Research on Optimization Method of Coal Blending for Carbon Emission Reduction Based on Bi-level Programming

doi:10.12096/j.2096-4528.pgt.22012

Abstract

Abstract:

As the “dual carbon” goal has been upgraded to a national strategy, coal-fired power plants are the top priority for carbon reduction in the power generation industry, and coal-fired power plants are facing a huge challenge in limiting carbon emissions. Using the method of bi-level programming model, this paper established a low-carbon coal blending optimization model for thermal power units by considering the combination of carbon emission quotas for regulatory agencies and coal blending in power plants. The upper layer is the goal of the government management department, which seeks to minimize the cost of emission reduction of power plants under the given total carbon emissions. The lower layer is the goal of the power plant sector, pursuing the minimization of coal blending cost and carbon emission cost. The chaotic particle swarm optimization (CPSO) algorithm was used to solve the model. The calculation provides a certain reference for the allocation of carbon emission quotas for regulatory agencies and coal blending for power plant operators, and has good application value and guiding role.

Key words: carbon emission quota, bi-level programming model, coal blending optimization, chaotic particle swarm optimization (CPSO) algorithm

CLC Number:

TK 16

Siqin CHEN, Yinan ZHU, Xiaochen LI, Xuehai WANG. Research on Optimization Method of Coal Blending for Carbon Emission Reduction Based on Bi-level Programming[J]. Power Generation Technology, 2023, 44(2): 155-162.

