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Distributed Optimization Approaches with Discrete Variables in the Power Distribution Systems

Conference · · 2022 North American Power Symposium (NAPS)
 [1];  [2];  [2]
  1. West Virginia University,Lane Department of Computer Science and Electrical Engineering,Morgantown,West Virginia,26506; West Virginia University
  2. West Virginia University,Lane Department of Computer Science and Electrical Engineering,Morgantown,West Virginia,26506
Traditionally, centralized approaches have predominantly been used for the power system operation and control. With increasing penetration of small-scale distributed energy resources (DERs) in the distribution network, especially independently owned renewable resources, distributed algorithms can serve as a potential alternative for improving scalability, resiliency and addressing privacy concerns. However, the complexity of distributed algorithms significantly increases with the integration of the legacy devices, the operation of which depend on discrete control variables. This paper aims to provide a review of the distributed optimization algorithms incorporating discrete control variables for the power distribution system. While the research in this domain is still at its nascence, an extensive comparison of the approaches in the literature for applying quadratic penalty, branch and bound,ordinal optimization and proximal operator to handle discrete variables in the framework of ADMM and dual decomposition have been addressed. Future research direction in this field have been also provided.
Research Organization:
University of Utah
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
DOE Contract Number:
EE0008775
OSTI ID:
2481465
Conference Information:
Journal Name: 2022 North American Power Symposium (NAPS)
Country of Publication:
United States
Language:
English

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