Optimal scheduling of Stackelberg game based dispatch of virtual power plant including EV considering conditional value at risk

doi:10.3969/j.issn.2097-0706.2025.09.009

Abstract

Abstract:

To investigate the Stackelberg game when electric vehicles （EV） participate in virtual power plant （VPP） scheduling and to analyze the effect of conditional value at risk （CVaR） on VPP profits， a bilevel Stackelberg game scheduling model for EV-integrated VPP considering CVaR was established. A bilevel Stackelberg game model between the VPP and EV was established， in which the VPP acted as the upper-level leader， setting electricity prices and guiding the lower-level EV to carry out orderly charging. Then， CVaR theory was introduced into the upper level to measure the risks brought by renewable energy such as wind and solar power. An upper-level objective function was established to maximize VPP profits and minimize CVaR risks， and a lower-level objective function was set to minimize the charging costs of EV. The proposed Stackelberg game scheduling model was solved using MATLAB + CPLEX solver. The results showed that different participation ratios of EV in the VPP had different effects on the total VPP profits. The highest VPP profits were achieved when EV types were concentrated. The established model can effectively guide the VPP to avoid risks while minimizing the charging costs of EV.

Key words: onditional value at risk, electric vehicles, virtual power plant, Stackelberg game, bilevel model

CLC Number:

TK01：TM732

YANG Na, MA Longteng, LIU Haorui, LIU Yaoze, YANG Guohua. Optimal scheduling of Stackelberg game based dispatch of virtual power plant including EV considering conditional value at risk[J]. Integrated Intelligent Energy, 2025, 47(9): 80-88.

Figures/Tables 11

Fig.1

Fig.2

Table 1

Table 2

Parameters of electric vehicles

参数	私家EV	公务EV	公交EV
$V i m a x$ /（kW·h）	57	57	57
$V i 0$ /（kW·h）	36.42	36.42	36.42
$P i, m a x E V s, c h$ /kW	8	8	8

Table 2

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Table 3

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时段	电价
峰(07:00 — 09:00；17:00 — 23:00)	0.722
平(23：00 — 次日07:00)	0.488
谷(09:00 — 17:00)	0.255

风险厌恶系数	VPP总收益
0	2 894.866 3
0.2	2 853.002 5
0.4	2 810.888 1
0.6	2 769.024 3
0.8	2 726.909 9
0.9	2 687.051 6