Electric Vehicles Battery Wear Cost Optimization for Frequency Regulation Support

被引:35
|
作者
Kolawole, Olalekan [1 ]
Al-Anbagi, Irfan [2 ]
机构
[1] Econolite Canada Ltd, Markham, ON L3S 3J1, Canada
[2] Univ Regina, Fac Engn & Appl Sci, Regina, SK S4S 0A2, Canada
关键词
Aggregator; battery degradation; charge scheduling; mixed integer linear programming; Vehicle-to-Grid (V2G); frequency regulation; BENEFIT-ANALYSIS; ION BATTERIES; DEGRADATION;
D O I
10.1109/ACCESS.2019.2930233
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Due to their capacities and quick response, Electric Vehicle (EV) batteries can be used to support a number of power grid services and form a Vehicle-to-Grid (V2G) system. When aggregated and properly managed EV batteries can provide important ancillary services such as peak load levelling and frequency regulation. EVs can also provide various demand response services and help in renewable energy integration. The major challenge for having a wide-scale V2G system to effectively provide the above services is the availability of power which is limited by the battery degradation and the battery cycle life. The battery cycle life is inversely proportional to the charge/discharge cycles the battery goes through during its operation. Therefore, the charge/discharge operation should be optimized to maximize the benefit for both the EV owners and the grid operator. In this paper, we develop an EV charge/discharge optimization model that incorporates frequency regulation and electricity prices from both real and forecasting models into the objective function of the model. We develop a prediction and optimization model to reflect the effects of dynamic and static electricity and regulation prices on the battery cycle life. We present a case study for the charge/discharge scheduling problem utilizing real, predicted regulation and electricity hourly pricing.
引用
收藏
页码:130388 / 130398
页数:11
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