|Table of Contents|

[1] Lin Guoying, Feng Xiaofeng, Lu Shixiang, et al. Revenue optimization strategy of V2G based on evolutionary game [J]. Journal of Southeast University (English Edition), 2020, 36 (1): 50-55. [doi:10.3969/j.issn.1003-7985.2020.01.007]
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Revenue optimization strategy of V2G based on evolutionary game()
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
36
Issue:
2020 1
Page:
50-55
Research Field:
Electrical Engineering
Publishing date:
2020-03-20

Info

Title:
Revenue optimization strategy of V2G based on evolutionary game
Author(s):
Lin Guoying1 2 Feng Xiaofeng2 Lu Shixiang2
1College of Electrical Engineering, Zhejiang University, Hangzhou 310000, China
2Guangdong Power Grid Corporation, Guangzhou 510080, China
Keywords:
evolutionary game electric vehicle vehicle-to-grid electricity price
PACS:
TM732
DOI:
10.3969/j.issn.1003-7985.2020.01.007
Abstract:
In order to protect the interests of electric vehicle users and grid companies with vehicle-to-grid(V2G)technology, a reasonable electric vehicle discharge electricity price is established through the evolutionary game model. A game model of power grid companies and electric vehicle users based on the evolutionary game theory is established to balance the revenue of both players in the game. By studying the dynamic evolution process of both sides of the game, the range of discharge price that satisfies the interests of both sides is obtained. The results are compared with those obtained by the static Bayesian game. The results show that the discharge price which can benefit both sides of the game exists in a specific range. According to the setting of the example, the reasonable discharge electricity price is 1.106 0 to 1.481 1 yuan/(kW·h). Only within this range can the power grid company and electric vehicle users achieve positive interactions. In addition, the evolutionary game model is easier to balance the interests of the two players than the static Bayesian game.

References:

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Memo

Memo:
Biography: Lin Guoying(1982—), male, doctor, senior engineer, yetqmwei@163.com.
Foundation item: The National Natural Science Foundation of China(No.51577028).
Citation: Lin Guoying, Feng Xiaofeng, Lu Shixiang.Revenue optimization strategy of V2G based on evolutionary game[J].Journal of Southeast University(English Edition), 2020, 36(1):50-55.DOI:10.3969/j.issn.1003-7985.2020.01.007.
Last Update: 2020-03-20