Paper Info
Title
Impacts of EVs on power system operation: Guangdong case, China
Abstract
In addition to reduce oil consumption and pollution emissions, electric vehicles (EVs) show great potential for the power system as flexible load. For this reason, it provokes our interest to investigate the extent to which EVs could contribute to the power system management from the power system operator's perspective. To achieve this goal, a unit commitment (UC) model for the power system operation that considers EVs charging is used. A case study in Guangdong province is carried out to quantify the impact of EVs in terms of generation mix by fuel type, demand profiles with EVs, variable generation cost of the system, and power purchase cost for grid companies. Result shows that in an economic dispatch context, controlled charging could reduce the variable generation cost, and the purchase cost for grid companies. At the meantime, the high coal consumption due to controlled charging can be observed, which conflicts with the low-carbon electricity transition policy in China. In addition, the controlled charging reduces the peak load by 5.77% compared with uncontrolled charging, when there is 2 Million EVs. While the impact of control charging on reducing peak load is uncertain yet, the grid companies probably face peak load challenges in both controlled and uncontrolled charging when there is high penetration level of EVs.
Year
DOI
Venue
2014
10.1109/ICNSC.2014.6819693
ICNSC
Keywords
Field
DocType
pollution emissions,power system management,electric vehicles (evs),power system operation,peak load challenges,unit commitment model,china,power generation dispatch,generation mix,controlled charging,grid companies,ev,low-carbon electricity transition policy,power generation economics,coal consumption,guangdong,variable generation cost,unit commitment,battery storage plants,power grids,flexible load,oil consumption,electric vehicles,coal,wind
Economic dispatch,Automotive engineering,Power system operators,Simulation,Electricity,Computer science,China,Power system simulation,Electric power system,Control engineering,Grid,Peak load
Conference
ISSN
Citations 
PageRank 
1810-7869
1
0.37
References 
Authors
1
2
Name
Order
Citations
PageRank
Ying Li110.71
Zofia Lukszo29431.29