New Type Power System and the Integrated Energy

Dynamic Double-Layer Energy Management Strategy for Park Power Grid Considering Vehicle-to-Grid

  • QIU Gefei ,
  • FENG Zehua ,
  • SHEN Fu ,
  • HE Chao ,
  • HE Honghui ,
  • LIU Kaiming
Expand
  • College of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650500, China

Received date: 2022-12-16

  Revised date: 2023-02-12

  Accepted date: 2023-04-17

  Online published: 2024-07-05

Abstract

This paper proposes a two-layer optimal control strategy for the park power grid, aiming at addressing the energy management challenges arising from the fluctuations in the output of clean energy sources and the random changes in the number of electric vehicles (EV) at the charging station. The upper layer establishes a dynamic optimization model of landscape storage based on the model predictive control technology, which comprehensively incorporates both the battery energy storage system of the park and the battery energy storage system of EVs, enabling them to participate in balancing the energy demand of the power grid, while the lower layer considers meeting the charging demand of EV owners and the vehicle-to-grid management demand of upper layer for energy dispatching simultaneously, and formulates an orderly charging and discharging strategy for EVs in the parking lot of the power grid. The simulation results show that the proposed strategy effectively can integrate scattered EV storage in the park into a unified virtual energy storage system, expand the energy storage capacity of the grid, and increase the consumption of renewable distributed generation supply, ultimately improving economic benefits for the park grid.

Cite this article

QIU Gefei , FENG Zehua , SHEN Fu , HE Chao , HE Honghui , LIU Kaiming . Dynamic Double-Layer Energy Management Strategy for Park Power Grid Considering Vehicle-to-Grid[J]. Journal of Shanghai Jiaotong University, 2024 , 58(6) : 916 -925 . DOI: 10.16183/j.cnki.jsjtu.2022.524