Figures/Tables 7

References 19

1	刘志强，潘荔，赵毅，等．“十四五”时期我国火电行业节能潜力分析与建议[J]．中国能源，2021，43(4)：12-18．
	LIU Z Q， PAN L， ZHAO Y，et al ．Analysis and suggestions on energy saving potential of thermal power industry in China during the 14th Five-Year Plan period [J]．China Energy，2021，43(4)：12-18．
2	姜红丽，刘羽茜，冯一铭，等．碳达峰、碳中和背景下“十四五”时期发电技术趋势分析[J]．发电技术，2022，43(1)：10-18． doi:10.12096/j.2096-4528.pgt.21030
	JIANG H L， LIU Y X， FENG Y M，et al ．Analysis on the trend of power generation technology in the 14th Five-Year Plan period under the background of carbon peak and carbon neutralization[J]．Power Generation Technology，2022，43(1)：10-18． doi:10.12096/j.2096-4528.pgt.21030
3	王彤．我国煤电发展现状及“十四五”时期发展方向[J]．应用能源技术，2020(7)：20-23． doi:10.3969/j.issn.1009-3230.2020.07.005
	WANG T ．Development status and development direction of coal power in China during the 14th Five-Year Plan period[J]．Applied Energy Technology，2020(7)：20-23． doi:10.3969/j.issn.1009-3230.2020.07.005
4	张金良，贾凡．中国火电行业多模型碳达峰情景预测[J]．电力建设，2022，43(5)：18-28． doi:10.12204/j.issn.1000-7229.2022.05.003
	ZHANG J L， JIA F ．Multi-model carbon peak scenario prediction for thermal power industry in China[J]．Electric Power Construction，2022，43(5)：18-28． doi:10.12204/j.issn.1000-7229.2022.05.003
5	童光毅．基于双碳目标的智慧能源体系构建[J]．智慧电力，2021，49(5)：1-6． doi:10.3969/j.issn.1673-7598.2021.05.002
	TONG G Y ．Construction of smart energy system based on dual carbon goal[J]．Smart Power，2021，49(5)：1-6． doi:10.3969/j.issn.1673-7598.2021.05.002
6	WU M， NAKANO M， SHE J H ．A model-based expert control strategy using neural networks for the coal blending process in an iron and steel plant[J]．Expert Systems with Applications，1999，16(3)：271-281． doi:10.1016/s0957-4174(98)00076-1
7	黄海东，刘福国，国钦光，等．配煤掺烧最小煤质偏差模型及煤场存放优化[J]．热能动力工程，2020，35(5)：97-104．
	HUANG H D， LIU F G， GUO Q G，et al ．Minimum deviation model of coal quality and storage optimization of coal yard for blending and firing[J]．Thermal Energy and Power Engineering，2020，35(5)：97-104．
8	夏季，陆攀，华志刚，等．电站锅炉全局优化智能配煤模型的建立及系统开发[J]．动力工程学报，2010，30(7)：512-517．
	XIA J， LU P， HUA Z G，et al ．Establishment and system development of intelligent coal blending model for global optimization of utility boilers[J]．Chinese Journal of Power Engineering，2010，30(7)：512-517．
9	SHIH J S， FREY H C ．Coal blending optimization under uncertainty[J]．European Journal of Operational Research，1995，83(3)：452-465． doi:10.1016/0377-2217(94)00243-6
10	王英敏，张志刚，张文君，等．火电机组混煤掺烧与优化系统研究与应用[J]．科学技术与工程，2020，20(14)：5634-5638． doi:10.3969/j.issn.1671-1815.2020.14.026
	WANG Y M， ZHANG Z G， ZHANG W J，et al ．Research and application of coal blending and optimization system for thermal power units[J]．Science Technology and Engineering，2020，20(14)：5634-5638． doi:10.3969/j.issn.1671-1815.2020.14.026
11	张宇，周连升，王桂林，等．减少污染物排放成本的配煤优化模型[J]．热力发电，2015，44(7)：88-92． doi:10.3969/j.issn.1002-3364.2015.07.088
	ZHANG Y， ZHOU L S， WANG G L，et al ．Optimization model of coal blending to reduce pollutant emission cost[J]．Thermal Power，2015，44(7)：88-92． doi:10.3969/j.issn.1002-3364.2015.07.088
12	LÜ C W， XU J P， XIE H P，et al ．Equilibrium strategy based coal blending method for combined carbon and PM₁₀ emissions reductions[J]．Applied Energy，2016，183：1035-1052．
13	段翩，朱建全，刘明波．基于双层模糊机会约束规划的虚拟电厂优化调度[J]．电工技术学报，2016，31(9)：58-67． doi:10.3969/j.issn.1000-6753.2016.09.008
	DUAN P， ZHU J Q， LIU M B ．Optimal scheduling of virtual power plants based on double-layer fuzzy opportunistic constrained programming[J]．Journal of Electrotechnical Technology，2016，31(9)：58-67． doi:10.3969/j.issn.1000-6753.2016.09.008
14	叶泽，何姣，周鑫，等．发电行业碳排放权初始配额分配的双层规划模型[J]．系统工程，2018，36(11)：140-146．
	YE Z， HE J， ZHOU X， et al. A two-layer planning model for the initial allocation of carbon emission rights in the power generation industry[J]. Systems Engineering， 2018， 36(11)：140-146．
15	刘福国，刘科，王守恩．基于机会约束的电厂混煤煤质和成本的Pareto前沿[J]．发电技术，2022，43(1)：160-167． doi:10.12096/j.2096-4528.pgt.21042
	LIU F G， LIU K， WANG S E ．The Pareto frontier of coal quality and cost of power plant blending based on opportunity constraints[J]．Power Generation Technology，2022，43(1)：160-167． doi:10.12096/j.2096-4528.pgt.21042
16	高鹰，谢胜利．混沌粒子群优化算法[J]．计算机科学，2004，31(8)：13-15． doi:10.3969/j.issn.1002-137X.2004.08.004
	GAO Y， XIE S L ．Chaos particle swarm optimization algorithm[J]．Computer Science，2004，31(8)：13-15． doi:10.3969/j.issn.1002-137X.2004.08.004
17	付轩熠，茅大钧，印琪民．基于多种算法的火电厂配煤优化方法研究[J]．煤炭工程，2018，50(9)：150-154． doi:10.11799/ce201809038
	FU X Y， MAO D J， YIN Q M ．Research on coal blending optimization method for thermal power plants based on multiple algorithms[J]．Coal Engineering，2018，50(9)：150-154． doi:10.11799/ce201809038
18	刘艳军．电厂动力配煤煤质预测模型与优化模型研究[D]．长沙：中南大学，2011．
	LIU Y J ．Research on coal quality prediction model and optimization model of power coal blending in power plants[D]．Changsha：Central South University，2011．
19	国家发展和改革委员会应对气候变化司．2015年中国区域电网基准线排放因子[R]．北京：国家发展和改革委员会，2015．
	Department of Climate Change，National Development and Reform Commission ．2015 China regional power grid baseline emission factor[R]．Beijing：National Development and Reform Commission，2015．

