Optimization Study of Power Plant Direct Flow Cold-end Subsystem Based on Negative Digging

doi:10.12096/j.2096-4528.pgt.21005

Abstract

Abstract:

In view of the unstable performance of the cold-end system of traditional power plants and the high annual operating cost, a mathematical model based on the heat, resistance, civil construction and annual operating cost calculation of the direct flow cold end system based on negative digging depth was established, and the cold end system configuration was obtained from different conditions outside the tower. The optimal configuration was used to analyze the effect of cooling water for intlet tower water temperature, coagulator area unit price and condenser negative digging depth on the performance of cold end system. The results show that reducing the cooling water for intlet tower water temperature and condenser area unit price can reduce the annual operating cost of cold end system. The performance parameters of the cold end system with a negative digging depth of 3 to 5 m reach the lager value. Therefore, selecting the cold end system configuration according to different weather parameters outside the tower can improve the operating efficiency of the power plant and reduce the annual operating cost of the cold end system.

Key words: power plant, direct flow cold-end subsystem, cold-end optimization, negative digging depth, annual operating cost

CLC Number:

TK 264.1

Yun CHEN, Sen LI, Yuanbin ZHAO. Optimization Study of Power Plant Direct Flow Cold-end Subsystem Based on Negative Digging[J]. Power Generation Technology, 2022, 43(4): 655-663.

Figures/Tables 17

Tab. 1 Calculation formula for cold-end optimization

公式名称	公式
热平衡方程	$Q = K × Δ T × A = W c w t w 2 - t w 1$
凝结水温度	$t n = t w 1 + Δ t + δ t$
HEI传热计算法	$K = K 0 F t F m F c$
别尔曼总传热系数法	$K = 4 070 ξ 1 Φ W Φ t Φ z Φ δ$
凝汽器水阻	$H c p = L T × R T × R 1 + ∑ R E$
沟道沿程阻力损失	$v = 1 n R 2 / 3 i 1 / 2$
渠道沿程阻力	$i 0 = n 2 v 2 R 2 y + 1$
管、沟、渠的局部阻力	$h j = ∑ ξ 2 v 2 2 g$
年费用计算	$C = P ⋅ R A F C + A p - A t$
循环水泵耗电费用	$A p = 10 - 4 N b H l G p$
年微增功率收益	$A t = 10 - 4 t l G e ∑ N i$

Tab. 1 Calculation formula for cold-end optimization

公式名称	公式
热平衡方程	$Q = K × Δ T × A = W c w t w 2 - t w 1$
凝结水温度	$t n = t w 1 + Δ t + δ t$
HEI传热计算法	$K = K 0 F t F m F c$
别尔曼总传热系数法	$K = 4 070 ξ 1 Φ W Φ t Φ z Φ δ$
凝汽器水阻	$H c p = L T × R T × R 1 + ∑ R E$
沟道沿程阻力损失	$v = 1 n R 2 / 3 i 1 / 2$
渠道沿程阻力	$i 0 = n 2 v 2 R 2 y + 1$
管、沟、渠的局部阻力	$h j = ∑ ξ 2 v 2 2 g$
年费用计算	$C = P ⋅ R A F C + A p - A t$
循环水泵耗电费用	$A p = 10 - 4 N b H l G p$
年微增功率收益	$A t = 10 - 4 t l G e ∑ N i$

Tab. 2 Calculation parameters of the cold end subsystem

参数	取值
热力计算方法	HEI传热计算法
循泵配置	一机两泵
虹吸井管沟类型	矩形管沟
溢流堰类型	斜交堰
负挖深度/m	0
溢流堰堰顶绝对标高/m	11.8
虹吸井底板绝对标高/m	6
成本电价/［元/(kW^·h)］	0.24
微增电价/［元/(kW^·h)］	0.42
循环水泵效率	0.95
年固定分摊率	0.126 5
年运行时间/h	7 000
汽轮机排气量/(m³/h)	1 728
冷却水进水温度/℃	20
凝汽器单价/(元/m²)	1 000
盐度/(g/kg)	50
冷却管管材	钛管
背压形式	单背压
流程数	2
冷却管外径/mm	25
冷却管壁厚/mm	1
清洁系数	0.85
冷却管长度/m	13.3
管内流速范围/(m/s)	1.0~3.5

Tab. 3 Monthly water temperature and circulating water volume ratio for cold-end optimization

月份	1	2	3	4	5	6	7	8	9	10	11	12
温度/℃	12.6	14.1	17.2	20.8	23.5	24.9	24.9	24.6	23.3	20.6	16.8	13.5
水流量比值	0.85	0.85	0.85	1.00	1.00	1.00	1.00	1.00	1.00	1.00	0.85	0.85

