姓名: 李铮伟
性别:

出生年月:

1981-10-29

职称:

副教授

党政职务:

研究方向:

建筑能源系统的优化运行及故障诊断等
导师类型: 硕导

通讯地址:

上海市四平路1239号,同济大学四平路,机械与能源工程学院

电子邮箱:

zhengwei_li@tongji.edu.cn

教育背景:

2003年9月,西安交通大学,建筑环境与设备工程专业,学士

2006年9月,西安交通大学,动力工程及工程热物理,硕士

2012年5月,美国佐治亚理工学院,建筑系,博士

工作履历:

2013年10月至今,同济大学暖通空调研究所,助理教授

2012年5月-2013年9月,香港城市大学,博士后

学术兼职:

中国暖通空调学会模拟分会青年委员、秘书;

中国建筑性能模拟学会会员;

上海市制冷学会会员;

 

研究领域:

1)暖通空调系统的故障诊断及优化运行

2)基于分项计量系统的全建筑能耗诊断及预测

详细请见 http://energygeek.cn

在研项目 :

[1] 同济大学青年优秀人才培养计划,2014KJ029,微环境与建筑能耗的耦合模拟,同济大学资助,10万元,负责,2015.1-2016.12

[2] 上海市浦江人才计划,15PJ1408100,基于分项计量数据对规则型公共建筑运行策略的识别和寻优,上海市科委,20万元,负责, 2015.7-2017.7

[3] 国家青年科学基金项目,51508394,基于数据挖掘方法及不确定性分析对公共建筑冷水机组群控策略的识别、评估和优化方法研究,国家自然科学基金委,20万元,负责, 2016.1-2018.12

 

学术成果与奖励:

[1] 第三届美国建筑性能模拟会议最佳论文奖,2008

[2] 国际建筑性能模拟会议学生竞赛团体奖,2009

[3] 第四届美国建筑性能模拟会议学生奖学金,2010

论文:

[1] Y. Ruan, J. Cao, F. Feng, Z. Li, The role of occupant behavior in low carbon oriented residential community planning: a case study in Qingdao, Energy and Buildings 139 (2017) 385-394

[2] X. Wang, Z. Li, H. Meng, Identification of key energy efficiency drivers through global city benchmarking: a data driven approach, Applied Energy 190 (2017) 18-28.

[3] F. Feng, Z. Li, Y. Ruan, An empirical study of influencing factors on residential building energy consumption in Qingdao city, China, Energy Procedia 104 (2016) 245-250.

[4] Z. Li, S. J. Quan, P. P. Yang, Energy performance simulation for planning a low carbon neighborhood urban district: a case study in the city of Macau, Habitat International 53 (2016) 206-214.

[5] Z. Li, G. Huang, Y. Sun, Stochastic chiller sequencing control, Energy and Buildings 84 (2014) 203-213. (SCI)
[6] Z. Li, G. Huang, A Hybrid Technique to Reduce the Impact of Measurement Uncertainty in HVAC Systems, HVAC&R Research 20 (2014) 581-591. (SCI)
[7] Z. Li, Y. Han, P. Xu, Methods for benchmarking building energy consumption against its past or intended performance: An overview, Applied Energy 124 (2014) 325-334. (SCI)
[8] B. Dong, Z. O’Neill, Z. Li, A BIM-enabled information infrastructure for building energy Fault Detection and Diagnostics, Automation in Construction 44 (2014) 197-211. (SCI)
[9] P. Zhou, G. Huang, Z. Li, Demand-based temperature control of large-scale rooms aided by wireless sensor network: energy saving potential analysis, Energy and Buildings 68 (2014) 532-540. (SCI)
[10] Y. Sun, G. Huang, Z. Li, Multiplexed optimization for complex air conditioning systems, Building and Environment 65 (2013) 99-108. (SCI)
[11] Z. Li, G. Huang, Preventive approach to determine sensor importance and maintenance requirements, Automation in Construction 31 (2013) 307-312. (SCI)
[12] Z. Li, G. Huang, Re-evalulation of building cooling load prediction models for use in humid subtropical area, Energy and Buildings 62 (2013) 442-449. (SCI)
[13] Z. Li, C. J. J. Paredis, G. Augenbroe, et al., A rule augmented statistical method for air-conditioning system fault detection and diagnostics, Energy and Buildings 54 (2012) 154-159. (SCI)
[14] Z. Li, C. J. J. Paredis, G. Augenbroe, Using CUSUM method to detect faults in secondary HVAC systems, ASHRAE Transactions 118 (1) (2012) 151-158. (ISTP)


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