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Amir Mehdi Pasdar

Bio: Amir Mehdi Pasdar is an academic researcher from University of Akron. The author has contributed to research in topics: Computer science & Power-line communication. The author has an hindex of 7, co-authored 14 publications receiving 177 citations. Previous affiliations of Amir Mehdi Pasdar include Iran University of Science and Technology.

Papers
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Proceedings ArticleDOI
24 Sep 2007
TL;DR: Smart meter detection system for detect illegal usage of electricity may be easily added to distribution network by sending test signal at high frequency in network and software calculates line impedance that connect each two energy meters.
Abstract: Power line carrier communication presents new area for automatic meter reading, by equipped energy meter with power line system all user connect each other with this communication method, Smart metering uses all potential of this communication channel to presents new service in low voltage distribution grid, by installing smart meter detection system for detect illegal usage of electricity may be easily added to distribution network, in this method by sending test signal at high frequency in network, software calculates line impedance that connect each two energy meters, by comparing the data that related to installation time with other times data, system can find and locate place of illegal usage of electricity.

61 citations

Journal ArticleDOI
TL;DR: An on-line method for detecting and locating a faulty node in the utility grid is proposed for smart grids based on injection of high frequency (A-Band) current signal into the grid that would impose voltages on the nodes to determine changes in the impedance characteristics.
Abstract: An on-line method for detecting and locating a faulty node in the utility grid is proposed for smart grids. The method is based on injection of high frequency (A-Band) current signal into the grid that would impose voltages (less than 1V according to EN50065-1 standard) on the nodes to determine changes in the impedance characteristics. This detection is accomplished on-line without interrupting the power flow in the network. The developed algorithm has been implemented within an electrical power system model. This low voltage network model has been tested with different fault scenarios. The proposed procedure is able to detect the faulty nodes with high accuracy.

36 citations

Journal ArticleDOI
TL;DR: In this paper, the problem of current balancing in a three-phase, lowvoltage distribution network was studied, where each meter reports the customer consumption and local current/voltage data to the central station at specified intervals.

26 citations

Proceedings ArticleDOI
18 May 2009
TL;DR: In this paper, an intelligent current balancing technique in smart meters enhances grid balancing based on statistical information of low voltage network that each smart meter gathers periodically, where each meter is connected to a central station via existing power lines.
Abstract: Power line carrier technique often is used in automatic meter reading systems and presents new area for communication. In this method each meter is connected to a central station via existing power lines. In low voltage distribution systems one of the most problematic issues is three phase current balancing. Applying intelligent current balancing technique in smart meters enhances grid balancing based on statistical information of low voltage network that each smart meter gathers periodically.

18 citations

Journal ArticleDOI
TL;DR: In this paper, an s-domain home power-line impedance model estimation method at the Federal Communications Commission band based on impedance signatures of the loads and cables as well as the load schedules is developed.
Abstract: Power-line communication (PLC) systems use the existing power line as a communication channel between the nodes. Understanding the high-frequency behavior of the power line and loads at the PLC frequency band is essential for designing the PLC system to achieve the desired performance. Based on the impedance behavior of the channel, PLC transceivers can adaptively adjust their operating behaviors to operate more effectively and efficiently. Tracking the impedance variation would also enable smart-grid systems to implement channel health monitoring. In this research, an s-domain home power-line impedance model estimation method at the Federal Communications Commission band based on impedance signatures of the loads and cables as well as the load schedules is developed. The model contains the amplitude and phase characteristics of the impedance at the FCC band. The presented home appliance signature contains an s-domain impedance model and complex power consumption at the power-line frequency. Measurements have been made for nine different appliances and a standard cable with proper lengths is typically used in US homes in order to define their high-frequency impedance signatures. The performance of the status detection algorithm is tested for five different scenarios. Based on the experimental tests, we found that the method we proposed for detecting the working status of the appliances and the method for estimating PLC channel impedance works very accurately.

16 citations


Cited by
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Proceedings ArticleDOI
04 Nov 2010
TL;DR: A distributed incremental data aggregation approach, in which data aggregation is performed at all smart meters involved in routing the data from the source meter to the collector unit, which is especially suitable for smart grids with repetitive routine data aggregation tasks.
Abstract: In this paper, we present a distributed incremental data aggregation approach, in which data aggregation is performed at all smart meters involved in routing the data from the source meter to the collector unit. With a carefully constructed aggregation tree, the aggregation route covers the entire local neighborhood or any arbitrary set of designated nodes with minimum overhead. To protect user privacy, homomorphic encryption is used to secure the data en route. Therefore, all the meters participate in the aggregation, without seeing any intermediate or final result. In this way, our approach supports efficient data aggregation in smart grids, while fully protecting user privacy. This approach is especially suitable for smart grids with repetitive routine data aggregation tasks.

552 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a comprehensive study on Smart Grid and the role of Advanced Metering Infrastructure (AMI) in SG, which is not a single technology; rather it is a combination of different areas of engineering, communication and management.

487 citations

Journal ArticleDOI
TL;DR: In this paper, the authors proposed an architectural design of smart meter, external control station, harmonic generator, and filter circuit to deject illegal consumers, and conserve and effectively utilize energy, where smart meters are designed to provide data of various parameters related to instantaneous power consumption.

286 citations

Proceedings ArticleDOI
20 Mar 2011
TL;DR: The problems underlying detection of electricity theft, previously implemented ways for reducing theft and the approximate energy consumption patterns of several customers involving theft are discussed.
Abstract: Most utility companies in developing countries are subjected to major financial losses because of non-technical losses (NTL). It is very difficult to detect and control potential causes of NTL in developing countries due to the poor infrastructure. Electricity theft and billing irregularities form the main portion of NTL. These losses affect quality of supply, electrical load on the generating station and tariffs imposed on electricity consumed by genuine customers. In light of these issues, this paper discusses the problems underlying detection of electricity theft, previously implemented ways for reducing theft. In addition, it presents the approximate energy consumption patterns of several customers involving theft. Energy consumption patterns of customers are compared with and without the presence of theft. A dataset of customer energy consumption pattern is developed based on the historical data. Then, support vector machines (SVMs) are trained with the data collected from smart meters, that represents all possible forms of theft and are tested on several customers. This data is classified based on rules and the suspicious energy consumption profiles are grouped. The classification results of electricity consumption data are also presented.

168 citations

Journal ArticleDOI
TL;DR: A typology for the categorization of solutions for detection of non-technical losses is proposed and the sources and possible attack/vulnerability points are identified.
Abstract: This paper is a review of literature with an analysis on a selection of scientific studies for detection of non-technical losses. Non-technical losses occurring in the electric grid at level of transmission or of distribution have negative impact on economies, affecting utilities, paying consumers and states. The paper is concerned with the lines of research pursued, the main techniques used and the limitations on current solutions. Also, a typology for the categorization of solutions for detection of non-technical losses is proposed and the sources and possible attack/vulnerability points are identified. The selected literature covers a wide range of solutions associated with non-technical losses. Of the 103 selected studies, 6 are theoretical, 25 propose hardware solutions and 72 propose non-hardware solutions. Data based classification models and data from consumption with high resolution are respectively required in about 47% and 35% of the reported solutions. Available solutions cover a wide range of cases, with the main limitation found being the lack of an unified solution, which enables the detection of all kinds of non-technical losses.

121 citations