Analysis of the Influence of Furnace Side Heat Storage Coefficient on Primary Frequency Modulation Capacity Under Deep Modulation Condition of Thermal Power Unit

doi:10.12096/j.2096-4528.pgt.24023

Abstract

Abstract:

In order to study the influence of the heat storage coefficient of the furnace side evaporation section and superheating section on the primary frequency modulation capacity of the thermal power unit under the deep modulation working conditions, a refined simulation model suitable for the thermal power under the deep modulation working condition was built, based on the typical model in the transient stability program PSD-BPA, and the control logic of the thermal power unit under the actual furnace-machine coordination mode. The correctness of the model was verified by the actual primary frequency modulation data of a DC furnace with a rated power $P e$ of 1 000 MW at 35% $P e$ working conditions. Through the simulation model, the influence of the heat storage coefficient of the evaporation section and the superheat section of the furnace side on the primary frequency modulation capacity of the unit under the deep modulation condition was explored. It is found that the smaller the heat storage coefficient of the evaporation section on the furnace side, the stronger the primary frequency modulation response ability of the unit. The larger the heat storage coefficient of the superheated section on the furnace side, the more friendly it is to the primary frequency modulation of the unit. The frequency regulation capability of the unit can be improved by increasing or decreasing the heat storage coefficient in the evaporation and overheat sections. In addition, the refined model of primary frequency regulation established can provide analysis of the margin of primary frequency regulation for thermal power units for power production and regulatory authorities, which is beneficial for the safety of new power systems.

Key words: thermal power unit, deep modulation, thermal storage coefficient, simulation model, frequency modulation margin

CLC Number:

TK 01

Zhan LI, Zhenyong YANG, Lei LIU, Zhensan CHEN, Weiming JI, Feng HONG. Analysis of the Influence of Furnace Side Heat Storage Coefficient on Primary Frequency Modulation Capacity Under Deep Modulation Condition of Thermal Power Unit[J]. Power Generation Technology, 2024, 45(2): 226-232.

Figures/Tables 13

Fig. 1 Refined model of primary frequency regulation under deep regulation condition

Fig. 2 GX combustion model

Fig. 3 Comparison of power parameters

Fig. 4 Comparison of pressure parameters

Tab. 1 R2 value under working condition of 35%Pe

特征参数

扰动转差/（r/min）

R 2

机组功率

主汽压力

0.898

0.973

Tab. 1 R2 value under working condition of 35%Pe

特征参数

扰动转差/（r/min）

R 2

机组功率

主汽压力

0.898

0.973

Fig. 5 Power variation diagram of the unit in the direction of 6 r/min load reduction under different evaporation section heat storage coefficient

Fig. 6 Power variation diagram of the unit in the direction of 6 r/min load increase under different evaporation section heat storage coefficient

Fig. 7 Pressure variation diagram of the unit in the direction of 6 r/min load reduction under different evaporation section heat storage coefficient

Fig. 8 Pressure variation diagram of the unit in the direction of 6 r/min load increase under different evaporation section heat storage coefficient

Fig. 9 Power variation diagram of the unit in the direction of 6 r/min load reduction under different heat storage coefficient of superheat section

Fig. 10 Pressure variation diagram of the unit in the direction of 6 r/min load reduction under different heat storage coefficient of superheat section

Fig. 11 Power variation diagram of the unit in the direction of 6 r/min load increase under different heat storage coefficient of superheat section

Fig. 12 Pressure variation diagram of the unit in the direction of 6 r/min load increase under different heat storage coefficient of superheat section