References

[1] 黄强, 郭怿, 江建华, 等. “双碳” 目标下中国清洁电力发展路径[J]. 上海交通大学学报, 2021, 55(12): 1499-1509.
  HUANG Qiang, GUO Yi, JIANG Jianhua, et al. Development pathway of China’s clean electricity under carbon peaking and carbon neutrality goals[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1499-1509.
[2] FAN M, SUN K, LANE D, et al. A novel generation rescheduling algorithm to improve power system reliability with high renewable energy penetration[J]. IEEE Transactions on Power Systems, 2018, 33(3): 3349-3357.
[3] 廖启术, 胡维昊, 曹迪, 等. 新能源电力系统中的分布式光伏净负荷预测[J]. 上海交通大学学报, 2021, 55(12): 1520-1531.
  LIAO Qishu, HU Weihao, CAO Di, et al. Distributed photovoltaic net load forecasting in new energy power systems[J]. Journal of Shanghai Jiao Tong University, 2021, 55(12): 1520-1531.
[4] 朱青, 曾利华, 寇凤海, 等. 考虑储能并网运营模式的工业园区风光燃储优化配置方法研究[J]. 电力系统保护与控制, 2019, 47(17): 23-31.
  ZHU Qing, ZENG Lihua, KOU Fenghai, et al. Research on optimal allocation method of wind, photovoltaic, gas turbine and energy storage in industrial parks considering energy storage’s grid-connected operation modes[J]. Power System Protection & Control, 2019, 47(17): 23-31.
[5] 李玲芳, 陈占鹏, 胡炎, 等. 基于灵活性和经济性的可再生能源电力系统扩展规划[J]. 上海交通大学学报, 2021, 55(7): 791-801.
  LI Lingfang, CHEN Zhanpeng, HU Yan, et al. Expansion planning of renewable energy power system considering flexibility and economy[J]. Journal of Shanghai Jiao Tong University, 2021, 55(7): 791-801.
[6] 白雪岩, 樊艳芳, 刘雨佳, 等. 考虑可靠性及灵活性的风光储虚拟电厂分层容量配置[J]. 电力系统保护与控制, 2022, 50(8): 11-24.
  BAI Xueyan, FAN Yanfang, LIU Yujia, et al. Wind power storage virtual power plant considering reliability and flexibility tiered capacity configuration[J]. Power System Protection & Control, 2022, 50(8): 11-24.
[7] 刘世林, 禹威威, 姚伟. 用于风电场发电计划跟踪的复合储能控制策略[J]. 太阳能学报, 2018, 39(4): 1060-1068.
  LIU Shilin, YU Weiwei, YAO Wei. Composite energy storage control strategy for wind farm power generation planning tracking[J]. Acta Energiae Solaris Sinica, 2018, 39(4): 1060-1068.
[8] YILMAZ U C, SEZGIN M E, GOL M. A model predictive control for microgrids considering battery aging[J]. Journal of Modern Power Systems & Clean Energy, 2020, 8(2): 296-304.
[9] 王磊, 周建平, 朱刘柱, 等. 基于分布式模型预测控制的综合能源系统多时间尺度优化调度[J]. 电力系统自动化, 2021, 45(13): 57-65.
  WANG Lei, ZHOU Jianping, ZHU Liuzhu, et al. Multi-time-scale optimization scheduling of integrated energy system based on distributed model predictive control[J]. Automation of Electric Power Systems, 2021, 45(13): 57-65.
[10] 祁希, 何山, 王维庆, 等. 基于FMPC的储能系统跟踪光伏发电计划控制策略[J]. 可再生能源, 2019, 37(3): 354-360.
  QI Xi, HE Shan, WANG Weiqing, et al. FMPC based control strategy for tracking PV power schedule output of energy storage system[J]. Renewable Energy Resources, 2019, 37(3): 354-360.
[11] 杜祥伟, 沈艳霞, 李静. 基于模型预测控制的直流微网混合储能能量管理策略[J]. 电力系统保护与控制, 2020, 48(16): 69-75.
  DU Xiangwei, SHEN Yanxia, LI Jing. Energy management strategy of DC microgrid hybrid energy storage based on model predictive control[J]. Power System Protection & Control, 2020, 48(16): 69-75.
[12] 吴岩, 王玮, 吴学智, 等. 微电网跟踪调度计划双层双时间尺度实时控制策略[J]. 电力自动化设备, 2021, 41(1): 120-127.
  WU Yan, WANG Wei, WU Xuezhi, et al. Two-layer double-time scale real-time control strategy of microgrid for tracking scheduling plan[J]. Electric Power Automation Equipment, 2021, 41(1): 120-127.
[13] 田壁源, 常喜强, 徐海奇, 等. 考虑电动汽车虚拟储能的高渗透配电网鲁棒优化调度[J]. 电力需求侧管理, 2021, 23(3): 19-24.
  TIAN Biyuan, CHANG Xiqiang, XU Haiqi, et al. Robust optimal scheduling of high permeability distribution network considering EV-VES[J]. Power Demand Side Management, 2021, 23(3): 19-24.
[14] 程杉, 钟仕凌, 尚冬冬, 等. 考虑电动汽车时空负荷分布特性的主动配电网动态重构[J]. 电力系统保护与控制, 2022, 50(17): 1-13.
