高背压抽凝热电联供系统建模及快速变负荷控制策略研究

doi:10.12096/j.2096-4528.pgt.24208

发电技术 ›› 2025, Vol. 46 ›› Issue (6): 1074-1084.DOI: 10.12096/j.2096-4528.pgt.24208

• 分布式能源 • 上一篇

高背压抽凝热电联供系统建模及快速变负荷控制策略研究

展宗波¹, 任吉平¹, 丁立平¹, 孙兆龙¹, 丁衡², 曹越²

^1.内蒙古京隆发电有限责任公司，内蒙古自治区丰镇市 012100
^2.能源热转换及;过程测控教育部重点实验室(东南大学)，江苏省南京市 210096

收稿日期:2024-09-14 修回日期:2024-12-26 出版日期:2025-12-31 发布日期:2025-12-25
通讯作者: 曹越
作者简介:展宗波(1980)，男，高级工程师，研究方向为燃煤机组运行优化及数字化技术，dhp129@163.com；
曹越(1989)，男，博士，副教授，研究方向为热力系统性能优化、智能控制理论等，本文通信作者，ycao@seu.edu.cn。
基金资助:
国家自然科学基金项目(52206006)

Research on Modeling and Rapid Load Change Control Strategy for High Back- Pressure Extraction-Condensing Combined Heat and Power System

Zongbo ZHAN¹, Jiping REN¹, Liping DING¹, Zhaolong SUN¹, Heng DING², Yue CAO²

^1.Inner Mongolia Jinglong Power Generation Co. , Ltd. , Fengzhen 012100, Inner Mongolia Autonomous Region, China
^2.Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education (Southeast University), Nanjing 210096, Jiangsu Province, China

Received:2024-09-14 Revised:2024-12-26 Published:2025-12-31 Online:2025-12-25
Contact: Yue CAO
Supported by:
National Natural Science Foundation of China(52206006)

摘要/Abstract

摘要：

目的热电联供机组快速变负荷能够保障电网对新能源的消纳能力，对提高火电机组经济效益也具有重要作用。因此，以某电厂高背压抽凝热电联供系统为研究对象，结合其高背压乏汽配合供热抽汽实现热网回水梯级加热的特点，开展了系统建模、动态特性分析及快速变负荷控制策略的研究。方法基于APROS仿真平台构建了系统的动态特性模型，通过现场运行数据验证了模型的准确性；研究了变工况下系统热电调节过程的动态响应特性，建立了不同工况下机组热、电负荷与抽汽调节蝶阀；提出了一种耦合供热抽汽调节的机组快速变负荷控制策略，通过调节蝶阀前馈补偿实现机组出力的快速变化，提高了机组的变负荷响应速度。结果与热电协调控制相比，快速变负荷策略响应自动发电控制(automatic generation control，AGC)指令的时间缩短150 s，到达稳态所用时间缩短300 s。结论双机热电联供系统快速变负荷控制策略能够显著提高系统对AGC指令的响应速度，且过渡过程的震荡更小，到达稳态所用的时间更短。

关键词: 热电联供系统, 新能源消纳, 抽汽阀门控制, 快速变负荷, 协调控制系统, 高背压, 抽汽调节蝶阀

Abstract:

