田喆
工学博士，教授，博士生导师，注册公用设备(暖通空调)工程师，天津市建筑环境与能源重点实验室副主任，全国暖通空调学会性能模拟专委会委员，中国绿建与建筑节能专委会委员，天津可再生能源学会理事，天津市电子计算机应用协会理事。2013年受聘天津大学教授，从事建筑节能领域的科研和教学工作，主要研究领域：建筑综合能源系统、暖通空调系统运行优化与数据分析、建筑与城市气候等。
Prof. Dr. TIAN Zhe, vice director of key lab of building Environment and Building Energy of Tianjin Municipality, Committee member of HVAC simulation, member of China Green building and energy saving society, director of renewable energy society of Tianjin. He was employed as professor in 2013, working on building energy saving, main interests includes: building integrated energy system, operation optimization of HVAC system, building and urban climate.
联系方式/contact
Email: tianzhe@tju.edu.cn
Tel: +86 13920440039
一、 承担科研项目/Research Projects：
1. 国家自然科学基金面上项目， “基于时序数据逆向解析的建筑耗热量热流组分定向提取方法”，项目负责人， 2018.1-2021.12;
“Extraction of component flux of building cooling load based on time series data disaggregation”, National Science Found Committee, 2018-2021;
2. 国家“十三五”重点研发计划“多能互补集成优化的分布式能源系统”项目课题“分布式综合能源系统联合仿真技术”, 课题负责人， 2017.7-2021.6;
“Co-simulation of distributed integrated energy system”, National key research project, 2017-2021;
3. 国家“十三五”重点研发计划“建筑全性能仿真平台内核开发”项目子课题“建筑机电系统和可再生能源系统与建筑热过程耦合计算模型开发”，子课题负责人，2017.7-2020.12;
“Building full performance simulation platform core tech development”, National key research project, 2017-2020;
4. 国家自然科学基金面上项目，“基于可靠性预期的空调室外计算参数确定”，项目负责人，2020.1 - 2024.12;
“The generation of climatic design condition of building HVAC based on probability prediction”, National Science Found Committee, 2020-2024;
5. 企业课题，波音舟山飞机交付中心机电系统综合调试技术，项目负责人，2018.7-2020.6
“Commissioning of HVAC system in Boeing Plant in Zhoushan”.2018-2019
6. 企业课题，“基于数据挖掘的集中供热换热站智能运行策略和运行评价诊断研究”，项目负责人，2018.12-2019.12
“The generation of operation strategy of Heating sub-station based on data mining”, 2018-2019
7. 雄安国网综合能源监控集中供能运行调度功能算法开发，项目负责人，2019.10-2020.12
“XiongAn city intelligent energy management system - integrated energy system dispatch and operation strategy algorithm development”，2019.10-2020.12
二、论文发表/Publishments
1. Jide Niu, Zhe Tian, Yakai Lu, Hongfang Zhao, Bo Lan, A robust optimization model for designing the building cooling source under cooling load uncertainty, Applied Energy, Volume 241, May 2019, Pages 390-403
2. Jide Niu, Zhe Tian, Yakai Lu, Hongfang Zhao, Flexible dispatch of a building energy system using building thermal storage and battery energy storage, Applied Energy, Volume 243, 1 June 2019, Pages 274-287
3. Qiang Zhang, Zhe Tian, Yan Ding, Yakai Lu, Jide Niu, Development and evaluation of cooling load prediction models for a factory workshop, Journal of Cleaner Production, In press, accepted manuscript, Available online 10 May 2019
4. Xinyi Lin, Zhe Tian, Yakai Lu, Hejia Zhang, Jide Niu, Short-term forecast model of cooling load using load component disaggregation, Applied Thermal Engineering, Volume 157, 5 July 2019
5. LI Yang, TIAN Zhe, QIN Kaiming, NIU Jide, ZHAO Hongfang, Impacts of water storage on robust optimal design of cooling system considering uncertainty, Energy Procedia, Volume 159, February 2019, Pages 430-435
6. Wenxuan Han, Zhe Tian, Yuanyuan Wang, Hejia Zhang, Jide Niu, Evaluation on determination method of current climate design conditions in China based on indoor thermal environment risk level, Energy, Volume 161, October 2018, Pages 610-617
7. Wancheng Li, Zhe Tian, Yakai Lu, Fawei Fu, Stepwise calibration for residential building thermal performance model using hourly heat consumption data, Energy and Buildings, Volume 181, 15 December 2018, Pages 10-25
8. Lu YK, Tian Z. Peng P. Niu JD, Li WC, Zhang HJ, GMM clustering for heating load patterns in-depth identification and prediction model accuracy improvement of district heating system, ENERGY AND BUILDINGS, Vol.190, P 49-60, MAY 1 2019
9. Zhe Tian, Jide Niu, Yakai Lu. The improvement of a simulation model for a distributed CCHP system and its influence on optimal operation cost and strategy, Applied Energy, Vol165, 1 2016, 430-444
10. Guo Qiang, Tian Zhe, Ding Yan, Zhu Neng. An improved office building cooling load prediction model based on multivariable linear regression, Energy and Buildings, Vol107, 15 Nov 2015: 445-455