Back to Search Start Over

Optimisation model for power system restoration with support from electric vehicles employing battery swapping.

Authors :
Sun, Lei
Wang, Xiaolei
Liu, Weijia
Lin, Zhenzhi
Wen, Fushuan
Ang, Swee Peng
Salam, Md. Abdus
Source :
IET Generation, Transmission & Distribution (Wiley-Blackwell). Feb2016, Vol. 10 Issue 3, p771-779. 9p.
Publication Year :
2016

Abstract

The energy stored in the batteries of electric vehicles (EVs) could be employed for starting generators when a blackout or a local outage occurs. Considering the feature of the battery swapping mode, an available capacity model of the batteries in a centralised charging station is first developed. Then, the authors analyse the start‐up characteristics of a generator powered by batteries and propose a bi‐level optimisation‐based network reconfiguration model to determine the restoration paths with an objective of maximising the overall generation capability. In the upper‐level optimisation model, the generator start‐up sequence is optimised, whereas the restoration paths are optimised in the lower‐level one. Moreover, they consider the uncertainties associated with the available capacity of the batteries. The bi‐level optimisation model for the network reconfiguration is developed in the chance‐constrained programming framework and solved by the well‐established particle swarm optimisation algorithm. Finally, case studies are employed to demonstrate the effectiveness of the presented model. Simulation results show that a centralised EV charging station could act as a power source to effectively restore a power system without black‐start (BS) generators or with insufficient cranking power from BS generators, and the presented model could be used to guide actual system restorations. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17518687
Volume :
10
Issue :
3
Database :
Academic Search Index
Journal :
IET Generation, Transmission & Distribution (Wiley-Blackwell)
Publication Type :
Academic Journal
Accession number :
148082486
Full Text :
https://doi.org/10.1049/iet-gtd.2015.0441