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The smart meter sends the meter readings to the utilities at desired frequency allowing better visibility of consumer electricity consumption behaviour by providing more data points for in-depth analysis and for generating insights using advanced data analytics and data science techniques. The granulated data helps utilities in designing schemes for audience suitable for demand response management to shift the peak hour demand to off-peak hours. In this paper, a method is proposed for load profile segmentation which can be used by utilities for identifying the characteristics of different users and targeting those whose demand curve can be flattened during peak hours with various demand response management schemes. Firstly, exploratory data analysis is done on the cleaned dataset to find the optimal epoch size, understand the distribution of data in each epoch, and use it for dimensionality reduction. For reducing the clustering computation time, dimensionality reduction is done by around 64% using Principal Component Analysis. The first six principal components are identified as carrying maximum variance using the cumulative variance technique in each epoch. Unsupervised Machine Learning based k-means clustering technique is applied to these principal components. The optimal value of k is evaluated using the WCSS technique where k = 5 and k = 3 for residential and SME users respectively is found. The average silhouette coefficient for residential users is 0.48 and for SME users is 0.51. Hence, well-separated clusters are formed with minimum intra-cluster distance using PCA for dimensionality reduction which is used for load profile segmentation and Post Clustering Analysis. [ABSTRACT FROM AUTHOR]

In smart grid communication, tampering and illegally accessing power data can lead to ambiguous decisions that disturb power demand management and may lead to system failure. Hence, an efficient security protocol is required to secure smart grid communications. This paper proposes a secure authenticated key agreement scheme to establish a session key between smart meters and service providers. The session key is further used to securely share crucial information like power consumption reports and smart appliances. The proposed scheme is free from the requirement of Public Key Infrastructure (PKI) to authenticate the public key, which makes it more reliable to implement. The security analysis shows that the protocol is secure against all security attacks possible over a key agreement protocol. As the proposed technique uses a 160-bit ECC key, it offers the same level of security with lighter computation. As per the performance evaluation, the proposed technique can establish the session key between the smart meter and service provider in just 13.744 ms, showing its efficiency over the other existing protocols in the literature. [ABSTRACT FROM AUTHOR]

Home area network (HAN) devices send the electricity consumption and other important data to the smart meter that must remain confidential from other devices. This paper proposes a novel one-dimensional hybrid chaotic map. The proposed map shows excellent chaotic properties when analyzed by bifurcation diagram, Lyapunov exponent & Shannon entropy. We further design an encryption strategy for data transfers between the smart meter and HAN devices. The proposed encryption scheme uses the existing lightweight key management in advanced metering infrastructure (LKM-AMI) architecture for data transfers, in which the encrypted data is transferred through an insecure channel and private keys are provided by trusted third party (TTP) through secure channels. The 2-way communication between HAN devices and the smart meter sends messages that are encrypted by using the proposed novel hybrid one-dimensional chaotic map. The encryption strategy mainly consists of three steps. In the first step, the seed and the control parameters are initialized. The second phase generates two intermediate keys using the proposed hybrid chaotic map. In the last phase, we encrypt the message by applying permutation followed by diffusion using intermediate keys. The proposed encryption strategy is resistant to various attacks. [ABSTRACT FROM AUTHOR]

Smartness in smart grids and cities is an assemblage of devices that produce data as truth claims and deploy new modes of governance focused on chal (deception, cunning) and bal (power) with a promise to reduce losses and maximise profits. Building on postcolonial geographies, the paper argues that chal (छल) and bal (बल) are central to understanding the deployment of smart grids in India. Managers use the idea of the practice of chal and bal by political citizen-subjects, and the disorder of governance this causes, to justify the deployment of smart infrastructure. However, the paper shows that smartness can be understood as automation, and deployment from a distance, of chal and bal by a capital-state nexus to counter the chaliya (छलिया) (deceptive/cunning/cheat/trickster) citizen-subjects. Planners and implementers expect data and digitalisation to bring order by (re)training and excluding lower-level workers and consumers. These promise to reduce resource losses, making electricity utilities profitable. Rather than being distinctly corporate or clearly in the domain of the state, smart is situated at the fracture of public and private resources, and political and civil spaces. By developing a postcolonial analysis of smart grids and focusing on the 'inbetweeners', electricity utility staff and middle-class citizen-subjects, the paper furthers the understanding of smartness and subalternity of elites. [ABSTRACT FROM AUTHOR]

The article is a book review of "Smart Grid and Enabling Technologies" by Shady S. Refaat, Omar Ellabban, Sertac Bayhan, Haitham Abu-Rub, Dr. Frede Blaabjerg, Miroslav M. Begovic. The book explores the topic of smart grid and the technologies that enable it to work efficiently. It covers various chapters on topics such as renewable energy, power electronics, energy storage, microgrids, smart transportation, net zero energy buildings, smart grid communication infrastructures, information security, data management, demand-side management, sustainable business models, customer acceptance, cloud computing, artificial intelligence, simulation tools, and smart grid standards. The book provides a comprehensive overview of the subject and is suitable for those interested in learning about smart grid technology. [Extracted from the article]

Smart metering infrastructures collect data almost continuously in the form of fine-grained long time series. These massive data series often have common daily patterns that are repeated between similar days or seasons and shared among grouped meters. Within this context, we propose an unsupervised method to highlight individuals with abnormal daily dependency patterns, which we term evolution outliers. To this end, we approach the problem from the standpoint of High Dimensional Functional Time Series and we use the concept of functional depth to exploit the dynamic group structure and isolate individual meters with a different evolution. The performance of the proposal is first evaluated empirically through a simulation exercise under different evolution scenarios. Subsequently, the importance and need for an evolution outlier detection method are shown by using actual smart-metering data corresponding to photo-voltaic energy generation and circuit voltage records. Here, our proposal detects outliers that might go unnoticed by other approaches of the literature that have demonstrated to be effective capturing magnitude and shape abnormalities. [ABSTRACT FROM AUTHOR]

