家电科技 ›› 2025, Vol. 0 ›› Issue (4): 30-38.doi: 10.19784/j.cnki.issn1672-0172.2025.04.004

• 论文 • 上一篇    下一篇

海量复杂公共建筑柔性资源调节能力评估

孙冬梅1, 李雨桐1, 赵宇明2, 康靖1, 王振尚2, 王静2   

  1. 1.深圳市建筑科学研究院股份有限公司 广东深圳 518049;
    2.深圳供电局有限公司 广东深圳 518052
  • 出版日期:2025-08-01 发布日期:2025-10-09
  • 通讯作者: 李雨桐,E-mail:liyutong@ibrcn.com。
  • 作者简介:孙冬梅,工学硕士。研究方向:建筑光储直柔技术、建筑调节能力评估、需求响应。地址:上海市杨浦区江浦路627号2号楼201室。E-mail:531386739@qq.com。
  • 基金资助:
    中国南方电网有限责任公司创新项目(090000KK52220020; 090000KC23020078)

Evaluation of the adjustable capacity of flexible resources in massive and complex public buildings

SUN Dongmei1, LI Yutong1, ZHAO Yuming2, KANG Jing1, WANG Zhenshang2, WANG Jing2   

  1. 1. Shenzhen Institute of Building Research Co., Ltd. Shenzhen 518049;
    2. Shenzhen Power Supply Corporation Shenzhen 518052
  • Online:2025-08-01 Published:2025-10-09

摘要: 新型电力系统的“双高”与“双随机”特征,导致系统惯量降低、调节能力减弱,给电力系统的实时供需平衡、安全稳定运行和可再生能源消纳带来了严峻挑战。针对海量公共建筑复杂多变的影响因素,提出了一种分阶段公共建筑调节能力评估方法。一级评估通过能耗指标对标快速筛选具有调节潜力的建筑,为需求响应系统建设提供初步依据;二级评估结合建筑能耗影响因素分析和数据驱动建模方法,定量评估空调系统在不同运行模式、不同调节策略下的逐时可调节功率,满足响应邀约与申报阶段需求;三级评估融合模型与数据驱动方法,精确动态评估空调系统在不同调节策略下的可调节功率和持续时间,适用于执行与效果评估阶段。在深圳公共建筑能耗监测平台中的1212栋建筑中应用了该评估方法,验证了其有效性,为公共建筑需求响应业务提供了科学适用的评估方法参考。

关键词: 公共建筑, 柔性资源, 调节能力评估, 数据驱动, 模型驱动, 需求响应

Abstract: The dual-high and dual-random characteristics of the new power system, combined with the increasingly prominent peak load demand for electricity, have presented significant challenges to the real-time supply-demand balance, safe and stable operation of the power system, and the consumption of renewable energy. A phased evaluation method is proposed for assessing the adjustable capacity of public buildings in order to address the complex and variable factors associated with numerous public buildings. The first-level evaluation rapidly screens buildings with adjustable potential through benchmarking of energy consumption indicators, providing an initial basis for the construction of the demand response system. The second-level evaluation integrates major factors analysis and data-driven modeling methods to quantitatively assess the adjustable capacity of air conditioning systems under different conditions, meeting requirements of the invitation and declaration stages of the demand response. The third-level evaluation combines model-driven and data-driven approaches to precisely and dynamically evaluate the adjustable capacity of air conditioning systems, applicable to the execution and effect evaluation stages. The evaluation method has already been applied to 1212 buildings in the energy consumption monitoring platform for public buildings in Shenzhen, confirming its effectiveness and providing a scientifically viable reference for the demand response business of public buildings.

Key words: Public buildings, Flexible resources, Adjustable capacity evaluation, Data-driven, Model-driven, Demand response

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