综合智慧能源 ›› 2025, Vol. 47 ›› Issue (7): 12-22.doi: 10.3969/j.issn.2097-0706.2025.07.002

• 综合能源系统优化调度 • 上一篇    下一篇

考虑电动汽车充电模式和楼宇热惯性的商业智能楼宇能量管理策略

吴国梁1(), 郑文2,*(), 何玲1(), 王雷1(), 黄媛2(), 刘俊勇2()   

  1. 1.南京远能电力工程有限公司, 南京 210046
    2.四川大学 电气工程学院, 成都 610207
  • 收稿日期:2025-03-05 修回日期:2025-04-11 出版日期:2025-07-25
  • 通讯作者: *郑文(1999),男,硕士生,从事新型电力系统方面的研究,xianxianjia061@163.com
  • 作者简介:吴国梁(1975),男,高级工程师,硕士,从事新型电力系统方面的研究,d156489@qq.com
    何玲(1985),女,工程师,从事新型电力系统方面的研究,x164898465@qq.com
    王雷(1991),男,工程师,从事新型电力系统方面的研究,hg1654956@qq.com
    黄媛(1974),女,副教授,博士,从事电力系统的稳定与运行分析、能源互联网、配电网的储能及故障恢复策略等方面的研究,yuanhuang@scu.edu.cn
    刘俊勇(1963),男,教授,博士,从事园区/智能楼宇能量管理、能源互联网、智慧能源与生态农业、电力市场、智能配电网、电力系统大数据技术、电动汽车等方面的研究,liujy@scu.edu.cn
  • 基金资助:
    中央高校基本科研业务费专项资金资助项目(YJ2021163)

Energy management strategy for smart commercial buildings considering electric vehicle charging patterns and building thermal inertia

WU Guoliang1(), ZHENG Wen2,*(), HE Ling1(), WANG Lei1(), HUANG Yuan2(), LIU Junyong2()   

  1. 1. Nanjing Yuanneng Power Engineering Company Limited, Nanjing 210046, China
    2. School of Electrical Engineering, Sichuan University, Chengdu 610207, China
  • Received:2025-03-05 Revised:2025-04-11 Published:2025-07-25
  • Supported by:
    Fundamental Research Funds for the Central Universities(YJ2021163)

摘要:

随着经济水平的增长,楼宇用电比重不断增加,优化楼宇的能量管理策略能有效促进节能减排。在商业智能楼宇负荷中,空调及电动汽车能耗占据较大比重,为此,提出了一种考虑楼宇热惯性、含电动汽车接入的商业智能楼宇能量管理模型。通过蒙特卡罗模拟对电动汽车行为特性进行建模,基于热容-热阻模型建立楼宇热动态平衡方程,采用基于场景的随机规划(SP)建立商业智能楼宇能量管理模型,引入条件风险价值法(CVaR)使模型增加一定的保守性。算例结果证明考虑楼宇热惯性时空调负荷的运行费用降低了9.7%,收益增加了1.4%。CVaR虽然降低了楼宇的运行风险,但也降低了楼宇综合期望收益。

关键词: 楼宇热惯性, 电动汽车, 随机规化, 智能楼宇, 能量管理, 风险价值法

Abstract:

With the growth of the economic level, the proportion of electricity consumption in buildings continues to increase. Optimizing building energy management strategies can effectively enhance energy conservation and reduce emissions. In commercial building loads, air conditioning loads and electric vehicles loads account for a large proportion of energy consumption. Therefore, a smart commercial building energy management model considering building thermal inertia and incorporating electric vehicle integration was proposed, with the behavioral characteristics of electric vehicles modeled via Monte Carlo simulation. Based on the thermal capacitance-resistance model, a building thermal dynamic balance equation was established. Scenario-based stochastic programming was adopted to establish a smart commercial building energy management model, and Conditional Value at Risk (CVaR) was introduced to improve robustness. The results of case studies showed that considering building thermal inertia could reduce the operating costs of air conditioning loads by 9.7% and increase revenue by 1.4%. Although CVaR reduces the operational risks of buildings, it also lowers their comprehensive expected returns.

Key words: building thermal inertia, electric vehicle, stochastic programming, smart building, energy management, value at risk

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