In recent years, the need to develop a user-centric Smart Product-Service Systems (smart PSS) with user experience (UX) has been widely recognized by both industry and academia. Although perceived value is a key driver of smart product/service development with unique experience, existing research has rarely systematically explored the perceived value of smart PSS that can be identified, which could lead organizations to be unable to adapt to this rapid digital transformation. Thus, this study adopted smart kitchen appliances to identify which dimensions of perceived value are influential in the development of the smart PSS with UX. The primary objectives of this study were to: (1) develop a comprehensive perceived value scale of smart PSS; and (2) validate the scale's stability and goodness of fit. The analysis results of this study show that a one-order confirmatory factor analysis is effective for verifying the scale. Five latent variables, usefulness, flexibility, reliability, fee, and technicality, and 19 observable variables can be used as effective evaluation measurement indicators to demonstrate that a value-based viewpoint is crucial for development of the smart PSS with UX in the organization. [ABSTRACT FROM AUTHOR]

The increasing electricity demand has led the conventional distribution system to evolve into the smart grid context. One of the advantages of this intelligent system is the ability to estimate the states of a grid. Implementing a state estimator in distribution networks requires much analysis – such as the observability of an extensive system, big data techniques for data processing, and the use of artificial intelligence to generate predictions and protect the control system against cyber-attacks. This systematic mapping study covers 15148 articles, selecting 37 for further research and discussion. The reports offer different state estimators and techniques to improve performance, for instance, solutions against malicious data, optimal meter allocation, and voltage control. In addition to these topics, this article discusses different approaches to generate pseudo measurements. Probabilistic and deterministic, machine learning, and neural network models appear as a trend. The studies show the main methods used for data collection, offering a trend toward smart meters. [ABSTRACT FROM AUTHOR]

Vehicle to grid (V2G) is the most hopeful approach to transfer energy as well as information in the bidirectional way. V2G network is formed by electric vehicles which connect with smart metres for information and energy transfer in a wireless manner. Even though many security preserving schemes developed in V2G networks, they were prone to enormous number of security breaches. A countless deal of works has been done towards it, but security mechanisms in V2G networks are not effective. This survey work provides a summary about the V2G network characteristics, significance, security services and the security challenges. Moreover, this work offers a summary of some foremost security attacks on various security services such as accessibility, confidentiality, authentication, integrity and non-repudiation and the related countermeasures to make the V2G communications more protected. [ABSTRACT FROM AUTHOR]

Model-assisted estimators have attracted a lot of attention in the last three decades. These estimators attempt to make an efficient use of auxiliary information available at the estimation stage. A working model linking the survey variable to the auxiliary variables is specified and fitted on the sample data to obtain a set of predictions, which are then incorporated in the estimation procedures. A nice feature of model-assisted procedures is that they maintain important design properties such as consistency and asymptotic unbiasedness irrespective of whether or not the working model is correctly specified. In this article, we examine several model-assisted estimators from a design-based point of view and in a high-dimensional setting, including linear regression and penalized estimators. We conduct an extensive simulation study using data from the Irish Commission for Energy Regulation Smart Metering Project, to assess the performance of several model-assisted estimators in terms of bias and efficiency in this high-dimensional data set. [ABSTRACT FROM AUTHOR]

Critical Infrastructures (CIs) are the backbone of our societal and economic activities. Safeguarding their uninterrupted operation and keeping them safe against different types of threats, from natural disasters to human-induced acts, is of the essence. This analysis focuses on the energy sector mostly and the water sector secondarily as these two sectors are among the CIs that have mainly suffered the consequences of cyber incidents. In this context, the paper examines the applicability of the EU cybersecurity regulatory framework in the energy (including both electricity and gas) and the water sectors, as well as the sector specific initiatives that have been adopted so far to tackle the cybersecurity challenges the two sectors face. Given the expansive deployment of smart technologies and devices in both sectors, the regulatory regime of smart metres and the complications that are associated with their installation and use in terms of privacy and security of the collected data is examined separately. Finally, the analysis attempts to shed some light on the shortcomings of the existing legal framework and to contribute to its further effectiveness by suggesting further steps that could potentially help make the energy and water sectors more cyber resilient in the new threat landscape. [ABSTRACT FROM AUTHOR]

The correct determination of water consumption is key to increasing hydraulic modeling reliability. In this context, Smart Metering (SM) is an important concept. The SM systems can provide consumption at a customer level and in small intervals of time. In this scenario, the work focused on a residential condominium, in Brazil, where an SM system was implemented. The work uses data obtained to model consumers' water consumption and proposes a system to detect metering failures and internal water loss. Three models were proposed: one uses Autoregressive Integrated Moving Average (ARIMA) theory, another uses the Seasonal Autoregressive Integrated Moving Average (SARIMA), and the last uses multivariate linear regression. The average root mean square error of the first model was 14,73, of the second was 13,50, and of the third was 20,99. A metering and consumption system, able to detect internal leaks and others, was also developed. [ABSTRACT FROM AUTHOR]

Rampant power theft is a growing concern for power distribution companies as well as the country's economy at the low voltage consumer end. Power theft including theft of power, defective meters, or errors in billing has been an area of growing attention from researchers. Power theft affects the power supply efficiency, raises the demand on the generating station, and causes significant harm to the legitimate customers. This is a major problem in developing countries, and detecting and dealing with the people responsible for theft have been extremely troublesome for utility companies. This paper discusses the factors that influence power theft and pilferages. In this paper, we have given due diligence to the literature review on the methods for detecting power theft. Apparently in a huge democratic setup like India, none of the proposed methods have been very effective so far. There has been no respite from the rampant power thefts, which at times happens in a very organized manner by well-known establishments. There are many power distribution companies active in India. All these companies install energy meters in every house for the measurement of the power consumption. However, the consumers tamper and bypass these devices to connect unauthorized loads sometimes in cohort with the employees of these distribution companies. The change to centralized metering infrastructure for a huge number of consumers is not a feasible solution at all. Thus there is a need for designing alternate low-cost tamper free smart energy meter to detect and communicate the pilferage of power. [ABSTRACT FROM AUTHOR]

