Title :
PEV Charging Control Considering Transformer Life and Experimental Validation of a 25 kVA Distribution Transformer
Author :
Qiuming Gong ; Midlam-Mohler, Shawn ; Serra, Emmanuele ; Marano, Vincenzo ; Rizzoni, Giorgio
Author_Institution :
Ford Motor Co., Dearborn, MI, USA
Abstract :
When considering the characteristics of electric power systems in the U.S., the local distribution is the most likely part to be adversely affected by the unregulated plug-in electric vehicle (PEV) charging. The increased load that can result from unregulated charging of PEVs could dramatically accelerate the aging of electrical transformers. In this paper, the control strategies that can mitigate or eliminate the accelerated aging that could result from load peaks caused by PEV charging is developed. The aging model makes it possible to develop charging control strategies that protect the transformer system while maximizing overall PEV charging quality. The charging control policy makes use of load prediction algorithms using data-driven models that are based on actual electricity consumption data. The experimental tests are done to calibrate the thermal model of a 25 kVA distribution transformer and validate the effectiveness of the control strategy.
Keywords :
ageing; electric vehicles; load forecasting; power consumption; power transformers; secondary cells; PEV; accelerated aging elimination; apparent power 25 kVA; charging control; data driven model; distribution transformer; electrical transformers; electricity consumption data; load prediction; plug-in electric vehicle; thermal model; transformer life; Aging; Load modeling; Oil insulation; Predictive models; System-on-chip; Temperature measurement; Windings; Distribution transformer; grid interaction; plug-in electric vehicles (PEVs); smart charging;
Journal_Title :
Smart Grid, IEEE Transactions on
DOI :
10.1109/TSG.2014.2365452
