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Decomposition Techniques for Power S...

Dong, Ming.

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Decomposition Techniques for Power System Load Analysis.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Decomposition Techniques for Power System Load Analysis./
Author:	Dong, Ming.
Description:	206 p.
Notes:	Source: Dissertation Abstracts International, Volume: 75-06(E), Section: B.
Contained By:	Dissertation Abstracts International75-06B(E).
Subject:	Energy. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NS27527
ISBN:	9780499275271

Decomposition Techniques for Power System Load Analysis.
Dong, Ming.

Decomposition Techniques for Power System Load Analysis. - 206 p.

Source: Dissertation Abstracts International, Volume: 75-06(E), Section: B.

Thesis (Ph.D.)--University of Alberta (Canada), 2013.

In recent years, the increased public awareness of energy conservation has attracted serious attention to detailed energy consumption monitoring and management for the end users of power system. Load decomposition is a technique that can extract detailed sub-load information from compound load information. This technique decomposes a compound load such as an entire residential house into specific sub-load levels such as different home appliances by using only the aggregated metering data of the compound load. Through load decomposition, users can better understand the usage patterns of individual loads or load groups and therefore decide on how to save energy. On the utility side, load decomposition can be very helpful for load forecast, demand response program development, and Time-Of-Use price design.

ISBN: 9780499275271Subjects--Topical Terms:

876794
Energy.

Decomposition Techniques for Power System Load Analysis.
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100 1 $a Dong, Ming. $3 2104908
245 1 0 $a Decomposition Techniques for Power System Load Analysis.
300 $a 206 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-06(E), Section: B.
502 $a Thesis (Ph.D.)--University of Alberta (Canada), 2013.
520 $a In recent years, the increased public awareness of energy conservation has attracted serious attention to detailed energy consumption monitoring and management for the end users of power system. Load decomposition is a technique that can extract detailed sub-load information from compound load information. This technique decomposes a compound load such as an entire residential house into specific sub-load levels such as different home appliances by using only the aggregated metering data of the compound load. Through load decomposition, users can better understand the usage patterns of individual loads or load groups and therefore decide on how to save energy. On the utility side, load decomposition can be very helpful for load forecast, demand response program development, and Time-Of-Use price design.
520 $a In the past, traditional methods are either too costly or inaccurate. Therefore, some researchers proposed a non-intrusive load monitoring (NILM) approach that can identify and track major sub-loads based on only the total signal collected from the meter-side with acceptable error. Recently, the vast deployment of smart meters has raised considerable interests in this approach. However, many critical problems still need to be solved before it truly becomes technically available for ordinary end-users.
520 $a To solve the above problems, at the beginning, this thesis presents a novel NILM method based on event detection and load signature studies. The key idea is to model the entire operating cycle of a load and make identification based on event-window candidates. The proposed technique makes NILM more applicable for complex loads, more robust for load inventory change and can also simplify the training process; on the other hand, the thesis addresses a new and critical problem that previous researchers ignored---the non-intrusive extraction of load signatures. The proposed approach is an unsupervised non-intrusive approach which can automatically extract load signatures by using the meter-side data and requires almost zero effort from users. This thesis also discusses how to estimate the energy for several key components in a residential house such as the NILM identified appliances, load groups and background power. Based on estimation, residential energy characteristics are discussed with respect to the Time-of-use price.
590 $a School code: 0351.
650 4 $a Energy. $3 876794
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710 2 $a University of Alberta (Canada). $b Department of Electrical and Computer Engineering. $3 2104909
773 0 $t Dissertation Abstracts International $g 75-06B(E).
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791 $a Ph.D.
792 $a 2013
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NS27527