References 18

1	袁岑颉，戴敏敏，周旭，等．电力市场环境下火电机组调频性能提升研究[J]．浙江电力， 2022， 41(6)： 84-91．
	YUAN C J， DAI M M， ZHOU X， et al ． Research on frequency modulation performance improvement of thermal power units in the context of power market[J]．Zhejiang Electric Power， 2022， 41(6)： 84-91．
2	田云峰，郭嘉阳，刘永奇，等．用于电网稳定性计算的再热凝汽式汽轮机数学模型[J]．电网技术， 2007， 31(5)： 39-44． doi:10.3321/j.issn:1000-3673.2007.05.009
	TIAN Y F， GUO J Y， LIU Y Q， et al ． A mathematical model of rehear turbine for power grid stability calculation[J]． Power System Technology， 2007， 31(5)： 39-44． doi:10.3321/j.issn:1000-3673.2007.05.009
3	王永庆，赵嘉，曹越，等．超临界机组及其一次调频控制系统的辨识与仿真[J]．热能动力工程， 2018， 33(2)： 111-116． doi:10.16146/j.cnki.rndlgc.2018.02.016
	WANG Y Q， ZHAO J， CAO Y， et al ． Identification and simulation of a supercritical unit and its primary frequency modulation and control system[J]． Journal of Engineering for Thermal Energy and Power， 2018， 33(2)： 111-116． doi:10.16146/j.cnki.rndlgc.2018.02.016
4	盛锴，邹鑫，邱靖，等．火电机组一次调频功率响应特性精细化建模[J]．中国电力， 2021， 54(6)： 111-118． doi:10.11930/j.issn.1004-9649.202101111
	SHENG K， ZOU X， QIU J， et al ． Refined modeling for power response characteristic of thermal power unit under primary frequency control[J]． Electric Power， 2021， 54(6)： 111-118． doi:10.11930/j.issn.1004-9649.202101111
5	于国强，崔晓波，史毅越，等．基于改进群优化算法的深度调峰机组一次调频建模[J]．中国电力， 2020， 53(6)： 147-152． doi:10.11930/j.issn.1004-9649.201910003
	YU G Q， CUI X B， SHI Y Y， et al ． Primary frequency regulation modeling of deep peak regulation unit based on improved group optimization algorithm[J]．Electric Power， 2020， 53(6)： 147-152． doi:10.11930/j.issn.1004-9649.201910003
6	郭越，徐飞，郝玲，等．一次调频中的锅炉建模与参数在线确定[J]．中国电机工程学报， 2023， 43(17)： 6551-6562．
	GUO Y， XU F， HAO L， et al ． Boiler modeling and online parameters identification for primary frequency regulation[J]． Proceedings of the CSEE， 2023， 43(17)： 6551-6562．
7	王学华，姚力，陈学州，等．超超临界百万机组20%负荷深度调峰运行试验研究[J]．能源与节能， 2024(1)： 1-6． doi:10.3969/j.issn.2095-0802.2024.01.001
	WANG X H， YAO L， CHEN X Z， et al ． 20% load deep peak shaving operation test of ultra-supercritical million units[J]． Energy and Energy Conservation， 2024(1)： 1-6． doi:10.3969/j.issn.2095-0802.2024.01.001
8	吕建，白东海，温武．新型电力系统下基于深度调峰的火电机组控制技术研究[J]．山西电力， 2023(6)： 49-53． doi:10.3969/j.issn.1671-0320.2023.06.011
	LV J， BAI D H， WEN W ． Research on control technology of thermal power units based on deep peak regulation in new power systems[J]． Shanxi Electric Power， 2023(6)： 49-53． doi:10.3969/j.issn.1671-0320.2023.06.011
9	张洪福，高明明，于浩洋，等． 300 MW深度调峰循环流化床机组负荷响应特性研究[J]．动力工程学报， 2023， 43(9)： 1116-1122．
	ZHANG H F， GAO M M， YU H Y， et al ． Study on load response characteristics of a 300 MW circulating fluidized bed unit with deep peak regulation[J]． Journal of Chinese Society of Power Engineering， 2023， 43(9)： 1116-1122．
10	于国强，刘克天，胡尊民，等．大规模新能源并网下火电机组深度调峰优化调度[J]．电力工程技术， 2023， 42(1)： 243-250． doi:10.12158/j.2096-3203.2023.01.029