Fig. 1 Loop flowchart for cold-end optimization

Tab. 4 Best back pressure of each month for cold-end optimization

月份	1	2	3	4	5	6	7	8	9	10	11	12
温度/℃	12.6	14.1	17.2	20.8	23.5	24.9	24.9	24.6	23.3	20.6	16.8	13.5
最佳背压/kPa	3.26	3.54	4.17	5.30	6.10	6.55	6.55	6.45	6.03	5.24	4.09	3.42

Tab. 5 The top ten optimal configuration parameters before cold-end optimization

参数组号	背压/kPa	冷却面积/m²	冷却倍率	主径/m	年费用/万元	水流量/(m³/h)	扬程/m	管根数	管流速/(m/s)
1	5.16	62 000	55	3.7	3 050.005	95 040	23.43	32 258	2.0
2	5.21	59 000	55	4.0	3 050.396	95 040	23.40	30 697	2.1
3	5.21	59 000	55	3.9	3 051.587	95 040	23.55	30 697	2.1
4	5.21	59 000	55	3.8	3 054.168	95 040	23.72	30 697	2.1
5	5.28	58 000	54	3.6	3 054.207	93 312	23.96	30 176	2.1
6	5.19	61 000	55	3.8	3 054.595	95 040	23.38	31 737	2.0
7	5.16	62 000	55	3.6	3 056.241	95 040	23.67	32 258	2.0
8	5.10	63 000	56	4.1	3 056.930	96 768	22.96	32 778	2.0
9	5.10	63 000	56	4.0	3 057.287	96 768	23.09	32 778	2.0
10	5.21	59 000	55	3.7	3 058.411	95 040	23.93	30 697	2.1

Fig. 2 Influence of cooling water temperature on back pressure and cooling rate

Fig. 3 Influence of cooling water temperature on cooling area and main pipe diameter

Fig. 4 Influence of cooling water temperature on circulating pump lift and cooling water flow rate

Fig. 5 Influence of cooling water temperature on annual cost value

Fig. 6 Influence of condenser area price on back pressure and cooling rate

Fig. 7 Influence of condenser area price on cooling area and main pipe diameter

Fig. 8 Influence of condenser area price on circulating pump lift and cooling water velocity

Fig. 9 Influence of condenser area price on annual cost value

Fig. 10 Influence of negative digging depth on cooling area and cooling rate

Fig. 11 Influence of negative digging depth on main pipe diameter and circulating pump lift

Fig. 12 Influence of negative excavation depth on cooling water outlet temperature and flow rate