Objectives Rapid load change capability of combined heat and power units can ensure the consumption capacity of the power grid for renewable energy and play an important role in improving the economic efficiency of thermal power units. Therefore, taking a high back-pressure extraction-condensing combined heat and power system in a power plant as the research object, this study focuses on system modeling, dynamic characteristic analysis, and rapid load change control strategy, leveraging the characteristics of its high back-pressure exhaust steam and heating extraction steam to achieve cascade heating of the return water in the heating network. Methods A dynamic characteristic model of the system is established based on the APROS simulation platform, and the accuracy of the model is verified using on-site operation data. The dynamic response characteristics of the thermal and electrical regulation process of the system under varying operating conditions are investigated, and the relationship between the thermal and electrical loads of the unit and the steam extraction valve (EV) under different operating conditions is established. A rapid load change control strategy coupling the heating steam extraction regulation of the unit is proposed. By implementing feedforward compensation at the EV valve, rapid changes of the unit output are realized, improving its load change response speed. Results Compared to coordinated thermal-electrical control, the rapid load change strategy reduces the response time to automatic generation control (AGC) commands by 150 seconds and shortens the time to reach steady state by 300 seconds. Conclusions The rapid load change control strategy for the dual-unit combined heat and power system significantly enhances the response speed of the system to AGC commands, with reduced oscillations during the transition process and a shorter time to reach steady state.

Key words: combined heat and power system, new energy consumption, steam extraction valve control, rapid load change, coordinated control system, high back-pressure, steam extraction regulation butterfly valve

中图分类号:

TK 32

展宗波, 任吉平, 丁立平, 孙兆龙, 丁衡, 曹越. 高背压抽凝热电联供系统建模及快速变负荷控制策略研究[J]. 发电技术, 2025, 46(6): 1074-1084.

Zongbo ZHAN, Jiping REN, Liping DING, Zhaolong SUN, Heng DING, Yue CAO. Research on Modeling and Rapid Load Change Control Strategy for High Back- Pressure Extraction-Condensing Combined Heat and Power System[J]. Power Generation Technology, 2025, 46(6): 1074-1084.

图/表 12

图1 高背压抽凝热电联供系统图

Fig. 1 Diagram of high back-pressure extraction-condensing combined heat and power system

图2 高背压抽凝热电联供系统整体模型图

Fig. 2 Overall model of high back-pressure extraction-condensing combined heat and power system

图3 供热机组输入输出变量

Fig. 3 Input and output variables of heating unit

图4 高背压机组THA工况EV调节过程相关参数随时间变化曲线

Fig. 4 Time variation curves of related parameters during EV adjustment under THA condition in high back-pressure unit

图5 THA工况EV阀调节过程汽轮机各缸做功能力随时间变化曲线

Fig. 5 Time variation curves of mechanical power output of turbine cylinders during EV regulation under THA condition

图6 EV阀调节过程抽凝机组电功率与供热量随时间变化曲线

Fig. 6 Time variation curves of electric power and heat supply during EV regulation in extraction-condensing unit

图7 THA工况电、热负荷与EV开度的对应关系

Fig. 7 Relationship between electrical and thermal loads and EV opening under THA condition

图8 不同工况下相关参数随EV开度的变化关系

Fig. 8 Relationship between variations of relevant parameters and EV opening under different operating conditions

图9 抽凝机组电、热负荷与EV开度对应关系的拟合曲面

Fig. 9 Fitting surface of relationship between electrical and thermal loads and EV opening in extraction-condensing unit

图10 高背压机组电、热负荷与EV开度对应关系的拟合曲面

Fig. 10 Fitting surface of relationship between electrical and thermal loads and EV opening in high back-pressure unit

表1 各机组热耗特性曲面拟合系数

Tab. 1 Fitting coefficients of heat consumption characteristic surfaces of each unit

系数	高背压抽凝机组拟合值(j=1)	抽凝机组拟合值(j=2)
z₀	-1.619	1.233
a	8.085×10^-3	-1.691×10^-2
b	5.523×10^-3	6.417×10^-3
c	-1.157×10^-5	7.915×10^-5
d	-2.876×10^-5	-7.074×10^-5
e	7.816×10^-6	1.942×10^-5
f	3.877×10^-9	-1.338×10^-7
g	3.911×10^-8	2.008×10^-7
h	-2.269×10^-8	-1.095×10^-7
i	5.054×10^-9	1.952×10^-8

图11 3种控制策略下的电负荷响应曲线对比图

Fig. 11 Comparison of electrical load response curves under three control strategies