	YU G Q， LIU K T， HU Z M， et al ． Optimal scheduling of deep peak regulation for thermal power units in power grid with large-scale new energy[J]．Electric Power Engineering Technology， 2023， 42(1)： 243-250． doi:10.12158/j.2096-3203.2023.01.029
11	袁春峰，刘锴慧，张帆，等．火电机组一次调频技术研究进展综述[J]．南方能源建设，2022，9(3)：1-8． doi:10.16516/j.gedi.issn2095-8676.2022.03.001
	YUAN C F， LIU K H， ZHANG F， et al ． Review on the research progress of primary frequency modulation technology for thermal power units[J]． Southern Energy Construction， 2022， 9(3)： 1-8． doi:10.16516/j.gedi.issn2095-8676.2022.03.001
12	赵国钦，蓝茂蔚，李杨，等．基于最小二乘支持向量机的火电厂烟气含氧量预测模型优化研究[J]．发电技术， 2023， 44(4)： 534-542． doi:10.12096/j.2096-4528.pgt.21088
	ZHAO G Q， LAN M W， LI Y， et al ． Study on optimization of prediction model of flue gas oxygen content in thermal power plant based on least squares support vector machine[J]． Power Generation Technology， 2023， 44(4)： 534-542． doi:10.12096/j.2096-4528.pgt.21088
13	顾正皓，包劲松，张宝，等．考虑主蒸汽压力的燃煤机组调速模型的分析与改进[J]．中国电力， 2016， 49(9)： 93-98． doi:10.11930/j.issn.1004-9649.2016.09.093.06
	GU Z H， BAO J S， ZHANG B， et al ． Analysis and improvement of speed governor model considering the main steam pressure influences[J]． Electric Power， 2016， 49(9)： 93-98． doi:10.11930/j.issn.1004-9649.2016.09.093.06
14	隋云任，梁双印，黄登超，等．飞轮储能辅助燃煤机组调频动态过程仿真研究[J]．中国电机工程学报， 2020， 40(8)： 2597-2606．
	SUI Y R， LIANG S Y， HUANG D C， et al ． Simulation study on frequency modulation process of coal burning plants with auxiliary of flywheel energy storage[J]． Proceedings of the CSEE， 2020， 40(8)： 2597-2606．
15	谢昌亚，朱龙飞，胡娱欧，等． 660 MW超临界火电机组汽轮机及其调速系统精细化模型研究和应用[J]．热能动力工程， 2023， 38(6)： 58-67．
	XIE C Y， ZHU L F， HU Y O， et al ． Research and application of refined model for 660 MW supercritical thermal power unit steam turbine and its governing system[J]． Journal of Engineering for Thermal Energy and Power， 2023， 38(6)： 58-67．
16	邓拓宇，田亮，刘吉臻．超超临界直流锅炉蓄热能力的定量分析[J]．动力工程学报， 2012， 32(1)： 10-14． doi:10.3969/j.issn.1674-7607.2012.01.002
	DENG T Y， TIAN L， LIU J Z ． Quantitative analysis on heat storage capacity of ultra-supercritical once-through boilers[J]． Journal of Chinese Society of Power Engineering， 2012， 32(1)： 10-14． doi:10.3969/j.issn.1674-7607.2012.01.002
17	杨玉龙，王淞，陈韬，等．基于蓄热水箱温度可行域模糊确定的电锅炉优化调度方法[J]．电力建设， 2023， 44(7)： 111-120．
	YANG Y L， WANG S， CHEN T， et al ． Optimal scheduling method of electric boiler based on fuzzy determination of temperature feasible region of hot water storage tank[J]． Electric Power Construction， 2023， 44(7)： 111-120．
18	周鑫，程松，任景，等．含储热型热电联产机组的电力系统源荷联合优化调峰方法[J]．电力科学与技术学报， 2023， 38(5)： 12-21．
	ZHOU X， CHENG S， REN J， et al ． A source-load joint optimization peak regulation method of power system with heat storage combined heat and power units[J]． Journal of Electric Power Science and Technology， 2023， 38(5)： 12-21．

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