References 21

1	王玮．火电机组冷端系统建模与节能优化研究[D]．北京：华北电力大学，2011．
	WANG W ． Research on modeling and energy-saving optimization of cold end system in thermal power units[D]．Beijing： North China Electric Power University， 2011．
2	GAO X， ZHANG C， WEI J， et al ． Numerical simulation of heat transfer performance of an air-cooled steam condenser in a thermal power plant[J]．Heat & Mass Transfer， 2009， 45(11) ：1423-1433． doi:10.1007/s00231-009-0521-x
3	LASKOWSKI R ． Relations for steam power plant condenser performance in off-designconditions in the function of inlet parameters and those relevant in reference conditions[J]．Applied Thermal Engineering， 2016， 103 ： 528-536． doi:10.1016/j.applthermaleng.2016.04.127
4	SUN J L， XUE R J， PENG M J ． Investigation of the thermal characteristics ofcondensers in nuclear power plant by simulation with zoning model[J]．Annals of Nuclear Energy，2018， 113 ： 37-47． doi:10.1016/j.anucene.2017.11.015
5	AHMED H， YAHYA R， ABRAHAM E ． Feasibility of using vapor compressionrefrigeration system for cooling team plant condenser[J]．Applied Thermal Engineering，2016， 106 ： 570-578． doi:10.1016/j.applthermaleng.2016.06.005
6	EDRAN M V， BRANIMIR P， VEDRAN M ． Numerical model foron-condition monitoring of condenser in coal-fired power plants[J]．International Journal of Heat and Mass Transfer，2018， 117： 912-923． doi:10.1016/j.ijheatmasstransfer.2017.10.047
7	唐江，王学栋，赵玉柱，等．凝汽机组高背压供热改造后的性能指标与调峰能力分析[J]．发电技术，2018，39(5)：455-461． doi:10.12096/j.2096-4528.pgt.2018.070
	TANG J， WANG X D， ZHAO Y Z， et al ． Analysis of performance indicators and peak regulation capacity of condensing unit after high back pressure retrofit for heating[J]．Power Generation Technology， 2018，39(5)：455-461． doi:10.12096/j.2096-4528.pgt.2018.070
8	卢怀钿，钟少伟．1 036 MW机组汽轮机冷端运行优化及循泵双速节能改造的试验研究[J]．电力建设，2011，32(7)：109-112．
	LU H T， ZHONG S W ． Experimental research on Double speed energy efficiency innovation of water circulation pump and operation optimization of cold end system for 1 036 MW steam turbine units[J]．Electric Power Construction， 2011，32(7)：109-112．
9	王东海，赵云驰．滨海核电厂配置单、双背压凝汽器技经分析[J]．电力建设， 2013， 34(3)： 80-83． doi:10.3969/j.issn.1000-7229.2013.03.018
	WANG D H， ZHAO Y C ． Technical and economic analysis on single and double backpressure condensers in coastal nuclear power plants[J]．Electric Power Construction， 2013， 34(3)： 80-83． doi:10.3969/j.issn.1000-7229.2013.03.018
10	李振鹏，陶志伟，侯平利，等．内陆核电厂冷端系统参数优化分析[J]．核科学与工程， 2010， 30(S1)： 211-216．
	LI Z P， TAO Z W， HOU P L， et al ．Optimised analysis of cold-end system parameters of inland nuclear power plants[J]．Nuclear Science and Engineering， 2010， 30(S1)： 211-216．
11	黄璟晗． F级联合循环冷端系统优化方案研究[J]．汽轮机技术， 2020， 62(1)： 73-74．
	HUANG J H ． Study of F class GTCC cold junction optimization[J]．Turbine Technology， 2020， 62(1)： 73-74．
12	杨若冰，牛华寺，白玮，等．直流冷却核电厂冷端系统优化探讨[J]．给水排水， 2018，54(S1)： 28-31．
	YANG R B， NIU H S， BAI W， et al ． Discussion cold nd optimization in nuclear power plant with once-through cooling mode[J]．Water & Wastewater Engineering， 2018， 54(S1)： 28-31．
13	王奔，司风琪，刘海军．燃煤电厂300 MW机组循环水系统运行优化研究[J]．热能动力工程， 2017， 32(11)： 78-85．
	WANG B， SI F Q， LIU H J ． Study on operation optimization for circulating water system of 300 MW unit in a coal-fired power plant[J]．Journal of Engineering for Thermal Energy and Power， 2017， 32(11) ： 78-85．
14	李萍，王鹏，周建新，等．基于自适应模型的热电联产机组循环水系统运行优化[J]．中国电机工程学报， 2018， 38(18)： 5500-5509．
	LI P， WANG P， ZHOU J X， et al ． Circulating water system operation optimization of cogeneration units based on adaptive model[J]．Proceedings of the CSEE． 2018，38(18)： 5500-5509．
15	赵银亮． AP1000核电机组冷端设计优化研究[D]．北京：华北电力大学， 2016．
	ZHAO Y L ．Study on optimal design cold-end system of an AP1000 nuclear power plant[D]．Beijing：North China Electric Power University， 2016．
16	郭容赫．基于定流量的火电厂冷端优化分析及试验研究[D]．北京：华北电力大学，2018．
	GUO R H ． Cold end optimization of thermal power plant based on constant flow Analysis and experimental research[D]．Beijing：North China Electric Power University， 2018．
17	靳江波．大型燃气联合循环汽轮机凝汽器及冷端节能优化评价与分析[D]．北京：华北电力大学， 2017．
	JIN J B ． Large gas Combined--cycle Steam turbine Condenser and Cold side Energy conservation the evaluation and analysis[D]．Beijing：North China Electric Power University， 2017．
18	茅泽育，赵凯，赵璇，等．管道汇流口局部阻力试验研究[J]．水利学报，2007(7)：812-818． doi:10.3321/j.issn:0559-9350.2007.07.008
	MAO Z Y， ZHAO K， ZHAO X， et al ． Experimental study on local flow resistance at junctions of circular pipes[J]．Journal of Water Resources， 2007(7)： 812-818． doi:10.3321/j.issn:0559-9350.2007.07.008
19	胡寿根，秦宏波，白晓宁，等．固体物料管道水力输送的阻力特性[J]．机械工程学报，2002(10)：12-16． doi:10.3321/j.issn:0577-6686.2002.10.003
	HU S G， QIN H B， BAI X N， et al ． Resistance characteristics of particulate materials in pipeine hydro-transport[J]． Journal of Mechanical Engineering， 2002(10)： 12-16． doi:10.3321/j.issn:0577-6686.2002.10.003
20	费祥俊．固体管道水力输送摩阻损失的预测[J]．水利学报，1986(12)：20-29． doi:10.3321/j.issn:0559-9350.1986.12.003
	FEI X J ． Predietion of the frietional energy gradient for soldi liqud fliow in pipe[J]．Journal of Water Resources， 1986(12)： 20-29． doi:10.3321/j.issn:0559-9350.1986.12.003
21	庄乾伟．火电机组冷端分析与优化[D]．北京：华北电力大学，2018．
	ZHUANG Q W ． Cold-end analysis and optimization of thermal power units[D]．Beijing： North China Electric Power University， 2018．