参考文献 21

[1]	刘洪波，刘珅诚，盖雪扬，等．高比例新能源接入的主动配电网规划综述[J]．发电技术，2024，45(1)：151-161． doi:10.12096/j.2096-4528.pgt.22106
	LIU H B， LIU S C， GAI X Y，et al ．Overview of active distribution network planning with high proportion of new energy access[J]．Power Generation Technology，2024，45(1)：151-161． doi:10.12096/j.2096-4528.pgt.22106
[2]	李令宇，程浩忠，张衡，等．含高比例新能源电力系统的低碳电源规划方法[J]．电测与仪表，2025，62(7)：30-37．
	LI L Y， CHENG H Z， ZHANG H，et al ．Low-carbon power planning method for power system with high proportion of renewable energy[J]．Electrical Measurement & Instrumentation，2025，62(7)：30-37．
[3]	于晓军，刘志远，王洪炳，等．考虑新能源并网影响的零序过电压解列策略[J]．电测与仪表，2024，61(6)：111-117．
	YU X J， LIU Z Y， WANG H B，et al ．Zero-sequence overvoltage splitting strategy considering the impact of new energy grid connection[J]．Electrical Measurement & Instrumentation，2024，61(6)：111-117．
[4]	杨金洲，李业成，熊鸿韬，等．新能源接入的受端电网暂态电压失稳高风险故障快速筛选[J]．电工技术学报，2024，39(21)：6746-6758．
	YANG J Z， LI Y C， XONG H T，et al ．A fast screening method for the high-risk faults with transient voltage instability in receiving-end power grids interconnected with new energy[J]．Transactions of China Electrotechnical Society，2024，39(21)：6746-6758．
[5]	马燕峰，程有深，赵书强，等．双馈风电场并网引起火电机组多模态次同步谐振机理分析[J]．电工技术学报，2025，40(5)：1395-1410．
	MA Y F， CHENG Y S， ZHAO S Q，et al ．Mechanism analysis of multi-mode ssr of thermal power unit caused by doubly fed wind farm integration[J]．Transactions of China Electrotechnical Society，2025，40(5)：1395-1410．
[6]	周一凡，胡伟，闵勇，等．热电联产参与电网调峰补偿定价与利益分配方法[J]．中国电机工程学报，2019，39(18)：5325-5335．
	ZHOU Y F， HU W， MIN Y，et al ．Peak regulation compensation price decision for combined heat and power unit and profit allocation method[J]．Proceedings of the CSEE，2019，39(18)：5325-5335．
[7]	周昊，陈振寰，张佳凯，等．富氧/水-氧条件下准东煤熔融特性研究[J]．发电技术，2019，40(3)：208-212．
	ZHOU H， CHEN Z H， ZHANG J K，et al ．Study on melting characteristics of zhundong coal under Oxygen-rich/H₂O-O₂ Conditions[J]．Power Generation Technology，2019，40(3)：208-212．
[8]	陈晓利，高继录，郑飞，等．多种深度调峰模式对火电机组性能影响分析[J]．热能动力工程，2020，35(12)：26-30．
	CHEN X L， GAO J L， ZHENG F，et al ．Comparative analysis of various deep peak regulation modes for thermal power units[J]．Journal of Engineering for Thermal Energy and Power，2020，35(12)：26-30．
[9]	中国可再生能源学会风能专业委员会．2023年中国风电吊装容量统计简报[J]．风能，2024(5)：52-67．
	Wind Energy Professional Committee of China Renewable Energy Society ．Statistical briefing on hoisting capacity of chinoiserie power in 2022[J]．Wind Energy，2024(5)：52-67．
[10]	ZHAI L M， CHEN Y S， LI Z W，et al ．Study on the adaptability of extracting steam and heat return pipe system of heating unit[J]．Energy and Environment Research，2021，11(2)：65-71． doi:10.5539/eer.v11n2p71
[11]	马良玉，成蕾，彭钢，等．基于神经网络预测模型和凝结水节流的超超临界机组协调系统智能优化控制[J]．动力工程学报，2017，37(8)：640-648．
