程春田

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:男

毕业院校:大连理工大学

学位:博士

所在单位:水利工程系

学科:水文学及水资源. 水利水电工程. 电力系统及其自动化. 计算机应用技术

联系方式:ctcheng@dlut.edu.cn

电子邮箱:ctcheng@dlut.edu.cn

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Coordinated operations of large-scale UHVDC hydropower and conventional hydro energies about regional power grid

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论文类型:期刊论文

发表时间:2016-01-15

发表刊物:ENERGY

收录刊物:SCIE、EI

卷号:95

页面范围:433-446

ISSN号:0360-5442

关键字:UHVDC hydropower; Coordinated operation; Peak shaving; Hydropower transmission; Regional power grid

摘要:The bulk hydropower transmission with one-fourth of its total capacity in China via UHVDC (ultra-high voltage direct current) lines brings a new challenge for receiving power grids. There is an urgent need for coordinated operations about the receiving regional power grids which operate outside energy and their own large plants linked in the AC/DC network. A great operating concern is how to shave peak loads from subordinate provincial power grids using their load differences and various energy source characteristics. The East China Grid, a main receiver of Chinese hydropower transmission and the largest regional power grid, is taken as the example. An integrated framework for coordinating large-scale UHVDC hydropower and conventional hydro energies for power grid peak operation is presented. It divides the original problem into several subproblems according to the types of energy sources. An EPSA (exterior point search algorithm), a heuristic method, and a multi-step optimization algorithm are developed to respectively solve the UHVDC hydropower subproblem, the pumped-storage subproblem, and the conventional hydropower subproblem. These algorithms are integrated into an iterative solution procedure between all subproblems, wherein the EPSA is also applied to allocate power generation among provincial power grids. The proposed method is effective and efficient for coordinating large-scale UHVDC hydropower with conventional hydro energies and for fully responding to different peak loads among provinces, as demonstrated in two case studies. (C) 2015 Elsevier Ltd. All rights reserved.