Phevs Contribution To The Self-Healing Process Of Distribution Systems
Keywords
Distribution system; Markov chain; Mixed integer linear programming; Plug-in hybrid electric vehicles; Self-healing
Abstract
Traditionally, distribution system takes a long time to recover after a major outage, due to its top-down operation strategy. As fast response energy resources, Plug-in Hybrid Electric Vehicles (PHEVs) can accelerate the load pickup process by compensating the imbalance between available generation and load in distribution system. In this paper, PHEVs are employed for reliable load pickup and faster self-healing process. The non-homogeneous Markov chain method has been employed for generation of synthetic driving behavior. The optimization problem of finding load pickup sequence to maximize restored energy is formulated as a Mixed Integer Linear Programming (MILP) problem. Simulation results on a 100-feeder test system demonstrate the benefit from PHEVs to restore more energy in a given recovery time. It also provides incentives to deploy a large amount of PHEVs to improve system resiliency.
Publication Date
11-10-2016
Publication Title
IEEE Power and Energy Society General Meeting
Volume
2016-November
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/PESGM.2016.7741842
Copyright Status
Unknown
Socpus ID
85002252459 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85002252459
STARS Citation
Golshani, Amir; Sun, Wei; and Zhou, Qun, "Phevs Contribution To The Self-Healing Process Of Distribution Systems" (2016). Scopus Export 2015-2019. 3969.
https://stars.library.ucf.edu/scopus2015/3969