Metering data from the advanced metering infrastructure can be used to find abnormal electricity behavior for the detection of electricity theft, which causes huge financial losses to electric ...companies every year. This article proposes an electricity theft detector using metering data based on extreme gradient boosting (XGBoost). The metering data are preprocessed, including recover missing and erroneous values and normalization. The classification model based on XGBoost is trained using both benign and malicious samples. Simulations are done by using the Irish Smart Energy Trails data set with six certain attack types. Compared with the support vector machine, decision tree, and other eight machine learning methods, the proposed method can detect electricity theft with either higher accuracy or lower false-positive rate. Experiment results also demonstrate that the proposed method is robust when the data are imbalanced. Our codes are available at https://github.com/WenHe-Hnu/Electric_Theft_XGBoost .
Smart meters have been deployed in many countries across the world since early 2000s. The smart meter as a key element for the smart grid is expected to provide economic, social, and environmental ...benefits for multiple stakeholders. There has been much debate over the real values of smart meters. One of the key factors that will determine the success of smart meters is smart meter data analytics, which deals with data acquisition, transmission, processing, and interpretation that bring benefits to all stakeholders. This paper presents a comprehensive survey of smart electricity meters and their utilization focusing on key aspects of the metering process, different stakeholder interests, and the technologies used to satisfy stakeholder interests. Furthermore, the paper highlights challenges as well as opportunities arising due to the advent of big data and the increasing popularity of cloud environments.
The traditional and estimated billing system of electric energy consumed in most part of Sub-Saharan Africa has become a lingering issue to the electricity consumers. This has therefore necessitated ...the advent of smart electric meters. In this work, we propose a smart electric meter reader that provides an efficient and economically viable technique for measuring the consumption of electricity. This proposed method tends to solve many issues of the traditional reading system, such as reading efficiency, accuracy, and the elimination of human interface. Our proposed method, consisting of a GSM module, is used to wirelessly communicate the smart meter readings to the electricity provider and the consumer in form of a text message. The results obtained from the evaluation of this work show that our proposed method has improved the accuracy of the meter reading process for proper accountability.
Reducing the energy requirements of buildings is essential in order to address anthropogenic global warming. Among the various factors affecting the energy requirements of buildings, the thermal ...transmittance of the walls is critical in understanding heat loss. It is therefore necessary to assess the thermal transmittances carefully in order to develop effective means of energy conservation. Although various theoretical methods and methods using in situ measurements are available for this purpose, the correct use of such methods depends on many factors. In a detailed review of more than 150 publications (scientific papers, congress reports, books, and other documents), the best-developed methods in use by researchers and professionals are analysed. These methods are as follows: the theoretical method, the heat flow meter method, the simple hot box-heat flow meter method, the thermometric method, and the quantitative infrared thermography method. This review is intended to be a useful resource for researchers and professionals in that it covers the fundamental theoretical background, the equipment and material required for in situ measurements, the criteria for installing the equipment, the errors caused by metrological and environmental aspects, data acquisition, data processing, and data analysis.
•Theoretical fundamentals of assessment methods of thermal transmittance.•Analysis of the benefits and limitations of the different assessment methods.•Acquisition, post-processing and data analysis for the different methods.
In smart grids, smart meters may potentially be attacked or compromised to cause certain security risks. It is challenging to identify malicious meters when there are a large number of users. In this ...paper, we explore the malicious meter inspection (MMI) problem in neighborhood area smart grids. We propose a suite of inspection algorithms in a progressive manner. First, we present a basic scanning method, which takes linear time to accomplish inspection. The scanning method is efficient when the malicious meter ratio is high. Then, we propose a binary-tree-based inspection algorithm, which performs better than scanning when the malicious meter ratio is low. Finally, we employ an adaptive-tree-based algorithm, which leverages advantages of both the scanning and binary-tree inspections. Our approaches are tailored to fit both static and dynamic situations. The theoretical and experimental results have shown the effectiveness of the adaptive tree approach.
Zusammenfassung
Im Zuge der Digitalisierung der Energiewende sind bei der 50Hertz Transmission GmbH (50Hertz) die erforderlichen Systeme installiert worden, mit denen die Daten in der Marktrolle ...Übertragungsnetzbetreiber (ÜNB) erfasst und ausgewertet werden können. In Zusammenarbeit zwischen dem Fraunhofer IFF und der 50Hertz wurde untersucht, inwieweit die Systeme für das Datenaufkommen im Realbetrieb bereits vorbereitet sind. Innerhalb dieses Beitrags wird die Methodik zur Untersuchung vorgestellt. Hierbei wurden sowohl die Marktkommunikation 2020 (MaKo 2020) als auch die direkte Smart-Meter-Gateway-Kommunikation untersucht. Die Ergebnisse sowie erforderlichen Maßnahmen zur Anpassung der Systeme werden präsentiert.
