深度调峰下超超临界机组再热汽温控制优化

doi:10.11930/j.issn.1004-9649.201812016

中国电力 ›› 2020, Vol. 53 ›› Issue (5): 143-149.DOI: 10.11930/j.issn.1004-9649.201812016

深度调峰下超超临界机组再热汽温控制优化

丁建良¹, 于国强¹, 罗建裕²

1. 江苏方天电力技术有限公司，江苏南京 211102;
2. 国网江苏省电力有限公司，江苏南京 210009

收稿日期:2018-12-05 修回日期:2019-11-20 发布日期:2020-05-05
作者简介:丁建良(1969-),男,高级工程师,从事火电厂运行控制研究,E-mail:djl6815@sina.com;于国强(1979-),男,通信作者,硕士,从事火电机组自动控制技术研究,E-mail:guoqiang.yu@163.com;罗建裕(1961-),男,高级工程师,从事电网调控运行管理工作,E-mail:hoffmanluo@sina.com
基金资助:
国网江苏省电力有限公司科技项目（特高压输电条件下大受端电网源网快速协调关键技术及安全性研究，J2017006）

Optimization of Reheat Steam Temperature Control for Ultra-Supercritical Units under Deep Peak Shaving

DING Jianliang¹, YU Guoqiang¹, LUO Jianyu²

1. Jiangsu Frontier Electric technology Co.,Ltd., Nanjing 211102, China;
2. State Grid Jiangsu Electric Power Co., Ltd., Nanjing 210009, China

Received:2018-12-05 Revised:2019-11-20 Published:2020-05-05
Supported by:
This work is supported by Science and Technology Project of State Grid Jiangsu Electric Power Co., Ltd. (Research on Key Technology and Safety of Rapid Coordination of Large-Shoulder Grid Source Network under UHV Transmission Conditions, No.J2017006)

摘要/Abstract

摘要： 火电厂在深度调峰过程中存在再热器出口汽温大延迟、大惯性和非线性等特点，使控制效果变差或难以投自动，提出一种基于模糊切换的仿人智能控制算法，对再热汽温控制系统进行优化，并利用粒子群算法结合控制经验对参数进行选择，仿真结果表明该方法增强了再热汽温控制系统的鲁棒性。在某1 000 MW超超临界机组的实际投运中取得较好的控制效果，有效提高了机组的经济性和安全性。

关键词: 再热汽温控制, 模糊切换, 仿人智能控制, 粒子群算法

Abstract: In view of the long time delay, large inertia and strong nonlinearity of the reheater outlet steam temperature in the process of deep peak shaving in thermal power plants, which makes the control less effective or hard to be put into service automatically, this paper proposes a humanoid intelligent control algorithm based on fuzzy switching. This method first optimizes the reheat steam temperature control system, and then uses the particle swarm optimization algorithm combined with the control experience to select the parameter settings. The simulation results show that the proposed method can enhance the robustness of the reheat steam temperature control system. In the actual operation of a 1 000 MW ultra-supercritical unit, satisfactory results have been achieved through this approach, which effectively improved the economic and security of the unit operation.

Key words: reheat steam temperature control, fuzzy switching, human simulation intelligent control, particle swarm optimization

丁建良, 于国强, 罗建裕. 深度调峰下超超临界机组再热汽温控制优化[J]. 中国电力, 2020, 53(5): 143-149.

DING Jianliang, YU Guoqiang, LUO Jianyu. Optimization of Reheat Steam Temperature Control for Ultra-Supercritical Units under Deep Peak Shaving[J]. Electric Power, 2020, 53(5): 143-149.

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深度调峰下超超临界机组再热汽温控制优化

Optimization of Reheat Steam Temperature Control for Ultra-Supercritical Units under Deep Peak Shaving

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深度调峰下超超临界机组再热汽温控制优化

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