编号	M_ar/%	A_ar/%	V_ar/%	S_ar/%	Q/(MJ⋅kg^-1)	P/(元/t)
M1	1.14	30.58	11.05	0.4	20.69	638.29
M2	2.09	36.28	7.61	0.72	18.38	487.47
M3	1.82	33.24	22.83	3.66	16.78	405.54
M4	2.39	29.52	6.25	0.42	21.04	494.00
M5	0.76	24.71	12.72	0.35	23.09	624.00
M6	0.51	32.27	14.96	2.99	20.28	515.14
M7	1.72	38.88	7.83	0.57	18.50	506.00
M8	0.94	28.98	12.23	1.24	21.29	734.08
M9	2.07	47.23	9.98	1.14	15.16	409.86
M10	3.23	33.49	9.04	1.91	18.45	519.53

编号	M_ar/%	A_ar/%	V_ar/%	S_ar/%	Q/(MJ⋅kg^-1)	P/(元/t)
M1	1.14	30.58	11.05	0.4	20.69	638.29
M2	2.09	36.28	7.61	0.72	18.38	487.47
M3	1.82	33.24	22.83	3.66	16.78	405.54
M4	2.39	29.52	6.25	0.42	21.04	494.00
M5	0.76	24.71	12.72	0.35	23.09	624.00
M6	0.51	32.27	14.96	2.99	20.28	515.14
M7	1.72	38.88	7.83	0.57	18.50	506.00
M8	0.94	28.98	12.23	1.24	21.29	734.08
M9	2.07	47.23	9.98	1.14	15.16	409.86
M10	3.23	33.49	9.04	1.91	18.45	519.53

[1]	Jingji ZHU, Yishu XU, Jingying XU, Huakun WANG, Xiaowei LIU, Dunxi YU, Jingjing MA, Minghou XU. Effect of Co-firing Ammonia on Coal Volatile Flame Characteristics and Particulate Matter Formation Behaviours [J]. Power Generation Technology, 2022, 43(6): 908-917.
[2]	Hongjian WANG, Haiyang WANG, Hao KONG, Tuo ZHOU, Man ZHANG, Hairui YANG. Retrofitting Strategy and Operating Technology of Pure Burning Zhundong Coal in a 135 MW Circulating Fluidized Bed Boiler [J]. Power Generation Technology, 2022, 43(6): 918-926.
[3]	Jiangang HAO, Wenming GONG, Yang DING, Danwei ZHENG, Yong LIU. Analysis on Combustion Instability Characteristics of Model Swirl Combustor With Gas Fuel [J]. Power Generation Technology, 2022, 43(6): 927-934.
[4]	Zhenshan LI, Hu CHEN, Weicheng LI, Lei LIU, Ningsheng CAI. Research Status and Prospect of Chemical Looping Combustion Pilot Systems [J]. Power Generation Technology, 2022, 43(4): 544-561.
[5]	Zhenwu MIAO, Laihong SHEN, Haibo ZHAO. Study on Cycling Reaction Performance of Composite Hematite and Copper Ore Oxygen Carrier in Chemical Looping Combustion [J]. Power Generation Technology, 2022, 43(4): 574-583.
[6]	Hu GAO, Fan LIU, Hai LI. Opportunities, Challenges and Application Prospects of Ammonia Fuel Under the Target of Carbon Neutrality [J]. Power Generation Technology, 2022, 43(3): 462-467.
[7]	Yuan LI, Zhicheng GUO, Xiaochao MENG, Kefeng CHEN, Liming REN, Rui MAO, Kefa CEN. Design of an Online Monitoring System for Combustion Field Parameter in a Furnace Based on Tunable Diode Laser Absorption Spectroscopy Technology [J]. Power Generation Technology, 2022, 43(2): 353-361.
[8]	Fuguo LIU, Ke LIU, Shouen WANG. Pareto Fronts of Mixed Coal Quality and Cost in Power Plant Based on Chance Constraints [J]. Power Generation Technology, 2022, 43(1): 160-167.