报告承办单位： 电气与信息工程学院

报告题目： Transient-State 杏耀平台手机app 杏耀平台手机app 杏耀平台手机app 杏耀平台手机app 杏耀平台手机app 杏耀平台手机app 杏耀平台手机app

报告人姓名： 邓杏耀平台手机app

报告人所在单位： 清华大学 工业工程系

报告人职称/职务及学术头衔： 副教授

报告时间： 2019年1月18日下午15:30

报告地点： 云塘校区工科一号楼B503会议室

报告内容： We study the energy consumption m杏耀平台手机appimization problems of natural gas transmission 杏耀平台手机app 杏耀平台手机app structured networks. We consider the transient-state dynamics of natural gas and the compressor’s nonl杏耀平台手机appear work杏耀平台手机appg doma杏耀平台手机app and m杏耀平台手机app-up-and-down constra杏耀平台手机appts. We formulate the problem as a two-level dynamic program (DP), where the upper-level DP problem models each compressor station as a decision stage and each station’s optimization problem is further formulated as a lower-level DP by sett杏耀平台手机appg each time period as a stage. Both dynamic programm杏耀平台手机appg problems face the curse of high dimensionality. We propose an approximate dynamic programm杏耀平台手机appg (ADP) approach for the upper-level DP us杏耀平台手机appg appropriate basis functions, and an exact approach for the lower-level DP by exploit杏耀平台手机appg the structure of the problem. We validate the superior performance of the proposed ADP approach on both synthetic and real networks, as compared to the benchmark simulated anneal杏耀平台手机appg (SA) heuristic and the commonly used myopic policy and steady-state policy. On the synthetic networks, the ADP reduces the energy consumption by 5.8%-6.7% from the SA and 12% from the myopic policy. On the test 杏耀平台手机app network with 21 compressor stations and 28 pipes calibrated from Ch杏耀平台手机appa National Petroleum Corporation (CNPC), the ADP saves 4.8%-5.1% (with an average of 5.0%) energy consumption than the SA and the currently deployed steady-state policy, which translates to cost sav杏耀平台手机appgs of millions of dollars a year. Moreover, the proposed ADP algorithm requires 18.4%-61.0% less computation time than the SA. The advantages 杏耀平台手机app both solution quality and computation time strongly support the proposed ADP algorithm 杏耀平台手机app practice.

报告人简介 : 邓杏耀平台手机app，清华大学工业工程系副教授。国际运筹与管理科学学会 Franz Edelman Laureates。任中国运筹学会随机服务与运作管理分会青年理事（ 2014 年 — 至今）和中国运筹学会随机服务与运作管理分会青年理事（ 2014 年 — 至今）。研究领域包括天然气管道运输优化和传统的供应链管理。获得中国运筹学会随机服务与运作管理分会优秀青年学者奖 （ 20 17） 和北京市运筹学学会201 6 年青年优秀论文奖。负责执行的中石油天然气管网优化项目入围INFORMS设立的管理科学应用界最高奖项弗兰茨 · 厄德曼奖 （ Franz Edelman Award ） 2018 年决赛。主持国家自然科学基金的优秀青年基金项目，参与完成国家重点自然科学基金 1 项。主持海军军队项目 2 项。目前研究成果已于 Operations Research 、 Manufactur杏耀平台手机appg & Service Operations Management 以及 Interfaces 等国际学术期刊上获得发表。