Demand decomposition (disaggregation) presents the process of assessing time-varying participation of different load categories within the total active or reactive load. Information on load ...composition is highly beneficial for different demand side management applications. In order to decompose total forecasted load of aggregated households where only some are monitored by smart meters (SMs) with submetering capabilities, a two-level methodology is proposed. At the first level, load disaggregation of the load monitored by SMs is done based on measurements of power consumed by each home appliance, and at the second, the disaggregation of the total forecasted load is performed using artificial neural network. This paper investigates the required percentage of users in an aggregation that should be equipped with a SM with submetering capabilities in order to forecast (within certain confidence level) the load composition of the overall aggregated demand. The methodology was first tested on a UK statistics-based load model, and then validated on a real pilot site's consumption dataset. The results show that even with 5% SM coverage, one can forecast, with high confidence, the composition of the load at the substation (aggregation point). In other words, there is no techno-economic justification for submetering technologies to be installed at every user's premise; a limited installation of such devices would suffice.
There are strong links between music and mathematics dating back to Pythagoras and beyond. This book draws together the two disciplines outlining the key methods and concepts that underpin the ...subjects from one of the earliest uses of a musical cryptogram to computer music in the twenty-first century. Maths and Music is divided into sections, each one exploring a different mathematical aspect of music: rhythm; symmetry; scales; form and structure; and finally some musical curiosities. Musical examples are taken from across the world, from ancient and medieval music through to popular music of the twenty-first century. In all, the book covers over 200 pieces of music ranging from classical symphonies to electronic dance music with numerous musical excerpts given. There are clear explanations throughout along with glossaries of musical and mathematical terms.
Residential natural gas meter set assemblies (MSAs) emit methane (CH4), but reported emissions factors vary. To test existing emissions factors, we quantified CH4 emissions from 37 residential MSAs ...in Calgary, Alberta, Canada. A notable difference with previous studies is the targeted measurement of regulator vents in this study, which were measured with a static chamber, while fugitives were measured with a modified hi-flow sampler. Emissions were dominated by pressure regulator vents (emissions factor = 1.18 g CH4/h/MSA), but 7 fugitives were found (emissions factor = 0.018 g CH4/h/MSA). Six regulator vents were emitting at notably higher rates (≥ 1.79 g CH4/h/MSA). The total empirical emissions factor was 1.20 g CH4/h/MSA (95 % CI, 1.03 to 1.37 g/h/MSA). This is ∼7 times higher than the emissions factor for residential MSAs used in the U.S. EPA's Greenhouse Gas Inventory, which may not include emissions from regulator vents. Upscaling to annual CH4 emissions in Calgary indicates 3234.6 t CH4/yr (95 % CI, 2776.4 t to 3692.9 t CH4/yr) could be emitted from MSAs. This is equivalent to 4.1 % (95 % CI, 3.5 % to 4.7 %) of total city-level CH4 emissions as estimated with satellite data. Results suggest residential MSA emissions may be under-estimated and further study isolating root causes of regulator vent emissions is required to guide mitigation and improve emissions modeling.
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•Regulator vents on residential meters may emit methane by design but are understudied.•We fit close-range measurement methods to vent and fugitive emissions on the meters.•All regulator vents were emitting methane and dominated total meter emissions.•The total meter emissions factor derived from our measurements was 1.20 g CH4/h.•Understanding the mechanisms behind regulator emissions could accelerate mitigation.
The recent advent of smart meters has led to large micro-level datasets. For the first time, the electricity consumption at individual sites is available on a near real-time basis. Efficient ...management of energy resources, electric utilities, and transmission grids, can be greatly facilitated by harnessing the potential of this data. The aim of this study is to generate probability density estimates for consumption recorded by individual smart meters. Such estimates can assist decision making by helping consumers identify and minimize their excess electricity usage, especially during peak times. For suppliers, these estimates can be used to devise innovative time-of-use pricing strategies aimed at their target consumers. We consider methods based on conditional kernel density (CKD) estimation with the incorporation of a decay parameter. The methods capture the seasonality in consumption, and enable a nonparametric estimation of its conditional density. Using 8 months of half-hourly data for 1000 meterswe evaluate point and density forecasts, for lead times ranging from one half-hour up to a week ahead. We find that the kernel-based methods outperform a simple benchmark method that does not account for seasonality, and compare well with an exponential smoothing method that we use as a sophisticated benchmark. To gauge the financial impact, we use density estimates of consumption to derive prediction intervals of electricity cost for different time-of-use tariffs. We show that a simple strategy of switching between different tariffs, based on a comparison of cost densities, delivers significant cost savings for the great majority of consumers.
•We generate density forecasts for electricity consumption recorded by smart meters.•Methods based on Conditional Kernel Density (CKD) estimation are considered.•CKD methods can accommodate the seasonality in consumption time series.•We derive prediction interval of electricity cost for different time-of-use tariffs.•Switching between tariffs based on a comparison of cost densities delivers savings.
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