Consumer load prediction and theft detection on distribution network using autoregressive model

Load prediction is essential for the planning and management of electric power system and this has been an area of research interest recently. Various load forecasting techniques have been proposed to predict consumer load which represents the activities of the consumer on the distribution network....

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Main Authors:	Abdullateef, Adoyele Isqeel, Salami, Momoh Jimoh Eyiomika, Ahmed, Musse Mohamud, Onasanya, Mobolaji Agbolade
Format:	Article
Language:	English
Published:	International Journal of Scientific & Engineering Research 2013
Subjects:	TK3001 Distribution or transmission of electric power. The electric power circuit
Online Access:	http://irep.iium.edu.my/36065/ http://irep.iium.edu.my/36065/ http://irep.iium.edu.my/36065/1/Consumer-Load-Prediction-and-Theft-Detection-on-Distribution.pdf

id	iium-36065
recordtype	eprints
spelling	iium-360652014-03-17T02:14:49Z http://irep.iium.edu.my/36065/ Consumer load prediction and theft detection on distribution network using autoregressive model Abdullateef, Adoyele Isqeel Salami, Momoh Jimoh Eyiomika Ahmed, Musse Mohamud Onasanya, Mobolaji Agbolade TK3001 Distribution or transmission of electric power. The electric power circuit Load prediction is essential for the planning and management of electric power system and this has been an area of research interest recently. Various load forecasting techniques have been proposed to predict consumer load which represents the activities of the consumer on the distribution network. Commonly, these techniques use cumulative energy consumption data of various consumers connected to the power system to predict consumer load. However, this data fails to reveal the activities of individual consumers as related to energy consumption and stealing of electricity. A new approach of predicting consumer load and detecting electricity theft based on autoregressive model technique is proposed in this paper. The objective is to evaluate the relationship between the consumer load consumption vis-a-vis the model coefficients and model order selection. Such evaluation will facilitate effective monitoring of the individual consumer behaviour, which will be indicated in the changes in model parameters and invariably lead to detection of electricity theft on the part of the consumer. The study used the data acquired from consumer load prototype which represents a typical individual consumer connected to the distribution network. Average energy consumption obtained over 24 hours was used for the modelling and 5-minute step ahead load prediction based on model order 20 of minimum description length criterion technique was achieved. Electricity theft activities were detected whenever there are disparities in the model coefficients and consumer load data. International Journal of Scientific & Engineering Research 2013-12 Article PeerReviewed application/pdf en http://irep.iium.edu.my/36065/1/Consumer-Load-Prediction-and-Theft-Detection-on-Distribution.pdf Abdullateef, Adoyele Isqeel and Salami, Momoh Jimoh Eyiomika and Ahmed, Musse Mohamud and Onasanya, Mobolaji Agbolade (2013) Consumer load prediction and theft detection on distribution network using autoregressive model. International Journal of Scientific & Engineering Research, 4 (12). pp. 1609-1615. ISSN 2229-5518 http://www.ijser.org/onlineResearchPaperViewer.aspx?Consumer-Load-Prediction-and-Theft-Detection-on-Distribution.pdf
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TK3001 Distribution or transmission of electric power. The electric power circuit
spellingShingle	TK3001 Distribution or transmission of electric power. The electric power circuit Abdullateef, Adoyele Isqeel Salami, Momoh Jimoh Eyiomika Ahmed, Musse Mohamud Onasanya, Mobolaji Agbolade Consumer load prediction and theft detection on distribution network using autoregressive model
description	Load prediction is essential for the planning and management of electric power system and this has been an area of research interest recently. Various load forecasting techniques have been proposed to predict consumer load which represents the activities of the consumer on the distribution network. Commonly, these techniques use cumulative energy consumption data of various consumers connected to the power system to predict consumer load. However, this data fails to reveal the activities of individual consumers as related to energy consumption and stealing of electricity. A new approach of predicting consumer load and detecting electricity theft based on autoregressive model technique is proposed in this paper. The objective is to evaluate the relationship between the consumer load consumption vis-a-vis the model coefficients and model order selection. Such evaluation will facilitate effective monitoring of the individual consumer behaviour, which will be indicated in the changes in model parameters and invariably lead to detection of electricity theft on the part of the consumer. The study used the data acquired from consumer load prototype which represents a typical individual consumer connected to the distribution network. Average energy consumption obtained over 24 hours was used for the modelling and 5-minute step ahead load prediction based on model order 20 of minimum description length criterion technique was achieved. Electricity theft activities were detected whenever there are disparities in the model coefficients and consumer load data.
format	Article
author	Abdullateef, Adoyele Isqeel Salami, Momoh Jimoh Eyiomika Ahmed, Musse Mohamud Onasanya, Mobolaji Agbolade
author_facet	Abdullateef, Adoyele Isqeel Salami, Momoh Jimoh Eyiomika Ahmed, Musse Mohamud Onasanya, Mobolaji Agbolade
author_sort	Abdullateef, Adoyele Isqeel
title	Consumer load prediction and theft detection on distribution network using autoregressive model
title_short	Consumer load prediction and theft detection on distribution network using autoregressive model
title_full	Consumer load prediction and theft detection on distribution network using autoregressive model
title_fullStr	Consumer load prediction and theft detection on distribution network using autoregressive model
title_full_unstemmed	Consumer load prediction and theft detection on distribution network using autoregressive model
title_sort	consumer load prediction and theft detection on distribution network using autoregressive model
publisher	International Journal of Scientific & Engineering Research
publishDate	2013
url	http://irep.iium.edu.my/36065/ http://irep.iium.edu.my/36065/ http://irep.iium.edu.my/36065/1/Consumer-Load-Prediction-and-Theft-Detection-on-Distribution.pdf
first_indexed	2023-09-18T20:51:38Z
last_indexed	2023-09-18T20:51:38Z
_version_	1777410032985440256

Consumer load prediction and theft detection on distribution network using autoregressive model

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