Performance Evaluation of the ZIP Model-Phaselet Frame Approach for Identifying Appliances in Residential Loads
This paper presents the analysis and development of a new approach to monitor and update the ON-OFF status of appliances in residential loads (RSLs). The proposed approach is structured to employ power meter readings P to determine the values for the magnitude |S̅| and phase θ of the apparent power....
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Published in | IEEE transactions on industry applications Vol. 52; no. 4; pp. 3408 - 3421 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.07.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Summary: | This paper presents the analysis and development of a new approach to monitor and update the ON-OFF status of appliances in residential loads (RSLs). The proposed approach is structured to employ power meter readings P to determine the values for the magnitude |S̅| and phase θ of the apparent power. The value of |S̅|, associated with a value of P, is determined using Newton iterations, where a value of θ is calculated using six phaselet frames during each iteration. Once the iterations converge, the values of P and θ are used to construct the ZIP model (polynomial model) for the RSL, from which P is provided. The constructed ZIP model provides the values for the constants K pf and K qf that relate the change in frequency to the active and reactive power demands of the modeled load. The obtained values of K pf and K qf are compared to standardized values that are defined for each appliance in an RSL. The ZIP model-phaselet frame approach is implemented as an algorithm for monitoring the ON-OFF status of appliances in RSLs. The algorithm for the proposed approach is developed without a need to collect data for training. Test results show simple implementation, good accuracy, and insensitivity to variations in energy demands. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0093-9994 1939-9367 |
DOI: | 10.1109/TIA.2016.2535268 |