Optimization of thermoelectric load distribution in coupled multi-unit heating modes based on particle swarm algorithm

文珏; 施宏波; 薛康康; 薛小军; 袁威; 曹超; 张乐天

doi:10.19666/j.rlfd.202503053

English Version Reader LoginJournal Login

您当前的位置：

首页 >

文章列表页 >

Optimization of thermoelectric load distribution in coupled multi-unit heating modes based on particle swarm algorithm

更新时间：2026-01-21

- Optimization of thermoelectric load distribution in coupled multi-unit heating modes based on particle swarm algorithm
- Thermal Power Generation Vol. 54, Issue 12, Pages: 94-101(2025)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202503053
  CLC：
- Published：2025
- 稿件说明：
移动端阅览
文珏, 施宏波, 薛康康, et al. Optimization of thermoelectric load distribution in coupled multi-unit heating modes based on particle swarm algorithm[J]. Thermal Power Generation, 2025, 54(12): 94-101.
DOI：

文珏, 施宏波, 薛康康, et al. Optimization of thermoelectric load distribution in coupled multi-unit heating modes based on particle swarm algorithm[J]. Thermal Power Generation, 2025, 54(12): 94-101. DOI： 10.19666/j.rlfd.202503053.

摘要

多台机组联合供热时，机组间的热电负荷分配对全局能耗有重要影响。针对某电厂1号、3号机组为低压缸零出力、抽汽的双模式耦合供热，2号、4号机组为高背压、热泵、抽汽的三模式耦合供热的热电厂，使用EBSILON软件建立了变工况模型，通过调整主蒸汽流量、低压缸零出力汽量、热泵供热功率、高背压供热流量等参数，分析其热电特性和能耗特性，采用最小二乘法拟合电负荷和热负荷的运行边界以及煤耗量与热电负荷的关系，在全厂供热负荷和供电负荷固定的边界条件下通过粒子群算法优化热电负荷分配。结果表明：安排大容量高背压热泵机组提供热负荷，小容量高背压热泵机组提供电负荷时总煤耗量更低；优化后的全厂总煤耗量比优化前降低0.6～10.0 t/h，优化程度为0.3%～3.9%。

Abstract

关键词

Keywords

references

王晋权,蔡新春,张国胜.直接空冷热电联产机组供热优化分析[J].中国电力, 2015, 48(3):17-20.WANG Jinquan, CAI Xinchun, ZHANG Guosheng, et al.Optimal analysis on heat supply of combined heat and power direct air-cooling units[J]. Electric Power, 2015,48(3):17-20.

侯建军,付喜亮,李染生,等.基于??分析的能量梯级利用供热变工况运行优化研究[J].中国电力, 2023,56(8):230-240.HOU Jianjun, FU Xiliang, LI Ransheng, et al. Research on operation optimization of energy cascade utilization heating based on exergy analysis[J]. Electric Power, 2023,56(8):230-240.

高佳圣,徐浩东,王万权,等.集成太阳能辅助供热的600 MW高背压热电联产机组的运行及优化[J].热能动力工程, 2023, 38(9):158-165.GAO Jiasheng, XU Haodong, WANG Wanquan, et al.Operation and optimization of 600 MW high back pressure cogeneration unit with integrated solar assisted heating[J]. Journal of Engineering for Thermal Energy and Power, 2023, 38(9):158-165.

黄宇箴,陈彦奇,吴志聪,等.碳中和背景下热电联产机组抽汽分配节能优化[J].发电技术, 2023, 44(1):85-93.HUANG Yuzhen, CHEN Yanqi, WU Zhicong, et al.Energy saving optimization of extraction steam distribution for cogeneration units under carbon neutral background[J]. Power Generation Technology, 2023,44(1):85-93.

郭喜燕,刘嘉康,杨志平,等.考虑碳排放的热电解耦机组多目标负荷优化[J].热能动力工程, 2023, 38(6):68-79.GUO Xiyan, LlU Jiakang, YANG Zhiping, et al. Multiobjective load optimization of thermoelectric decoupling units considering carbon emissions[J]. Journal of Engineering for Thermal Energy and Power, 2023, 38(6):68-79.

