In the next decade, electric vehicles (EV) will be heading to the road in a fast speed. Utility company would have no control over the future EV charging points or stations, and no direct control over periods and frequency of EV charging that could cause great effects to the existing distribution network operations if not well planned. Distribution system operation and expansion planning would become more complicated
due to the high degree of uncertainty of the EV charging demand. Markov model is used in this study to calculate the probabilities and locations of EV charging. To mitigate the loading and voltage quality problem, feeder reconfiguration is proposed. The problem is formulated as an stochastic programming program with an objective function of minimizing total switching and system loss costs, and subject to radial
structure of the distribution network and security constraints. The problem is solved by a binary particle swarm optimization technique. Test results indicate that feeder reconfiguration can be exercised to match loading patterns of different types of feeders (residential, commercial and industrial) with various stochastic charging scenarios, and consequently, reduce the impacts of EV charging and optimize the use of the existing network.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0713112-175326 |
| Date | 13 July 2012 |
| Creators | Chan, Chieh-Min |
| Contributors | Gary-Wen Chang, Chih-Wen Liu, Jiann-Fuh Chen, Shr-Lin Chen, Ching-Tsai Pan, Chan-Nan Lu |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0713112-175326 |
| Rights | unrestricted, Copyright information available at source archive |
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