—This study proposes a direct load control (DLC) approach for residential demand response (DR) programs, which uses a dynamic voltage control method to reduce the peak electricity consumption in homes. In the proposed approach, if a utility needs to reduce electrical load consumption, a DLC signal is sent to a smart meter (SM) either via utility's communication infrastructure. SM communicates with a group of smart plugs attached to selected domestic appliances to individually reduce the output voltage. The electrical consumption of selected appliances can be reduced without turning them OFF. Hence, the peak demand of a residential house can be reduced without turning off selected power-intensive loads, like in a classic direct load control (DLC) approach used by several electric utilities. The proposed dynamic voltage control is operated can be done within a certain limit defined set by international standards to avoid any possible negative impacts on domestic appliances. The results indicated that the proposed DLC could reduce the peak electricity demand up to around 32% using both voltage control and renewable energy. The proposed approach is expected to give flexibility to utilities to control the electrical demand of homes while ensuring participants remain more comfortable during a DR event. [ABSTRACT FROM AUTHOR]

—The smart electricity meter (SEM) is a critical element of the smart grid, so power supply company and customers pay many attentions to its service life. SEM is directly employed in the power grid, and there is serious harmonic pollution. The traditional life prediction method of SEM has not considered the influence of the harmonic factor on the reliable life of the SEM, this paper proposes a novel life prediction method of SEM based on the harmonic factor. Based on the data of reliability harmonic test, the harmonic factor is extracted and integrated into the meter life prediction model to improve the accuracy of the prediction. The comparison between the prediction of multiple models of SEMs and the results of accelerated life testing verifies that the method has high accuracy. [ABSTRACT FROM AUTHOR]

Building Energy Management is the most promising, trending, and essential way to enhance Building energy performance but it varies from one system to another. It can be achieved only by extracting the entire knowledge of the system. For this, a deep learning framework is proposed. The framework visualizes the Energy profiles of various workspaces in a building and also accounts for the Generating sources feeding them. It imparts awareness among consumers on effective handling of available Energy sources. kRNN-LSTM is the proposed framework applied to real-time Smart energy meter data observed in the Two-storeyed Electrical department building block of Thiagarajar College of Engineering, Madurai. k-means clustering is done to achieve the underlying pattern uniformities while RNN based LSTM gives a one-month ahead prediction. The LSTM model is compared with the Machine learning-based ARIMA model and basic Naïve time series model by employing quality metrics computed from each model. The proposed model gives 94% accuracy and the reason behind the superiority of the model is due to temporal analytics dependencies and application of sliding window concept to Data for updating and learning the patterns of energy usage. In addition to this, the framework also points out some sort of information such as workspaces with higher energy profiles, Annual peaks in consumption, duration, and range of existence of peak demand, preferable Generating source on a cost basis, etc., Moreover, a suggestion for reducing the cost involved in Energy utilization is also depicted. [ABSTRACT FROM AUTHOR]

Data stream management (DSM) for cyber-physical systems (CPSs) provides good quality care services in the medical domain. This is a very prominent field of research that includes sensing, processing, and networking of various medical devices. The DSM for CPS is a combination of computation using Cyber world (computers or WBANs), including wearable sensors and smart meters as well as communication between the processes through the networks. Data analytics and mobile computing include the usage of wireless sensors which plays a very significant role while handling uncertainties of data stream in healthcare domain. This paper presents a comprehensive review of DSM techniques, including the problem of concept drift in the healthcare domain using CPS, and the challenges associated with the domain. The complete taxonomy characterizes and classifies all the components and methods required for data management in healthcare. This paper provides a glimpse of futuristic techniques used for DSM in view of concept drift while handling real-time data management in healthcare and also identifies the fields for future research. The prime objective of this review is to provide a solution to aggregate health data streams using DSM, generated from different sources, clean and normalize them, and improve them for analysis, diagnosis, pattern identification for data analytics and complex event processing. It is supposed that the techniques discussed in this paper are relevant and useful for further research in the area of DSM for CPS in healthcare. [ABSTRACT FROM AUTHOR]

Public opinion on critical issues, such as technology deployment aimed at reducing greenhouse gases or increasing energy efficiency, may be impacted through information disseminated through the media. It is therefore increasingly important to understand the role media plays in spreading misinformation to the public. Through this study, we add to the growing body of literature on misinformation by exploring the relationship between media attention, risk perceptions, knowledge of, and support for smart meter technology. Smart meter deployment has been hindered, in part, due to beliefs that the technology causes cancer or can lead to incorrect electricity billing. To examine the relationship between misinformation and support for smart meter technology, we analyzed a quota sample of 1,046 people living in the U.S. Results show that paying attention to smart meter stories is related to familiarity with false information about smart meters. Familiarity with false information is also associated with misperceiving risks regarding the technology (e.g. those who are aware of false information about health problems associated with smart meters are more concerned about health-related problems associated with this technology). Ultimately, reporting higher levels of concern about smart meters is associated with lower support for government and industry policies aimed at increasing smart meter installation. However, the relationship for misperceptions, which decreased support for smart meters, was only present among those with low knowledge levels of the technology. Results indicate that knowledge may be a protective factor in terms of mitigating the effects that misinformation could have on outcomes such as support for policies or technological developments. [ABSTRACT FROM AUTHOR]

Although distributed state estimation in the microgrids facilitates the application of monitoring and supervision, optimal methods for installation of meters and estimators, and determining optimal links between them have remained scarce. Thus, this study solves an optimization problem to determine the optimal number and location of the meters, the optimal number of estimators, optimal categorizing of meters for transferring data to each estimator, and the optimal determination of links between the estimators. To this end, the number of meters and the estimation errors in a Kalman filter-based distributed state estimation are minimized in this paper, subject to power flow equations of the microgrid, convergence condition of the state estimation, and observability of the microgrid. The proposed method is examined on a microgrid consisting of three distributed resources, one storage system, and three electrical loads. The results show that 10 meters and 4 estimators with proper communication can meet the constraints and perform state estimation with minimum cost and error. The optimality and effectiveness of the results are investigated by designing various studies. [ABSTRACT FROM AUTHOR]

