metering program has had brought great benefits to the residents of Shanghai. People respond to incentives; if electricity is charged at different prices throughout a day, consumers are likely to shift their usage to when it is cheaper. My findings suggest that policy makers should think harder about designing a pricing scheme that can optimize the social plus. / Thesis (BA) — Boston College, 2011. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: College Honors Program. / Discipline: Economics Honors Program. / Discipline: Economics.

Utility companies (electricity, gas, and water suppliers), governments, and researchers recognize an urgent need to deploy communication-based systems to automate data collection from smart meters and sensors, known as Smart Metering Infrastructure (SMI) or Automatic Meter Reading (AMR). A smart metering system is envisaged to bring tremendous benefits to customers, utilities, and governments. The advantages include reducing peak demand for energy, supporting the time-of-use concept for billing, enabling customers to make informed decisions, and performing effective load management, to name a few. A key element in an SMI is communications between meters and utility servers. However, the mass deployment of metering devices in the grid calls for studying the scalability of communication protocols. SMI is characterized by the deployment of a large number of small Internet Protocol (IP) devices sending small packets at a low rate to a central server. Although the individual devices generate data at a low rate, the collective traffic produced is significant and is disruptive to network communication functionality. This research work focuses on the scalability of the transport layer functionalities. The TCP congestion control mechanism, in particular, would be ineffective for the traffic of smart meters because a large volume of data comes from a large number of individual sources. This situation makes the TCP congestion control mechanism unable to lower the transmission rate even when congestion occurs. The consequences are a high loss rate for metered data and degraded throughput for competing traffic in the smart metering network. To enhance the performance of TCP in a smart metering infrastructure (SMI), we introduce a novel TCP-based scheme, called Split- and Aggregated-TCP (SA-TCP). This scheme is based on the idea of upgrading intermediate devices in SMI (known in the industry as regional collectors) to offer the service of aggregating the TCP connections. An SA-TCP aggregator collects data packets from the smart meters of its region over separate TCP connections; then it reliably forwards the data over another TCP connection to the utility server. The proposed split and aggregated scheme provides a better response to traffic conditions and, most importantly, makes the TCP congestion control and flow control mechanisms effective. Supported by extensive ns-2 simulations, we show the effectiveness of the SA-TCP approach to mitigating the problems in terms of the throughput and packet loss rate performance metrics. A full mathematical model of SA-TCP is provided. The model is highly accurate and flexible in predicting the behaviour of the two stages, separately and combined, of the SA-TCP scheme in terms of throughput, packet loss rate and end-to-end delay. Considering the two stages of the scheme, the modelling approach uses Markovian models to represent smart meters in the first stage and SA-TCP aggregators in the second. Then, the approach studies the interaction of smart meters and SA-TCP aggregators with the network by means of standard queuing models. The ns-2 simulations validate the math model results. A comprehensive performance analysis of the SA-TCP scheme is performed. It studies the impact of varying various parameters on the scheme, including the impact of network link capacity, buffering capacity of those RCs that act as SA-TCP aggregators, propagation delay between the meters and the utility server, and finally, the number of SA-TCP aggregators. The performance results show that adjusting those parameters makes it possible to further enhance congestion control in SMI. Therefore, this thesis also formulates an optimization model to achieve better TCP performance and ensures satisfactory performance results, such as a minimal loss rate and acceptable end-to-end delay. The optimization model also considers minimizing the SA-TCP scheme deployment cost by balancing the number of SA-TCP aggregators and the link bandwidth, while still satisfying performance requirements.

