Electric Vehicle Dispatching Strategy and Incentive Evaluation Based on Virtual Energy Storage

doi:10.16182/j.issn1004731x.joss.23-1316

Abstract

Abstract:

To address the multifaceted challenges arising from the widespread integration of electric vehicles into the power grid, harnessing the dispatchability features of electric vehicles becomes imperative. This paper based on a virtual energy storage aggregation model, optimizes the charging scheduling of electric vehicles and assesses their charging incentives through a composite weighting methodology. It establishes a framework for the participation of flexible loads in distribution network scheduling, formulates a second-order cone relaxation optimal power flow model, and develops dispatch strategies. By quantifying the contribution of electric vehicles concerning their flexibility and system stability, and simulating user charging preferences using a fuzzy inference system, this paper achieves effective guidance and optimization of electric vehicle charging. Simulation results affirm that this approach can fully tap into the demand response potential of electric vehicles, thereby enhancing the economic efficiency of system operation.

Key words: electric vehicles, virtual battery, comprehensive evaluation method, incentive mechanism, demand response

CLC Number:

TP391.9

Chen Shuo, Hu Hao, Fang Huimin, Wang Haiwei, Chen Xiaolong, Mei Chengcheng, Zhu Jiaʹnan, Ai Qian. Electric Vehicle Dispatching Strategy and Incentive Evaluation Based on Virtual Energy Storage[J]. Journal of System Simulation, 2025, 37(3): 732-741.

Figures/Tables 13

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Table 1

Formulas for evaluation metrics and meanings

指标名	计算公式	指标含义
电压偏移量	$f 1, t s t = ∑ i = 1 I U i, t b e f o r e 33 - 1$	节点电压偏移量的平均值
无功补偿量	$f 2, t s t = ∑ i ∈ u S V C Q i, t S V C + ∑ i ∈ u (C B) Q i, t C B$	SVC、CB无功补偿量
弃风量	$f 3, t s t = Δ P t w d$	风电场总弃风量
线路损耗	$f 4, t s t = P l o s s, t$	节点线路损耗总量
EV功率变化量	$f 5, t s t = P j, t V B + P j, t E V A - ∑ i ∈ N t D P i, t E V$	优化前后EV功率变化量
EV充放电量	$f 6, t s t = ∑ j ∈ u (E V) P j, t V B + P j, t E V A$	优化后EV充放电量

Table 1

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Table 2

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指标名	主观权重	客观权重	综合权重
电压偏移量	0.166 6	0.018 6	0.003 5
无功补偿量	0.083 3	0.039 0	0.003 7
弃风量	0.071 5	0.249 2	0.026 7
线路损耗量	0.023 8	0.328 0	0.011 7
EV功率变化量	0.436 5	0.158 0	0.060 2
EV充放电量	0.218 3	0.207 2	0.039 5

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