In recent decades, the adoption of smart water metering technology for water management has increased. The case for the adoption of smart water meters is mainly motivated by engineering and efficiency considerations around water conservation and related issues, for instance leak detection. At a consumer level, this can lead to improved feedback resulting in better customer control over consumption and household expenditure. The rate of adoption of smart water meters is dependent on many factors such as initial cost. The cost is expected to reduce as the technology matures and more options become available. The rate of adoption of the technology is also expected to be shaped by a variety of regulatory and social considerations. The purpose of this paper is to review the regulatory and social aspects that are likely to affect the adoption of the smart water metering technology in the future, with a focus on Australia. Instances of these aspects include privacy and health concerns, social acceptance, and communication strategies. It is expected that this paper will generate a healthy debate around the adoption of smart water meters to help the water sector to achieve a smooth transition from conventional to smart water meters. [ABSTRACT FROM AUTHOR]

Nowadays, knowing load profiles of different customers in electricity market-oriented operation of power system is very important. Smart metering system provides more than enough information about it. However, even if there is a load measurement on each customer in the system, it is economically unjustified and it is time consuming to conduct a detailed analysis each of them. In this study, unlike literature approaches, the different industrial load profiles are observed. The fuzzy c-means clustering is applied to get typical load curves representing different type of industry. For that purpose, the detailed statistical analysis and calculations of load shape factors of the industrial customers for different period of the year have been carried out. Customer's 15-min load was collected by developing Advanced Metering Infrastructure in the power system of Bosnia and Herzegovina. According to available data, statistical analysis and applied fuzzy c-means clustering, three typical load profiles for different industrial customers are proposed. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are preferred for industrial applications due to the progressive increase of sensor electronics. One such use is the deployment of WSNs in Smart Grids. The periodic data from the Smart Meters and critical information are transferred by the AMI network between the customer site and MDMS through WSNs. The AMI is composed of various sensors for metering purposes. These sensors communicate with the base station in a restricted range. In this article, an energy-efficient routing for WSNs in AMI networks is proposed through density-based Fuzzy C-Means clustering (DFCM) to attain load balancing. The obtained simulation results show that DFCM can provide satisfactory performance and is suitable for data collection in Smart Grids. [ABSTRACT FROM AUTHOR]

The urgency of climate change means that low-carbon transitions are needed in large socio-technical systems such as energy and transportation. These transitions must be rapid, but also fair. An emerging body of evidence suggests that users have important roles in transitions, yet much previous research has examined user involvement while assuming it to be largely a positive force. This goes against a growing amount of evidence within sociotechnical studies that highlight the potentially obstructive or negative role that users may play in transitions and innovation. In this study, we pose a critical question: In what ways may users perpetuate injustices within a transition? To answer this question, we provide conceptual background on energy justice and user adoption of low-carbon energy and mobility technologies. We then analyse users and energy injustices in three low-carbon transitions – solar energy in Germany, electric vehicles in Norway, and smart meters in Great Britain – based on empirical data from interviews, focus groups, and internet forums. Our main contribution is to show how users in low-carbon transitions are not always positively engaged, or even neutral, but can introduce and contribute to inequality and exclusion. [ABSTRACT FROM AUTHOR]

Decisions regarding the supply of electricity across a power grid must take into consideration the inherent uncertainty in demand. Optimal decision-making requires probabilistic forecasts for demand in a hierarchy with various levels of aggregation, such as substations, cities, and regions. The forecasts should be coherent in the sense that the forecast of the aggregated series should equal the sum of the forecasts of the corresponding disaggregated series. Coherency is essential, since the allocation of electricity at one level of the hierarchy relies on the appropriate amount being provided from the previous level. We introduce a new probabilistic forecasting method for a large hierarchy based on UK residential smart meter data. We find our method provides coherent and accurate probabilistic forecasts, as a result of an effective forecast combination. Furthermore, by avoiding distributional assumptions, we find that our method captures the variety of distributions in the smart meter hierarchy. Finally, the results confirm that, to ensure coherency in our large-scale hierarchy, it is sufficient to model a set of lower-dimension dependencies, rather than modeling the entire joint distribution of all series in the hierarchy. In achieving coherent and accurate hierarchical probabilistic forecasts, this work contributes to improved decision-making for smart grids. for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement. [ABSTRACT FROM AUTHOR]

Huge amounts of sensitive data are generated and transmitted on a smart grid infrastructure. These data are used for acquisition of various parameters of interest from smart meters in the grid and control of the grid. However, wireless communication processes across the smart grid network are vulnerable to different attacks like any other wireless communication infrastructure, which has unavoidably given rise to concerns about how to efficiently secure services and preserve privacy in smart grid network especially in metering. In this article, an efficient approach and framework was introduced for secure metering and preservation of consumers' privacy in different neighborhood area networks of different service providers of the smart grid communication network. Our approach effectively introduced a communication framework for efficient and secure metering, privacy preservation, load balancing, and billing using perturbation and data aggregation techniques. Computational and security analysis were performed to ascertain its efficiency in terms of computational cost, energy consumption, and security. The results showed that the approach not only prevented gleaning of the metering but did so at a relatively low computational overhead compared with other approaches. [ABSTRACT FROM AUTHOR]

The development of policies promoting smart meter adoption is essential to guide the transition towards sustainable use of resources such as water, electricity and gas, as well as inform smart-city initiatives. This article explores household preferences in terms of different smart meters and identifies the amounts that households are willing to pay for different smart meter configurations to monitor electricity, water and gas based on the features of their home including dwelling type, size and property value. To this aim, we employ a mixed multinomial logit model that accounts for the heterogeneity in customers' preferences for different smart meters. As a proof of concept, the proposed model is applied to a survey incorporating a discrete choice experiment carried out with 232 respondents in the Florianopolis metropolitan region, located in the south of Brazil. Our approach offers a number of advantages to facilitate the broader implementation of smart grid systems that would otherwise be overlooked using traditional approaches that rely on aggregated estimates for demand and willingness to pay for proposed schemes. [ABSTRACT FROM AUTHOR]

