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Article type: Research Article
Authors: Shi, Jiakuia | Yao, Kuna; * | Sun, Jianguob | Wang, Weic; * | Wan, Jiea | Gu, Weifeid | Tong, Xiaozhongd | Qin, Ganghuad
Affiliations: [a] Harbin Institute of Technology, Harbin, Heilongjiang 150001, China | [b] North Unites the Electric Power Dalate Power Plant, Inner Mongolian Dalate 014300, China | [c] The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China | [d] Zhejiang Zheneng technology institute Co., Ltd, Hangzhou, Zhejiang 310052, China
Correspondence: [*] Corresponding authors: Kun Yao, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China. E-mail: 19b353009 @stu.hit.edu.cn. Wei Wang, The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China. E-mail: wwang@ncepu.edu.cn.
Abstract: Load response characteristics of high thermal power units are critical to a safe and efficient grid-connected utilization of large-scale renewable energy with strong randomness. A condensate throttling regulation was reported to improve the units variable load rate. However, it is not verified by tests in different types of units. In the paper, the influence of the storage capacity of the steam generator’s condensate system on the load response characteristics is studied for four subcritical 330 MW heating units by simulation and an experimental test. The result shows the feasibility of the condensate throttling regulation, which is of great value to the practical engineering application in the future. In addition, this paper obtains the condensate regulation potential of units under different power generation load conditions through simulation and actual tests. These real data will help other units of the same type to carry out similar modifications or tests.
Keywords: Turbine generator units, condensate system, energy-storage utilization, throttling governing, load response
DOI: 10.3233/JCM-204843
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 21, no. 5, pp. 1179-1189, 2021
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