A hierarchical carbon trading and optimisation scheduling strategy for integrated energy system with electric vehicles

IF 2.7 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IET Smart Grid Pub Date : 2025-02-11 DOI:10.1049/stg2.70001
Yang Andrew Wu, Yui-yip Lau, Junjun Xu, Juai Wu
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Abstract

The integration of electric vehicles (EVs) into integrated energy systems (IES) presents new challenges for achieving low-carbon, economically efficient operations due to fluctuating demand and increased carbon emissions. This paper proposes an optimised scheduling model incorporating a stepped carbon trading mechanism and demand response strategies to address these challenges. First, a multi-stage carbon pricing model is developed to encourage EVs to charge during low-carbon periods, effectively reducing system-wide emissions. Then, a multi-period pricing response mechanism is introduced to guide EV charging behaviours, aligning energy consumption with low-demand intervals. Finally, simulations are conducted to analyse the impact of varying EV loads on system performance, demonstrating the model's benefits in cost savings, emissions reduction, and load balancing. Case studies validate that the proposed model significantly enhances the low-carbon economic efficiency of IES, particularly as EV penetration increases, by leveraging flexible load distribution and responsive pricing strategies.

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电动汽车集成能源系统的分级碳交易与优化调度策略
由于需求波动和碳排放增加,将电动汽车(ev)集成到综合能源系统(IES)中,为实现低碳、经济高效的运营提出了新的挑战。本文提出了一种结合阶梯式碳交易机制和需求响应策略的优化调度模型来解决这些挑战。首先,建立多阶段碳定价模型,鼓励电动汽车在低碳时期充电,有效减少全系统排放。然后,引入多时段定价响应机制,引导电动汽车充电行为,使能源消耗与低需求时段保持一致。最后,通过仿真分析了不同电动汽车负载对系统性能的影响,证明了该模型在节约成本、减少排放和平衡负载方面的优势。案例研究证实,该模型通过利用灵活的负荷分配和响应式定价策略,显著提高了IES的低碳经济效率,尤其是在电动汽车普及率增加的情况下。
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来源期刊
IET Smart Grid
IET Smart Grid Computer Science-Computer Networks and Communications
CiteScore
6.70
自引率
4.30%
发文量
41
审稿时长
29 weeks
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