Automation of the distribution system may be an essential requirement in the smart grid architecture. In this paper, the architecture of the distribution system has been proposed, where Phasor Measurement Unit (PMU) has been placed at the main substation receiving supply from the grid through the incoming feeder, as well as at all distribution transformers (DTs). PMU installed at the main substation is linked to master controller through IEC 61850. PMUs placed at DTs are connected to the corresponding local controller through the IEC 61850. Estimated voltage and current phasors together with frequency are transmitted from PMU to the local controller through IEC 61850 communication protocol. Controllers perform different tasks based on the data received from PMUs. Each local controller is linked to master controller as well as to all smart meters placed at loads supplied by the DT. Bidirectional exchange of information takes place between master and local controllers as well as between local controller and smart meter. PMUs are also linked with the smart meters using PLC communication link. In this paper, information about the available power at the substation and at the distribution transformer is developed in real-time with the help of PMU by considering the load disconnection/connection based on available power (from time t = 0.56sec to time t = 0.75sec), protection of feeder against overcurrent (from time t = 0.15sec to time t = 0.20sec), and power theft detection and elimination (from time t = 0.21sec to time t = 0.23sec) through eMEGASim® OP5600 OPAL-RT real-time simulator. [ABSTRACT FROM AUTHOR]

Existing electricity smart meter data sets lack sufficient details on building parameters to evaluate the impact that home characteristics can have on electricity consumption. An extensive, open-source virtual smart meter (VSM) data set with corresponding building characteristics is provided. The methodology used to develop the VSM data is presented in detail. The data set consists of a variety of homes representative of a subset of the Canadian single-family home building stock. The building characteristics cover a wide range of values that are based on probability distributions developed using a segmentation and characterization process. The resulting framework and VSM data set can be used by researchers to develop classification models, verify load disaggregation algorithms, and for a variety of other purposes. [ABSTRACT FROM AUTHOR]

This paper analyses the stability issues of a multi-fed radial distribution network (RDN) by evaluating its states using a state-of-the-art technique under different operating condition. In its working principle, the entire RDN is visualized as a network comprising of N number of 2-bus sections cascaded sequentially. The required bus states are evaluated using the feed forward technique on the basis of the measurements from customized PMU(s) and smart meters (SMs) placed at suitable locations within the RDN. The inherent single iterative feature of the feed forward technique reduces the computational time leading toward the possibility of real time monitoring. The stability indices are evaluated based on these measured parameters for different case studies viz. normal, contingent, and faulty as well as inclusions and/or exclusions of renewables at different bus nodes conditions. The stability indices are also analyzed for inclusions and/or exclusions of renewables at different bus nodes. The findings of the analysis are summarized to propose the prediction about the abnormal running of the segment(s) of this multi-fed RDN in real time. The MATLAB simulation shows the nature of variation in voltage and power angle profiles of different buses with change in positions of DERs. [ABSTRACT FROM AUTHOR]

Now, Smart Energy Meters (SEMs) have become very popular in controlling and managing electricity consumption in residential, commercial, industrial sectors, to name a few. SEMs collects the fine-grained energy-consumption data at a regular time interval (every hour). Such a low sampling data rate can be useful in research, evaluating the higher consumption of electricity, etc. However, existing research work cannot adequately assess the qualitative, quantitative, and logical properties of the data that could theoretically improve the performance of classification and analytics. The purpose of this bibliometric analysis is to understand the reach of SEMs and its data analysis worldwide and across the various applications to make the concept clear for future researchers. The Scopus, Semantic Scholar and Crossref databases are used for performing the bibliometric analysis. This research study revealed that the insights of the SEMs data-enabled significant advancement in many fields such as energy consumption pattern analysis and prediction, demand response, load profiling, and direct-indirect phone charging analysis. [ABSTRACT FROM AUTHOR]

Integrating increasing shares of renewable electricity generation within the European Union electricity market requires that the electricity system is capable of withstanding intermittency. One of the principal means of achieving this is by activating the demand side in such a way as to enable a more flexible balance between demand and supply. In practice, initiatives and technological solutions to activate the demand side are well exemplified by smart meters, which collect and communicate information on electricity consumption. The existing legal framework and the 2016 legislative proposals for the electricity sector recognise that significant opportunities exist to utilise consumer data collected via smart metering and that these are of fundamental importance in creating more flexibility in the electricity market. However, the extensive utilisation of this data also raises questions concerning data privacy and data protection. This article examines the interface between data protection and energy law in the EU. The focus of the legal analysis is on the General Data Protection Regulation (GDPR) and the proposed rules contained in the Winter Package, which are systematically analysed to determine the conditions under which smart metering data can be utilised to further the objectives of EU energy law. The underlying argument of the article is that there is an apparent conflict between the objectives embedded in EU data protection law and those embedded in EU energy law. EU energy law addresses smart metering and the resulting data as means of achieving a more sustainable electricity system that benefits the final consumer. Conversely, EU data protection rules focus on the protection of a fundamental right and perceive the collection and processing of data as a risk to the very same consumer that is considered to benefit from smart metering data under EU energy law. This article demonstrates how this apparent conflict can be reconciled through interpretation of the relevant rules of EU law. [ABSTRACT FROM AUTHOR]

The modern utility system is faced with two main problems: how to minimize losses in a power system and how to locate the source of harmonic pollution. Namely, the utility has losses whenever the power it delivers is greater than the power it registers at the point of common coupling (PCC). In this paper we will show that these losses occur because the measurement equipment and billing policy are not adequate, and we will stress the reasons why this happens. The main reason is the distortion power generated by nonlinear loads. The number of these loads at power grid is greater every day, thus enlarging the problem. Ordinary power meters are not able to measure distortion power, so in this paper we will also show which small modifications to existing ordinary meters needed, which could lead to the successful detection of sources of harmonic pollution, thus further reducing power losses. The suggested idea will be verified by numerous simulations and measurements on different household/office and industry loads that are commonly used. The proposed method is suitable either for software or hardware upgrade of existing smart meters, or it can be implemented on ordinary measurement systems. [ABSTRACT FROM AUTHOR]

