重庆理工大学学报2024,Vol.38Issue(21) :193-199.DOI:10.3969/j.issn.1674-8425(z).2024.11.024

V2G模式下考虑多利益主体的优化调度

Optimization scheduling with multiple stakeholders in V2G mode

陈将宏 郑新超 龚小玉 敖志强 胡佳慧 赵小涵
重庆理工大学学报2024,Vol.38Issue(21) :193-199.DOI:10.3969/j.issn.1674-8425(z).2024.11.024

V2G模式下考虑多利益主体的优化调度

Optimization scheduling with multiple stakeholders in V2G mode

陈将宏 1郑新超 2龚小玉 2敖志强 2胡佳慧 2赵小涵2
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作者信息

  • 1. 三峡大学电气与新能源学院,湖北宜昌 443002;湖北省输电线路工程技术研究中心,湖北宜昌 443002
  • 2. 三峡大学电气与新能源学院,湖北宜昌 443002
  • 折叠

摘要

针对目前大规模电动汽车(electric vehicle,EV)随机接入电网后导致电网负荷波动和稳定性下降等问题,提出基于车网互联(vehicle-to-grid,V2G)模式下考虑EV用户、电动汽车聚合商(electric vehicle aggregator,EVA)、电网的多利益主体的优化调度策略.电网侧以电网负荷波动最小为目标,EVA侧以EVA收益最大化为目标,EV用户侧在注重用户意愿度和调度能力的前提下,考虑EV电池损耗成本,以EV用户充电成本最小为目标.采用粒子群算法对模型进行算例分析,结果表明:所建立模型能够很好地平抑电网负荷波动,实现EVA和EV用户的经济收益最大化.

Abstract

To address the load fluctuations and stability degradation caused by the random connection of large-scale electric vehicles to the power grid,we propose an optimization scheduling strategy based on the vehicle network interconnection mode,which considers EV drivers,EV As,and the power grid.The fluctuation of grid load is minimized while the benefits of EV As are maximized.The the cost of battery loss is considered while EV drivers'intentions and scheduling ability are emphasized,aiming to minimize the charging costs of electric vehicles.The particle swarm optimization(PSO)is employed to analyze the model.Our results show our model effectively suppresses grid load fluctuations and delivers the highest economic returns to EV As and EV drivers.

关键词

电动汽车/车网互联/聚合商/电池损耗/负荷波动

Key words

electric vehicle/vehicle-to-grid/aggregator/battery loss/load fluctuation

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出版年

2024
重庆理工大学学报
重庆理工大学

重庆理工大学学报

CSTPCD北大核心
影响因子:0.567
ISSN:1674-8425
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