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陕西省智能电网重点实验室(西安交通大学),陕西省西安市 710049
贾士铎(1999—),男,硕士研究生,主要研究方向:能量管理、综合能源系统优化调度。E-mail:jiashiduo@stu.xjtu.edu.cn
康小宁(1968—),男,通信作者,博士,教授,博士生导师,主要研究方向:综合能源系统、电力系统继电保护。E-mail:kangxn@mail.xjtu.edu.cn
黑皓杰(1998—),男,硕士研究生,主要研究方向:综合能源系统、光伏系统孤岛检测。E-mail:1131485767@qq.com
收稿:2022-09-11,
修回:2023-03-06,
网络出版:2023-07-03,
纸质出版:2023-08-10
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贾士铎,康小宁,黑皓杰等.基于V2G负荷反馈修正的电热氢综合能源系统多层协调优化调度[J].电力系统自动化,2023,47(15):100-110.
JIA Shiduo,KANG Xiaoning,HEI Haojie,et al.Multi-layer Coordinated Optimal Dispatch of Electric-Thermal-Hydrogen Integrated Energy System Based on V2G Load Feedback Correction[J].Automation of Electric Power Systems,2023,47(15):100-110.
贾士铎,康小宁,黑皓杰等.基于V2G负荷反馈修正的电热氢综合能源系统多层协调优化调度[J].电力系统自动化,2023,47(15):100-110. DOI: 10.7500/AEPS20220911003.
JIA Shiduo,KANG Xiaoning,HEI Haojie,et al.Multi-layer Coordinated Optimal Dispatch of Electric-Thermal-Hydrogen Integrated Energy System Based on V2G Load Feedback Correction[J].Automation of Electric Power Systems,2023,47(15):100-110. DOI: 10.7500/AEPS20220911003.
含电动汽车和氢燃料电池汽车的综合能源系统可以实现多能协调互补,有效推动“双碳”目标的实现,但车辆出行计划的临时变动会对系统带来不利影响。为此,提出了包含对车联网(V2G)负荷反馈修正的电热氢综合能源系统多层协调优化策略。基于3层优化的协调配合,电动汽车充放电管理层综合考虑负荷曲线方差和车主不满意度,制定充放电计划并传递给模型预测控制滚动优化层。在滚动优化过程中,实时识别非计划车辆数,自主运行车联网负荷反馈修正层,从而消除车辆出行计划临时改变所带来的不利影响。仿真结果表明,所提策略在实现车主与运营商双赢的同时,提高了系统运行经济性并改善了主网联络线计划值跟踪情况。
The integrated energy system including electric vehicles (EVs) and hydrogen fuel cell vehicles (FCVs) can achieve multi-energy coordination and complementarity
and effectively promote the realization of the "carbon emission peak and carbon neutrality" goal
but temporary changes in vehicle travel plans have adverse effects on the system. Therefore
a multi-layer coordinated optimal strategy for the electric-thermal-hydrogen integrated energy system including the load feedback correction of the vehicle to grid (V2G) is proposed. Based on the coordination and cooperation of three-layer optimization
the charging and discharging management layer of EVs comprehensively considers the variance of the load curve and the dissatisfaction of EV owners
formulates charging and discharging plans and transmits them to the rolling optimization layer of model predictive control. In the rolling optimization process
the number of unplanned vehicles is identified in real time
and the V2G load feedback correction layer is operated independently
so as to eliminate the adverse effects of temporary changes in vehicle travel plans. The simulation results show that the proposed strategy not only achieves a win-win situation between car owners and operators
but also improves operational economy of the system and improves the track results of the planned power flow of the main grid tie-line line.
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