Implementing policies for sustainability transitions calls for actors that translate policy aims into practical solutions. This is particularly important in cases where policies require the application of new technologies. An example of such a policy is the requirement to install apartment-level water meters with the purpose of enabling fair invoicing and the saving of water. Economic incentives are expected to fulfil the objectives. In Finland, professional housing managers provide expert services that are crucial for implementing the policy requirements on metering in buildings. In this, they become middle actors between policy, technology, residents and their practices. In this study, the role of housing managers and their relationship to the different rationales that are used to justify decisions on apartment-level water metering is explored. The study shows that, although housing managers emphasize economic aspects, they also recognize technological and equity aspects. This raises questions of how middle actors should be considered in developing policies for sustainable housing. The results suggest that progress could be made by recognizing them in policy development and by raising their awareness as true intermediaries in advancing wider sustainability goals. [ABSTRACT FROM AUTHOR]

The rising demand for health and social care, and around the clock monitoring services, is increasing and are unsustainable under current care provisions. Consequently, a safe and independent living environment is hard to achieve; yet the detection of sudden or worsening changes in a patient's condition is vital for early intervention. The use of smart technologies in primary care delivery is increasing significantly. However, substantial research gaps remain in non-invasive and cost effective monitoring technologies. The inability to learn the unique characteristics of patients and their conditions seriously limits the effectiveness of most current solutions. The smart metering infrastructure provides new possibilities for a variety of applications that are unachievable using the traditional energy grid. By 2020, UK energy suppliers will install 50 million smart meters, therefore, providing access to a highly accurate sensing network. Each smart meter records the electrical load for a given property at 30 minute intervals. This granular data captures detailed habits and routines through the occupant's interactions with electrical devices, enabling the detection and identification of alterations in behaviour. The research presented in this paper explores how this data could be used to achieve a safe living environment for people living with progressive neurodegenerative disorders. [ABSTRACT FROM AUTHOR]

Despite a wealth of night remote sensing studies on electricity consumption, some unsolved issues limit future studies. These include the coarse resolution of nighttime light (NTL) imagery, the mismatching acquisition time between current NTL imagery and electric power data, and unknown data quality of public power records with a low update frequency and at a regional/national level. Thus, we attempt to address these well-known issues by using readings from smart meters. Such a new dataset provides high spatial and temporal resolution electricity consumption information, which enables the tracking of electricity consumption at the fine scale. To this end, all available NTL images from space and over eight million records of electric power consumption from ground smart meters with matching acquisition time were collectively employed for comprehensive examinations. Results of our analyses suggest two major findings. First, positive linear correlation exists between NTL images and smart meter readings at the pixel level. Second, their relationship is changing in different seasons, due to vegetation seasonality and snow cover. With the high update frequency of power consumption data from smart meters, these findings provide guidance for electricity consumption estimation at the fine-grained resolution, which will be informative and useful for local power planning. [ABSTRACT FROM AUTHOR]

Smart meters and in-home displays (IHDs) have been recently adopted to help give residential users more control over energy consumption, and meet environmental and supply security objectives. The article aims to identify the effectiveness and potential of smart meters and real-time IHDs in reducing Shanghai household energy consumption by affecting occupants' behaviour. A general landscape of the occupant behaviour in residential buildings was briefly painted. A pilot study in Shanghai with an effective sample of 131 respondents was arranged into two groups as IHD and non-IHD households. A dedicated statistical analysis model was developed based on the micro-level empirical data to investigate the characteristics and the regulations of electricity consumption in these two groups, such as check frequency, electricity consumption reduction and shifting, energy bill saving, and standby power. The research results demonstrate that IHDs could lead to around 9.1% reduction in monthly electricity consumption and about 11.0% cut off in monthly electricity bills. A general comparison of the electricity consumption reduction between this research and the average UK case was further made. Barriers at current stage and challenges for further work were finally discussed. The statistical model is expected to 'future proof' smart meter and real-time displays through macro-level designing in modularity and flexibility in China. The overall research initially proves the concept of the feasible impact of smart meter and display technologies in the Chinese context, which is further expected to contribute to the empirical evidence on how IHD feedback could influence household electricity consumption in the Chinese context. [ABSTRACT FROM AUTHOR]

The aims of this commentary are to generate thought and discussion about the potential role and value of energy feedback in future energy transitions. There is now a global research and policy effort devoted to developing energy feedback (e.g. from improved bills, metering or displays) in order to change energy-use behaviour and reduce demand. Within this, calls to go beyond conventional energy feedback through the use of disaggregation are increasingly common. An alternative approach is presented for how to go beyond energy feedback. Instead of focusing solely on generating larger energy savings, it is argued that new approaches need to consider how conventional energy feedback frames energy problems and shapes the agency and engagement of different actors. Three potential routes are highlighted for going beyond conventional approaches to energy feedback through emerging work on practice feedback, policy feedback and speculative design. Three core challenges for future work on energy feedback are: recognizing the multiple forms of energy-related feedback that shape everyday life; engaging with a much wider range of actors involved in shaping energy feedback loops; and using new approaches to energy-related feedback to reframe energy problems and establish new roles for actors engaged in energy transitions. [ABSTRACT FROM AUTHOR]

Energy-feedback tools are commonly used to promote energy saving. In the UK, energy-feedback provision (currently via an in-home display) is part of the government-mandated roll-out of smart meters to all homes by 2020. A core assumption underlying this widespread provision is that information, or evidence, can lead to positive changes in action. This is analogous to assumptions underlying the notion of 'evidence-based policy', and raises questions about how users, researchers and policy-makers go about using evidence when aiming for a 'successful' outcome. In addition, the 'policy feedback' research agenda has asked how policies alter the landscapes within which they operate by, for example, affecting relationships between actors. Via an in-depth review of Department of Energy and Climate Change (DECC) policy literature over 2010-16, the UK smart meter roll-out was analysed in terms of how its energy-feedbackfocused measures may be deemed as 'successful'. Findings include the fact that direct energy savings played a smaller role than might be expected, and translation from one success measure to another was repeatedly observed. A key conclusion is that acting on feedback requires an assessment of success, but such assessment is highly contextual, for consumers and policymakers alike. Ways to increase reflexivity in this area are discussed. [ABSTRACT FROM AUTHOR]