	MA L Y， CHENG L， PENG G，et al ．Intelligent control optimization for the coordinated system of an ultra-supercritical power unit based on neural network prediction models and condensate throttling[J]．Journal of Chinese Society of Power Engineering，2017，37(8)：640-648．
[12]	邓拓宇．供热机组储能特性分析与快速变负荷控制[D]．北京：华北电力大学，2016．
	DENG T Y ．Analysis of energy storage characteristics of heating unit and rapid load change control[D]．Beijing：North China Electric Power University，2016．
[13]	MA L， GE Z， ZHANG F，et al ．A novel super high back pressure cascade heating scheme with multiple large-scale turbine units[J]．Energy，2020，201：117469． doi:10.1016/j.energy.2020.117469
[14]	HEDEGAARD K， MÜNSTER M ．Influence of individual heat pumps on wind power integration-Energy system investments and operation[J]．Energy Conversion and Management，2013，75：673-684． doi:10.1016/j.enconman.2013.08.015
[15]	张云鹏，金晶，高新勇，等．配置蓄热装置对热电机组运行经济性的影响分析[J]．热能动力工程，2022，37(8)：143-149．
	ZHANG Y P， JIN J， GAO X Y，et al ．Analysis of the influence of heat storage device on the operation economy of thermal power unit[J]．Journal of Engineering for Thermal Energy and Power，2022，37(8)：143-149．
[16]	ZHAO Y， WANG C， LIU M，et al ．Improving operational flexibility by regulating extraction steam of high-pressure heaters on a 660 MW supercritical coal-fired power plant：a dynamic simulation[J]．Applied Energy，2018，212：1295-1309． doi:10.1016/j.apenergy.2018.01.017
[17]	胡勇．基于汽轮机蓄能特性的大型火电机组快速变负荷控制研究[D]．北京：华北电力大学，2015．
	HU Y ．Research on fast load changing control of large thermal power units based on energy storage characteristics of steam turbine[D]．Beijing：North China Electric Power University，2015．
[18]	卫丹靖．供热机组建模及快速变负荷控制[D]．北京：华北电力大学，2017． doi:10.17775/cseejpes.2017.0012
	WEI D J ．Modeling of heating unit and rapid variable load control[D]．Beijing：North China Electric Power University，2017． doi:10.17775/cseejpes.2017.0012
[19]	刘鑫屏，田亮，王琪，等．供热机组发电负荷-机前压力-抽汽压力简化非线性动态模型[J]．动力工程学报，2014，34(2)：115-121．
	LIU X P， TIAN L， WANG Q，et al ．Simplified nonlinear dynamic model of generating load-throttle pressure-extraction pressure for heating units[J]．Journal of Chinese Society of Power Engineering，2014，34(2)：115-121．
[20]	邓拓宇，田亮，刘吉臻．供热机组负荷指令多尺度前馈协调控制方案[J]．热力发电，2016，45(3)：48-53．
	DENG T Y， TIAN L， LIU J Z ．Multi-scale feedforward coordinated control scheme for load command of heat supply units[J]．Thermal Power Generation，2016，45(3)：48-53．
[21]	邓拓宇，田亮，刘吉臻．利用热网储能提高供热机组调频调峰能力的控制方法[J]．中国电机工程学报，2015，35(14)：3626-3633．
	DENG T Y， TIAN L， LIU J Z ．A control method of heat supply units for improving frequency control and peak load regulation ability with thermal storage in heat supply net[J]．Proceedings of the CSEE，2015，35(14)：3626-3633．

高背压抽凝热电联供系统建模及快速变负荷控制策略研究

Research on Modeling and Rapid Load Change Control Strategy for High Back- Pressure Extraction-Condensing Combined Heat and Power System

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