Non-intrusive Load Composition Estimation from Aggregate ZIP Load Models using Machine Learning-Reference-Cited by-同舟云学术

Non-intrusive Load Composition Estimation from Aggregate ZIP Load Models using Machine Learning

Published:2019-02 Issue: Volume:105 Page:191-200
ISSN:0142-0615
Container-title:International Journal of Electrical Power & Energy Systems
language:en
Short-container-title:International Journal of Electrical Power & Energy Systems

Author:

Asres Mulugeta W.,Girmay Awet A.,Camarda Christian^ORCID,Tesfamariam Gebremichael T.

Funder

Ethiopian Institute of Technology

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference28 articles.

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4. Experimental determination of the ZIP coefficients for modern residential, commercial, and industrial loads;Bokhari;IEEE Trans Power Deliv,2014

5. W. G. C4.605. Modelling and aggregation of loads in flexible power networks. CIGRE; 2014.

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