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Title: Consensus weighting of a multi-agent system for load shedding

Abstract

In this work, an agent-based scheme is proposed for distributed underfrequency load shedding (UFLS). The key concept is a consensus weighting protocol (CWP) for agents to reach an agreement. Unlike the well adopted average-consensus protocol (ACP), the proposed CWP enables each agent to converge to its weighted portion of the sum of all initial values. Thus, the proposed CWP is more suitable for the UFLS application, as it allows load buses with a higher level of loading to shed more, rather than reducing by the same average value over all load buses as required by the ACP. Proof of convergence for the proposed CWP is derived and presented in this paper, together with the constraints. For implementation of the multi-agent system (MAS), the monitoring, estimation, and distribution steps are developed. Two study cases and the simulation results are provided to validate the performance of the proposed agent-based UFLS scheme.

Authors:
 [1];  [2];  [3];  [4]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)
  3. TERNA, Rome (Italy)
  4. Beijing Jiaotong Univ. (China)
Publication Date:
Research Org.:
Vanderbilt Univ., Nashville, TN (United States)
Sponsoring Org.:
USDOE Advanced Research Projects Agency - Energy (ARPA-E); National Science Foundation (NSF)
OSTI Identifier:
1616413
Alternate Identifier(s):
OSTI ID: 1573124
Report Number(s):
DOE-VANDERBILT-0000666-32
Journal ID: ISSN 0142-0615
Grant/Contract Number:  
AR0000666; AC05-76RL01830; 1441214
Resource Type:
Accepted Manuscript
Journal Name:
International Journal of Electrical Power and Energy Systems
Additional Journal Information:
Journal Volume: 117; Journal Issue: C; Journal ID: ISSN 0142-0615
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 42 ENGINEERING; Agent; consensus weighting; multi-agent system (MAS); smart grid; underfrequency load shedding (UFLS)

Citation Formats

Xie, Jing, Liu, Chen-Ching, Sforna, Marino, and Xu, Yin. Consensus weighting of a multi-agent system for load shedding. United States: N. p., 2019. Web. https://doi.org/10.1016/j.ijepes.2019.105615.
Xie, Jing, Liu, Chen-Ching, Sforna, Marino, & Xu, Yin. Consensus weighting of a multi-agent system for load shedding. United States. https://doi.org/10.1016/j.ijepes.2019.105615
Xie, Jing, Liu, Chen-Ching, Sforna, Marino, and Xu, Yin. Tue . "Consensus weighting of a multi-agent system for load shedding". United States. https://doi.org/10.1016/j.ijepes.2019.105615. https://www.osti.gov/servlets/purl/1616413.
@article{osti_1616413,
title = {Consensus weighting of a multi-agent system for load shedding},
author = {Xie, Jing and Liu, Chen-Ching and Sforna, Marino and Xu, Yin},
abstractNote = {In this work, an agent-based scheme is proposed for distributed underfrequency load shedding (UFLS). The key concept is a consensus weighting protocol (CWP) for agents to reach an agreement. Unlike the well adopted average-consensus protocol (ACP), the proposed CWP enables each agent to converge to its weighted portion of the sum of all initial values. Thus, the proposed CWP is more suitable for the UFLS application, as it allows load buses with a higher level of loading to shed more, rather than reducing by the same average value over all load buses as required by the ACP. Proof of convergence for the proposed CWP is derived and presented in this paper, together with the constraints. For implementation of the multi-agent system (MAS), the monitoring, estimation, and distribution steps are developed. Two study cases and the simulation results are provided to validate the performance of the proposed agent-based UFLS scheme.},
doi = {10.1016/j.ijepes.2019.105615},
journal = {International Journal of Electrical Power and Energy Systems},
number = C,
volume = 117,
place = {United States},
year = {2019},
month = {11}
}

Journal Article:

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Cited by: 1 work
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