  CHENG Shan, ZHONG Shiling, SHANG Dongdong, et al. Dynamic reconfiguration of an active distribution network considering temporal and spatial load distribution characteristics of electric vehicles[J]. Power System Protection & Control, 2022, 50(17): 1-13.
[15] 李蓓, 赵松, 谢志佳, 等. 电动汽车虚拟储能可用容量建模[J]. 山东大学学报(工学版), 2020, 50(6): 101-111.
  LI Bei, ZHAO Song, XIE Zhijia, et al. Electric vehicle virtual energy storage available capacity modeling[J]. Journal of Shandong University (Engineering Science), 2020, 50(6): 101-111.
[16] 安小宇, 李元丰, 孙建彬, 等. 基于模糊逻辑的电动汽车双源混合储能系统能量管理策略[J]. 电力系统保护与控制, 2021, 49(16): 135-142.
  AN Xiaoyu, LI Yuanfeng, SUN Jianbin, et al. Energy management strategy of a dual-source hybrid energy storage system for electric vehicles based on fuzzy logic[J]. Power System Protection & Control, 2021, 49(16): 135-142.
[17] HAN X J, LIANG D X, WANG H. An optimization scheduling method of electric vehicle virtual energy storage to track planned output based on multiobjective optimization[J]. International Journal of Energy Research, 2020, 44(11): 8492-8512.
[18] RAMALINGESWAR J T, SUBRAMANIAN K. A novel energy management strategy to reduce gird dependency using electric vehicles storage in coordination with solar power[J]. Journal of Intelligent & Fuzzy Systems: Applications in Engineering & Technology, 2021, 41(1): 2207-2223.
[19] 程杉, 汪业乔, 廖玮, 等. 含电动汽车的新能源微电网多目标分层优化调度[J]. 电力系统保护与控制, 2022, 50(12): 63-71.
  CHENG Shan, WANG Yeqiao, LIAO Wei, et al. Bi-level multi-objective optimization of a new energy microgrid with electric vehicles[J]. Power System Protection & Control, 2022, 50(12): 63-71.
[20] XU J, XIE B Y, LIAO S Y, et al. Load shedding and restoration for intentional island with renewable distributed generation[J]. Journal of Modern Power Systems & Clean Energy, 2021, 9(3): 612-624.
[21] 唐佳, 王丹, 贾宏杰, 等. 基于迟滞模型的集群电动汽车参与实时需求响应V2G控制策略研究[J]. 电网技术, 2017, 41(7): 2155-2164.
  TANG Jia, WANG Dan, JIA Hongjie, et al. A study of V2G control strategies of aggregated electric vehicles for real-time demand response based on hysteresis model[J]. Power System Technology, 2017, 41(7): 2155-2164.
[22] QUELHAS A, MCCALLEY J D. A multiperiod generalized network flow model of the U.S. integrated energy system: Part II—Simulation results[J]. IEEE Transactions on Power Systems, 2007, 22(2): 837-844.
[23] GU W, WANG Z H, WU Z, et al. An online optimal dispatch schedule for CCHP microgrids based on model predictive control[C]//2017 IEEE Power & Energy Society General Meeting. Chicago, USA: IEEE, 2017: 1.
[24] 乐健, 廖小兵, 章琰天, 等. 电力系统分布式模型预测控制方法综述与展望[J]. 电力系统自动化, 2020, 44(23): 179-191.
  LE Jian, LIAO Xiaobing, ZHANG Yantian, et al. Review and prospect on distributed model predictive control method for power system[J]. Automation of Electric Power Systems, 2020, 44(23): 179-191.
[25] 王守相, 陈建凯, 王洪坤, 等. 综合考虑电动汽车充电与储能及可中断负荷调度的配电网两阶段灵活性提升优化方法[J]. 电力自动化设备, 2020, 40(11): 1-8.
  WANG Shouxiang, CHEN Jiankai, WANG Hongkun, et al. Two-stage flexibility improvement optimization method for distribution network considering EV charging and scheduling of energy storage and interruptible loads[J]. Electric Power Automation Equipment, 2020, 40(11): 1-8.
[26] 胡枭, 徐国栋, 尚策, 等. 工业园区参与调峰的电池储能-需求响应联合规划[J]. 电力系统自动化, 2019, 43(15): 116-123.
  HU Xiao, XU Guodong, SHANG Ce, et al. Joint planning of battery energy storage and demand response for industrial park participating in peak shaving[J]. Automation of Electric Power Systems, 2019, 43(15): 116-123.
[27] 肖朝霞, 张可信, 冯冀. 含电动汽车充电站的风/光/柴独立微电网分层优化调度[J]. 天津工业大学学报, 2022, 41(4): 61-74.
  XIAO Zhaoxia, ZHANG Kexin, FENG Ji. Hierarchical optimal dispatching of wind/PV/diesel islanded microgrid with EVs charging station[J]. Journal of Tianjin Polytechnic University, 2022, 41(4): 61-74.
Outlines

/