Non-technical loss and power blackout detection under advanced metering infrastructure using a cooperative game based inference mechanism

Tung-Sheng Zhan; Shi-Jaw Chen; Chih-Cheng Kao; Chao-Lin Kuo; Jian-Liung Chen; Chia-Hung Lin

Non-technical loss and power blackout detection under advanced metering infrastructure using a cooperative game based inference mechanism

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Author(s): Tung-Sheng Zhan ¹ ; Shi-Jaw Chen ² ; Chih-Cheng Kao ³ ; Chao-Lin Kuo ¹ ; Jian-Liung Chen ¹ ; Chia-Hung Lin ¹
- Affiliations: 1: Department of Electrical Engineering, Kao-Yuan University, Lu-Chu District, Kaohsiung City, 82151, Taiwan ;
  2: Department of Greenergy Science and Technology, Kao-Yuan University, Lu-Chu District, Kaohsiung City, 82151, Taiwan ;
  3: Department of Maritime Information and Technology, National Kaohsiung Marine University, Cijin District, Kaohsiung City, 80543, Taiwan
Source: Volume 10, Issue 4, 10 March 2016, p. 873 – 882
DOI: 10.1049/iet-gtd.2015.0003 , Print ISSN 1751-8687, Online ISSN 1751-8695

Received 07/01/2015, Accepted 22/10/2015, Revised 19/09/2015, Published 10/03/2016

To efficiently detect non-technical loss and power blackout in micro-distribution systems, this study proposes using a cooperative game (CG) based inference mechanism under the advanced metering infrastructure technique. Fractional-order Sprott system is designed to extract specific features between the profiled usages and the measurement usages in real time analysis. The fractional-order dynamic errors are positive correlated with the changes in load usages, including normal conditions, electricity fraudulent events, and power blackout events. Then, multiple agents in a game and multiple CG based inference mechanisms are used to locate abnormalities in micro-distribution systems. For energy management applications, the proposed inference mechanism can identify the 2.5–20% irregular usages during normal demand operations. In addition, it can also identify the large changes >20% in usages, while a micro-distribution system is disconnected to operate in the islanded mode within a few hours. This function can address an outage occurrence and then quickly resume service using the service restoration strategy and distributed generations in a local grid. Using a medium-scale micro-distribution system, computer simulations are conducted to show the effectiveness of the proposed inference model.

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Non-technical loss and power blackout detection under advanced metering infrastructure using a cooperative game based inference mechanism

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