Building Marginal Pattern Library With Unbiased Training Dataset for Enhancing Model-Free Load-ED Mapping-Reference-Cited by-同舟云学术

Building Marginal Pattern Library With Unbiased Training Dataset for Enhancing Model-Free Load-ED Mapping

Published:2022 Issue: Volume:9 Page:88-98
ISSN:2687-7910
Container-title:IEEE Open Access Journal of Power and Energy
language:
Short-container-title:IEEE Open J. Power Energy

Author:

Zhang Qiwei¹^ORCID,Li Fangxing¹^ORCID,Feng Wei¹^ORCID,Wang Xiaofei¹^ORCID,Bai Linquan²^ORCID,Bo Rui³^ORCID

Affiliation:

1. Min H. Kao Department of EECS, The University of Tennessee, Knoxville, TN, USA

2. Systems Engineering and Engineering Management Department, The University of North Carolina at Charlotte, Charlotte, NC, USA

3. Department of ECE, Missouri University of Science and Technology, Rolla, MO, USA

Funder

U.S. Department of Energy Cybersecurity for Energy Delivery Systems (CEDS) Project “Watching Grid Infrastructure Stealthily Through Proxies (WISP)”

Center for Ultra-Wide-Area Resilient Electric Energy Transmission Networks (CURENT) which is a U.S. NSF/Department of Energy (DOE) Engineering Research Center by NSF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Link

https://ieeexplore.ieee.org/ielam/8784343/9662292/9705567-aam.pdf

Reference26 articles.

1. Solving security constrained optimal power flow problems by a structure exploiting interior point method

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