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考虑电动汽车充电模式和供需灵活性的综合能源系统优化调度
Optimal Scheduling of Integrated Energy Systems Considering Electric Vehicle Charging Patterns and Supply-Demand Flexibility
【目的】为进一步提升综合能源系统（integrated energy system，IES）的灵活性和低碳性，提出考虑电动汽车（electric vehicle，EV）不同充电模式和供需灵活性的IES优化调度策略。【方法】首先，从需求侧灵活性出发，构建了基于常规慢充、快速充电及换电三种充电模式下的动态荷电状态的有序充电策略。其次，结合综合需求响应，进一步研究灵活性提升策略。然后，从供能侧出发，考虑卡琳娜循环（Kalina cycle，KC）相比于有机朗肯循环优势，引入KC，实现热电联产机组热电解耦和灵活经济输出。最后，考虑碳排放限制，构建了考虑阶梯碳交易、EV充电模式、需求响应及KC的IES低碳经济优化模型。【结果】通过多种场景对比分析，所提策略使总成本降低了16.22%。所提策略能有效提升IES供需双侧灵活性，实现EV不同充电模式下的有序充电，降低系统的经济成本和碳排放量。【结论】创新点包括不同充电模式的有序充电、供需双侧灵活性提升方法。研究成果可为IES灵活性提升提供新思路，后续可结合其他灵活性资源最大限度提升灵活性。
[Objective] To enhance the flexibility and low-carbon performance of integrated energy systems （IES）， this study proposes an optimal scheduling strategy that accounts for various electric vehicle （EV） charging modes and supply-demand flexibility. [Methods] First， from the demand perspective， an ordered charging strategy is developed based on the dynamic state of charge. This applies to three charging modes： conventional slow charging， fast charging， and power exchange. Second， flexibility-enhancement strategies are further explored in coordination with integrated energy demand. On the supply side， the Kalina cycle （KC） is introduced as an improvement over the organic Rankine cycle. The KC enables thermoelectric decoupling and supports flexible， efficient output from the CHP unit. Finally， an IES low-carbon economic optimization model is constructed. It incorporates stepwise carbon trading， EV charging modes， demand response， and the KC， while considering carbon emission constraints. [Results] By comparing and analyzing multiple scenarios， the proposed strategy reduces the total system cost by 16.22%. It also improves the flexibility of IES supply and demand， enables orderly charging across various EV charging modes， and lowers both economic costs and carbon emissions. [Conclusions] The key innovations include sequential charging tailored to different EV charging modes and strategies to enhance supply and demand flexibility. These findings offer new insights into improving IES flexibility and can be integrated with other flexibility resources to further maximize system performance.
electric vehicle / orderly charging / Kalina cycle / bilateral flexibility in supply and demand
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Access to large-scale electric vehicles poses new challenges for the optimal dispatching of a regional integrated energy system (RIES). This study proposes a bi-level day-ahead scheduling strategy for a RIES while considering the integration of electric vehicles. First, the Monte Carlo method was used to simulate the disordered charging of electric vehicles. On this basis, the time-of-use price was used to guide the orderly charging of electric vehicles on the load side. Next, based on the electricity and carbon trading markets and fully considering the uncertainty factors in the process of wind power output on the source side and the demand-side response on the load side, the system was optimized and scheduled to minimize the daily economic and carbon trading costs. An improved particle swarm optimization algorithm was used to solve the problem. Finally, through the analysis of simulated examples, it was concluded that the bi-level optimal scheduling strategy proposed in this study can effectively reduce the peak-valley difference of the system load, improve the electricity consumption satisfaction of users, reduce carbon emissions, and increase the economic benefits of the system, while realizing the orderly charging of electric vehicles. |
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