Different data visualizations are investigated for how they enable occupants to learn about domestic energy consumption. Smart metering can potentially encourage householders to change their behaviour and save energy. However, concerns exist about whether users understand domestic energy feedback. Two challenges are addressed: feedback displays typically show aggregate consumption and they show time-series data visualizations, which are difficult to relate to everyday actions in the household. A laboratory experiment (N = 43) assessed changes in participants' knowledge of how much electricity everyday actions consume after being exposed to different forms of energy-consumption data visualizations: (1) an aggregated time-series line graph, (2) a disaggregated time-series line graph and (3) a normalized disaggregated visualization that deemphasized time. Participants played an energy game both before and after they saw the simulation. Participants in condition (3) were more accurate and more confident in their post-test judgments about everyday domestic electricity consumption than other participants. These findings suggest that the type of data visualization affects users' understanding of domestic electricity consumption. The visualization of disaggregated energy feedback at the appliance level should be considered for future generations of technology. [ABSTRACT FROM AUTHOR]

This study aims to understand factors influencing the intention to adopt smart meters (SM) to save energy in the face of expected increases in electricity costs, stemming from the impact of Taiwan’s plans to increase the proportion of renewable energy in the post-Fukushima era demand. As far as we know, compared to previous relevant studies based on constructs of perceived usefulness, perceived ease of use, and attitudes, this study is the first one based on the application of protection motivation theory (PMT), which uses threat appraisal, coping appraisal, Social Influence, Secondary Data Influence constructs, and control variables to explain the correlation and impact of residential communities’ intention to adopt SM. With 292 valid questionnaires, this study applies SmartPLS 3 software in model analysis, and finds that the impact of coping appraisal variables is more significant than that of threat appraisal variables, while Secondary Data Influence, Age, and Electricity Cost variables have a significant influence on the intention to adopt SM. The relevant results and practical contributions are discussed. [ABSTRACT FROM PUBLISHER]

Environmental drivers have led to rapid uptake of residential photovoltaic (PV) systems in many parts of the world. PV intermittency and unpredictability have presented new challenges to the electricity generation, transmission and distribution sectors. The outputs of these residential PV systems cannot be determined by their DC rating alone, but are dependent on a number of installation and environmental parameters. A model of PV kW output in response to solar irradiance and temperature has been developed without the need for detailed experimentation and testing of individual PV units. Accuracy of the proposed model has been verified and its potential applications for electricity distribution networks are demonstrated. [ABSTRACT FROM AUTHOR]

For this special issue, we invite contributions that make a strong methodological contribution by highlighting the innovations and challenges of conducting research on technology in home environments. The past few years have seen a rapid increase in the number and variety of technologies embedded in and passing through home environments. [Extracted from the article]

The smart metering systems currently being installed in UK households support devices that give feedback aimed at encouraging behaviour changes, specifically to reduce energy demand and spending on energy. Detailed standards specify the minimum technical capabilities of the smart meters and feedback devices. In this paper, we assess the extent to which these standards enable feedback that is likely to be effective in reducing demand. Latest research in this field, drawing on theories of social practice, suggests that feedback devices assume and rely on what we term ‘reflection practice’, a distinctive type of social practice, and that feedback attentive to the particular energy-using practices of householders is likely to have most influence on demand. Neither the smart meter standards nor current commercial devices are found to incorporate these latest research findings, potentially significantly limiting the ability of the UK smart metering programme to fulfil its domestic energy demand reduction objectives. [ABSTRACT FROM PUBLISHER]

Although smart meters for electricity have received widespread acclaim as a means to achieve more resilient and sustainable electricity consumption, public opposition has emerged in several countries. In this article, I examine the reasons for public opposition in North America and the role of concern with health risks. The article provides an analysis of reasons given for opposing smart meters by 75 US and Canadian organisations listed in the 2013 EMF (electromagnetic field) Safety Network, a review of all news reports (499) in the Lexis-Nexis database relating to smart meters in seven US states and one Canadian province from 2010 to 2013 and case studies of policy responses in the same seven states and province. Thirty-one of the organisations in the EMF network focused mainly on health concerns about EMFs, and 44 organisations identified broader concerns as well as health risks. The more politically conservative groups focused on issues relating to privacy and government intrusion. Newspaper reports also identified health risks, although they also identified issues relating to cost overruns and privacy. The study of newspaper reporting in the seven US states and one Canadian province indicated that relevant agencies had responded to public concerns by developing opt-out provisions for meter installation, in some cases after protracted public campaigns. I consider possible patterns of opposition for future investigation: opposition may be higher where the roll-out of smart meters is rapid and without an opt-out provision; technological differences (for example, wired versus wireless) may contribute to levels of public opposition; and challengers to incumbent parties of either the right or left may also contribute to public opposition. In the ‘Conclusion’ section, I compare two policy strategies, one of which views public opposition as a lack of good communication from utilities, and the other which views it as an opportunity for innovation in systems design and improvements in governance policies. [ABSTRACT FROM AUTHOR]