[1]	Xin YUAN, Jun LIU, Heng CHEN, Peiyuan PAN, Gang XU, Xiuyan WANG. Effect of Carbon Capture Technology Application on Peak Shaving Capacity of Coal-Fired Units [J]. Power Generation Technology, 2024, 45(3): 373-381.
[2]	Hongwei ZHANG, Yongsheng ZHANG, Tao WANG, Jiawei WANG. Study on the Characteristics of Heavy Metal Lead in Desulfurization Sludge Solidified by Coal-Fired Fly Ash in Power Plant [J]. Power Generation Technology, 2024, 45(3): 527-534.
[3]	Yeqing ZHANG, Wenbin CHEN, Lüjun XU, Xingwen JIANG. Multi-Virtual Power Plant-Oriented Dynamic Aggregation Control Strategy Based on Hierarchical Partition and Multi-Layer Complementation [J]. Power Generation Technology, 2024, 45(1): 162-169.
[4]	Anan ZHANG, Qi ZHOU, Qian LI, Ning DING, Chao YANG, Yan MA. Research Status and Prospect of CO₂ Accounting Technology in Thermal Power Plants Under the Goal of Dual Carbon [J]. Power Generation Technology, 2024, 45(1): 51-61.
[5]	Daijun CHEN, Lili CHEN, Yangtao LI. Electrical Power Output Prediction of Combined Cycle Power Station [J]. Power Generation Technology, 2024, 45(1): 99-105.
[6]	Xingyuan XU, Haoyong CHEN, Yuxiang HUANG, Xiaobin WU, Yushen WANG, Junhao LIAN, Jianbin ZHANG. Challenges, Strategies and Key Technologies for Virtual Power Plants in Market Trading [J]. Power Generation Technology, 2023, 44(6): 745-757.
[7]	Songyuan YU, Junsong ZHANG, Zhiwei YUAN, Fang FANG. Resilience Enhancement Strategy of Combined Heat and Power-Virtual Power Plant Considering Thermal Inertia [J]. Power Generation Technology, 2023, 44(6): 758-768.
[8]	Zhenyu ZHAO, Xinxin LI. Low-Carbon Economic Dispatch Based on Ladder Carbon Trading Virtual Power Plant Considering Carbon Capture Power Plant and Power-to-Gas [J]. Power Generation Technology, 2023, 44(6): 769-780.
[9]	Zhonghao QIAN, Jun HU, Sichen SHEN, Ting QIN, Hanyi MA, Xiaodong WANG, Caoyi FENG, Zhinong WEI. Multi-Power Coordinated Optimization Operation Strategy Considering Conditional Value at Risk [J]. Power Generation Technology, 2023, 44(6): 781-789.
[10]	Xiaoqiang JIA, Yongbiao YANG, Jiao DU, Haiqing GAN, Nan YANG. Study on Uncertainty Operation Optimization of Virtual Power Plant Based on Intelligent Prediction Model Under Climate Change [J]. Power Generation Technology, 2023, 44(6): 790-799.
[11]	He HUANG, Yan WANG, Nian JIANG, Qiang WU, Yajing ZHANG, Xiuyuan YANG. Optimal Control of Residents’ Controllable Load Resources Considering Different Demands of Users [J]. Power Generation Technology, 2023, 44(6): 896-908.
[12]	Qiuye SUN, Jia YAO, Yifan WANG. From Virtual Power Plant to Real Electricity: Summary and Prospect of Virtual Power Plant Research [J]. Power Generation Technology, 2023, 44(5): 583-601.
[13]	Daogang PENG, Jijun SHUI, Danhao WANG, Huirong ZHAO. Review of Virtual Power Plant Under the Background of “Dual Carbon” [J]. Power Generation Technology, 2023, 44(5): 602-615.
[14]	Haoyong CHEN, Yuxiang HUANG, Yang ZHANG, Fei WANG, Liang ZHOU, Junbo TANG, Xiaobin WU. Architecture Design of Virtual Power Plant Based on “Three Flow Separation-Convergence” [J]. Power Generation Technology, 2023, 44(5): 616-624.
[15]	Ning ZHANG, Hao ZHU, Lingxiao YANG, Cungang HU. Optimal Scheduling Strategy of Multi-Energy Complementary Virtual Power Plant Considering Renewable Energy Consumption [J]. Power Generation Technology, 2023, 44(5): 625-633.