Faced with a looming electricity crisis, the provincial government is calling for Ontarians to adopt a “culture of conservation”, and is planning to equip all residential dwellings with new metering infrastructure known as “smart meters” by 2010. In addition to providing residents with the ability to “shift” their electricity consumption from the most expensive “on-peak” times of the day, the data from these meters can be used to provide residents with detailed information, or feedback, regarding their consumption patterns. This research assessed whether electricity-use feedback affected households’ electricity consumption behaviour, whether feedback effected pro-conservation attitude changes, and what types of feedback were most effective in these regards. An initial mail survey was sent to 1,257 smart metered Milton, Ontario homes to obtain information regarding residents’ appliances and their consumption behaviour and attitudes. Of the 298 respondents, most of whom were living in homes that were less than seven years old, 106 were chosen to receive weekly household-specific feedback in various formats from July to October 2006. A follow-up survey was conducted to assess any changes in attitude as a result of the feedback, and weather-adjusted 2005 and 2006 consumption data were used to quantitatively discern any resulting consumption changes. While overall results revealed that the feedback made little difference in household consumption levels compared to the 2005 baseline period, there were some indications that it was effective in encouraging shifting, and had the opposite effect on overall conservation (i.e. it encouraged increased consumption). Also, while the comparison of “pre-” and “postfeedback” surveys revealed the feedback had no measured effect on encouraging proconservation attitudes, overall, customer acceptance of the feedback was high.

Faced with a looming electricity crisis, the provincial government is calling for Ontarians to adopt a “culture of conservation”, and is planning to equip all residential dwellings with new metering infrastructure known as “smart meters” by 2010. In addition to providing residents with the ability to “shift” their electricity consumption from the most expensive “on-peak” times of the day, the data from these meters can be used to provide residents with detailed information, or feedback, regarding their consumption patterns. This research assessed whether electricity-use feedback affected households’ electricity consumption behaviour, whether feedback effected pro-conservation attitude changes, and what types of feedback were most effective in these regards. An initial mail survey was sent to 1,257 smart metered Milton, Ontario homes to obtain information regarding residents’ appliances and their consumption behaviour and attitudes. Of the 298 respondents, most of whom were living in homes that were less than seven years old, 106 were chosen to receive weekly household-specific feedback in various formats from July to October 2006. A follow-up survey was conducted to assess any changes in attitude as a result of the feedback, and weather-adjusted 2005 and 2006 consumption data were used to quantitatively discern any resulting consumption changes. While overall results revealed that the feedback made little difference in household consumption levels compared to the 2005 baseline period, there were some indications that it was effective in encouraging shifting, and had the opposite effect on overall conservation (i.e. it encouraged increased consumption). Also, while the comparison of “pre-” and “postfeedback” surveys revealed the feedback had no measured effect on encouraging proconservation attitudes, overall, customer acceptance of the feedback was high.

When consumers are able to buy electricity on an hourly instead of monthly basis, the demand side flexibility is likely to increase. One way to lower the cost of electricity is to move consumption from peak price hours to low price hours, a sort of inter-temporal substitution were the net energy use is unaffected. By simulating one example of inter-temporal substitution in the Swedish spot market during 2008-2010, we show that the general welfare effects are small in terms of a more efficient energy production, but that the transfer of resources from producers to consumers is large. Whether the welfare effect is positive or negative is highly dependent on future electricity prices, the introduction of renewable energy resources, and the price of the new technology needed for the demand side regulation. If 2010 is used as a reference case, the results from our specific case concludes that a natural investment equilibrium is reached when approximately 150 000 households invest in the proposed demand side regulation technology. Using the same reference year, we see that if 70 000 households participates the Net Present Welfare benefit is around 10% of the necessary investment cost; to be compared with the transfer of benefits from producers to consumers which estimates roughly 2100% of the necessary investment cost. We argue that this imbalance in potential welfare benefits between producers and consumers might slow down the process of increasing the general welfare.