This paper introduces Smart Grid and associated technical, environmental and socio-economic, and other non-tangible benefits to society, and articulates the need for the concept and the fact that it is a dynamic interactive, real-time infrastructure that responds to the challenges of designing and building the power system of the future, rather than being simply a marketing term. To illustrate the diversity of terminology, the paper compares an Electric Power Research Institute (EPRI) definition with that suggested by a study group of the International Electrotechnical Commission (IEC). Next, a paper sponsored by the Canadian Electricity Association (CEA) that cites three example definitions to highlight the diversity of views of Smart Grid is briefly reviewed. Early misconceptions and characterizations of Smart Grid are discussed as a prelude to addressing challenging issues that motivate developing and implementing related innovative technologies, products and services. The paper then discusses the potential promise of the Smart Grid, which is embedded in its often-cited attributes of efficiency, accommodating, quality focus, enabling and self-healing to name some. The paper then addresses some of the often-cited impediments to accepting Smart Grid which are based on concerns and issues confronting its forward progress, adoption and acceptance. Distribution Automation (DA) and embedded intelligence are discussed emphasising self-healing, optimizing operation and facilitating recreation and recovery from abnormal events. Functional and integration requirements of Distributed Energy Resources (DER,) are detailed. Smart Consumption Infrastructure elements of Distribution Management Systems (DMS,) Automated Metering Infrastructure (AMI,) Smart Homes (SH), and Smart Appliances (SA,) are discussed. Following the introductory section, this paper summarizes contributions included in the double issue 42(3–4) of the Electric Power Components and Systems Journal. To begin, papers are offered discussing smart grid activities in China, India, and the development of a Smart Grid roadmap for the US State of Kentucky. The approaches of each of these cases reflect the diversity of policy initiatives in these jurisdictions. Two state of the art reviews are given next. The first considers distribution network active management and future development trends in technologies and methods, where centralized and decentralized management frameworks and applying agent-based coordination are discussed. The second offers a review of smart home technologies and the goals of an energy management system (SHEMS). This section is concluded by a letter providing an overview of recent and expected advances nanotechnology applications in Smart Grid. Following the state of the art review section, ten papers offering new and innovative research approaches and results are included. These papers cover Smart Grid topics such as real-time energy control approach for smart home energy management systems, optimal operation of energy- efficient buildings with Combined Heat and Power (CHP) systems, energy management and control of Electric Vehicle (EV) charging stations, voltage-frequency control of a voltage source inverter (VSI) in a smart islanded microgrid, smart generation scheduling for wind-thermal-pumped storage systems, optimized power system restoration, robust data transmission upon compressive sensing, data fusion for wide-area oscillation monitoring, satellite based GPS synchronized monitoring systems, stability in Smart Grid with emerging renewable energy techno- logies. [ABSTRACT FROM PUBLISHER]

Residential households have the potential to conserve water, especially in behaviourally influenced end uses such as showering. Visual display monitors detailing shower water consumption parameters provide householders with a better understanding of their water use consumption and serve as a prompt to conserve. This longitudinal study first applied high resolution smart meters to create a registry of shower end use event parameters (i.e. shower duration, flow rate and duration) before and after the introduction of an alarming visual display monitor. The study showed a statistically significant mean reduction of 15.40 L (27%) in shower event volumes shortly after the implementation of the shower monitor. However, two subsequent smart metering reads indicated that shower end use water consumption savings diminished over time and mean showering volumes reverted back to their pre-intervention level after 4 months. That is, the longitudinal study provides empirical evidence that technological devices informing resource consumption may not be effective unless instilled habits or attitudes can be also modified; old habits die hard. Follow-up questionnaire surveys allowed for qualitative interpretations of the behavioural findings, through demographic summaries, residents' perceptions on shower monitor performance and their use of device over time, to name a few. [ABSTRACT FROM AUTHOR]

The Smart Meter Implementation Programme is the Government's flagship energy policy. In its search for solutions to address privacy dilemmas raised by smart meters, the Government has been content with using data protection principles as a policy framework to regulate the processing of consumers' personal information. This is worrying since the question ofwhohas access towhattype of information andhowit is used cannot simply be regarded as raising information security, authenticity and integrity issues. If we are to go beyond the rhetoric of protecting the privacy rights of energy consumers we must scrutinise the context in which legitimate interests and reasonable expectations of privacy subsist. To remedy this apparent policy oversight, the paper undertakes two tasks: first, to clarify the content and application of data protection and privacy rights to smart meters; and second, it outlines a policy framework that will address the lack of specificity on how best innovation and privacy issues can be better calibrated. More importantly, it calls for targeted substantive reforms, development of accessible privacy policies and information management practices that promote transparency and accountability and deployment of technological solutions that will help reduce emerging fault lines between innovation and privacy in this sphere of energy policymaking. [ABSTRACT FROM AUTHOR]

Australia's residential peak electricity demand is escalating rapidly and causing major distribution and generation challenges for the industry. This rise is largely attributed to converging and rising expectations of comfort in the home, which are being satisfied by Australians' increasing reliance on air-conditioning. Residential demand-management strategies seek to address this by either actively managing consumer demand, or encouraging consumers to act as co-managers of their demand, during peak times. Drawing on interviews with demand-management practitioners from electricity distributors and retailers, the impact of several residential demand-management techniques is considered in relation to comfort expectations. It is argued that utilities delivering demand-management trials are shaping, and being shaped by, 'normal' expectations of comfort. Further social research is called for to assess the impact of demand-management techniques on escalating comfort expectations, and to design and implement strategies that address this fundamental issue. En Australie, le pic de la demande d'electricite residentielle augmente rapidement, provoque des perturbations importantes et est a l'origine de difficultes pour l'industrie. Cette augmentation est due, en grande partie, a la convergence et a de nouvelles attentes en matiere de confort au foyer qui sont satisfaites par une dependance de plus en plus importante des Australiens vis-a-vis de la climatisation. Les strategies de gestion de la demande d'electricite residentielle cherchent a relever ces defis soit en gerant de maniere active la demande des consommateurs soit en encourageant ces derniers a agir comme des co-gestionnaires de la demande pendant les heures de pointe. S'appuyant sur des interviews de specialistes de la gestion de la demande des distributeurs d'electricite et des detaillants, l'auteur analyse l'impact de plusieurs techniques de gestion de la demande d'electricite residentielle par rapport aux attentes des consommateurs en matiere de confort. Il ressort de cette etude que les services proposant des essais de gestion de la demande donnent forme aux attentes normales en matiere de confort mais sont aussi formes par ces dernieres. Il est necessaire de mener d'autres recherches sur le plan social pour evaluer l'impact des techniques de gestion de la demande sur l'augmentation des attentes en matiere de confort et de concevoir et mettre en œuvre des strategies pour resoudre cette question fondamentale. comportement adaptatif, climatisation, changement climatique, confort, gestion de la demande, qualite de l'environnement interieur, habitants, pic de la demande, consommation d'energie residentielle, compteurs intelligents [ABSTRACT FROM AUTHOR]