The ability of typical utility meters and advanced meters including sub-circuit metering to disaggregate residential electric loads and determine what appliances a homeowner is using at a given time in investigated. The basics of residential electricity systems, instrumentation options, and characteristics of selected residential loads are presented. This information informs a discussion on present and future disaggregation algorithms. The conclusions highlight the importance of reactive power and current harmonics in determining power consumed and identifying modern electrical devices, and raise concerns related to the ability of typical 15 minute interval utility smart meters to disaggregate loads. / text

Utility companies (electricity, gas, and water suppliers), governments, and researchers recognize an urgent need to deploy communication-based systems to automate data collection from smart meters and sensors, known as Smart Metering Infrastructure (SMI) or Automatic Meter Reading (AMR). A smart metering system is envisaged to bring tremendous benefits to customers, utilities, and governments. The advantages include reducing peak demand for energy, supporting the time-of-use concept for billing, enabling customers to make informed decisions, and performing effective load management, to name a few. A key element in an SMI is communications between meters and utility servers. However, the mass deployment of metering devices in the grid calls for studying the scalability of communication protocols. SMI is characterized by the deployment of a large number of small Internet Protocol (IP) devices sending small packets at a low rate to a central server. Although the individual devices generate data at a low rate, the collective traffic produced is significant and is disruptive to network communication functionality. This research work focuses on the scalability of the transport layer functionalities. The TCP congestion control mechanism, in particular, would be ineffective for the traffic of smart meters because a large volume of data comes from a large number of individual sources. This situation makes the TCP congestion control mechanism unable to lower the transmission rate even when congestion occurs. The consequences are a high loss rate for metered data and degraded throughput for competing traffic in the smart metering network. To enhance the performance of TCP in a smart metering infrastructure (SMI), we introduce a novel TCP-based scheme, called Split- and Aggregated-TCP (SA-TCP). This scheme is based on the idea of upgrading intermediate devices in SMI (known in the industry as regional collectors) to offer the service of aggregating the TCP connections. An SA-TCP aggregator collects data packets from the smart meters of its region over separate TCP connections; then it reliably forwards the data over another TCP connection to the utility server. The proposed split and aggregated scheme provides a better response to traffic conditions and, most importantly, makes the TCP congestion control and flow control mechanisms effective. Supported by extensive ns-2 simulations, we show the effectiveness of the SA-TCP approach to mitigating the problems in terms of the throughput and packet loss rate performance metrics. A full mathematical model of SA-TCP is provided. The model is highly accurate and flexible in predicting the behaviour of the two stages, separately and combined, of the SA-TCP scheme in terms of throughput, packet loss rate and end-to-end delay. Considering the two stages of the scheme, the modelling approach uses Markovian models to represent smart meters in the first stage and SA-TCP aggregators in the second. Then, the approach studies the interaction of smart meters and SA-TCP aggregators with the network by means of standard queuing models. The ns-2 simulations validate the math model results. A comprehensive performance analysis of the SA-TCP scheme is performed. It studies the impact of varying various parameters on the scheme, including the impact of network link capacity, buffering capacity of those RCs that act as SA-TCP aggregators, propagation delay between the meters and the utility server, and finally, the number of SA-TCP aggregators. The performance results show that adjusting those parameters makes it possible to further enhance congestion control in SMI. Therefore, this thesis also formulates an optimization model to achieve better TCP performance and ensures satisfactory performance results, such as a minimal loss rate and acceptable end-to-end delay. The optimization model also considers minimizing the SA-TCP scheme deployment cost by balancing the number of SA-TCP aggregators and the link bandwidth, while still satisfying performance requirements.

With public opinion shifting to a believe in climate change in the early 2000s the interest in energy efficiency has been increasing. EU Directives set the goal of deploying smart meters if cost efficient for providing more detailed energy consumption. The main goal is to better inform consumers and to give individual households the power to change possibly energy wasting behaviours. This paper evaluates through a literature review the effectiveness of intelligent electricity metering systems with a focus on the DACH region, the provision of different types of feedback and its persistence. It can be concluded that energy feedback enabled by smart meters can lead to savings in the range of 0% to 4.5% in this region. If feedback is provided continuously savings persist. However, several aspects have to be considered to ensure effectiveness of smart meter deployment.