焦晓峰,范志强,贾斌,等. 300 MW机组厂级供热优化调度方式及性能分析[J].汽轮机技术, 2023, 65(2):149-153.JIAO Xiaofeng, FAN Zhiqiang, JIA Bin, et al. Heating supply optimization and performance analysis with plantlevel for 300 MW cogeneration unit[J]. Turbine Technology, 2023, 65(2):149-153.

汪可,田亮.供热机组低压缸零出力工况下热经济性分析[J].华北电力大学学报(自然科学版), 2023, 50(4):112-118.WANG Ke, TIAN Liang, North china electric power university school of control and computer engineering.thermal economy analysis of heating unit under zerooutput condition of low pressure cylinder[J]. Journal of North China Electric Power University(Natural Science Edition), 2023, 50(4):112-118.

张红昌,薛小军,徐钢,等.热电联产机组热电解耦改造方案的调峰特性及能耗分析[J].动力工程学报,2023, 43(10):1382-1390.ZHANG Hongchang, XUE Xiaojun, XU Gang, et al. Peak shaving characteristics and energy consumption analysis of the thermoelectric-decoupling retrofit scheme for cogeneration units[J]. Journal of Chinese Society of Power Engineering, 2023, 43(10):1382-1390.

程东涛,王生鹏,谢天,等.抽汽供热机组增设背压机节能效果评价[J].热能动力工程, 2021, 36(7):7-11.CHENG Dongtao, WANG Shengpeng, XlE Tian, et al.Energy-saving effect evaluation of adding back pressure turbine to steam extraction heat supply unit[J]. Journal of Engineering for Thermal Energy and Power, 2021, 36(7):7-11.

张艺晨,杨勇平,戈志华,等.基于能量梯级利用的高效灵活供热系统性能研究[J].动力工程学报, 2023,43(8):1085-1094.ZHANG Yichen, YANG Yongping, GE Zhihua, et al.Performance study of an efficient and flexible heating system based on cascade use of energy[J]. Journal of Chinese Society of Power Engineering, 2023, 43(8):1085-1094.

韩中合,肖炜刚,安国银.大型汽轮机供热改造方案研究[J].汽轮机技术, 2016, 58(3):198-200.HAN Zhonghe, XIAO Weigang, AN Guoyin, et al.Research of heating retrofitting schemes for large steam turbine[J]. Turbine Technology, 2016, 58(3):198-200.

张抖,张光明,牛玉广,等.吸收式热泵对热电联产机组调峰能力影响分析[J].热力发电, 2021, 50(10):95-100.ZHANG Dou, ZHANG Guangming, NIU Yuguang, et al.Impact analysis of absorption heat pump on peak regulation capacity of combined heat and power unit[J].Thermal Power Generation, 2021, 50(10):95-100.

高宽,鲍文龙,丁阳俊.大型汽轮机组深度调峰时抽汽供热的经济性分析[J].热能动力工程, 2020, 35(9):16-21.GAO Kuan, BAO Wenlong, DING Yangjun, et al.Economical analysis for a large sized unit of steam extractionunder deep regulating load[J]. Journal of Engineering for Thermal Energy and Power, 2020, 35(9):16-21.

范志强,焦晓峰,魏超,等. 300 MW供热机组低压缸零出力热力性能、调峰性能和经济性能分析[J].中国测试, 2024, 50(4):166-172.FAN Zhiqiang, JIAO Xiaofeng, WEI Chao, et al.Thermodynamic and economic performance and peak load regulation capacity analysis of 300 MW cogeneration unit with low pressure cylinder near zero output mode[J].China Measurement&Test, 2024, 50(4):166-172.

张德利,庞春凤.基于鸟群优化算法的机组多供热方式优化分配研究[J].汽轮机技术, 2024, 66(4):253-257.ZHANG Deli, PANG Chunfeng. Research on optimal distribution of multiple heating modes of unit based on bird optimization algorithm[J]. Turbine Technology, 2024,66(4):253-257.

周霞,李建锋,周宏,等.耦合蒸汽压缩与储热的燃煤热电联产机组调峰性能研究[J].中国电机工程学报,2025, 45(1):194-206.ZHOU Xia, LI Jianfeng, ZHOU Hong, et al. Research on peak shaving performance of coal-fired cogeneration unit coupled with vapor compression and heat storage[J].Proceedings of the CSEE, 2025, 45(1):194-206.

高新勇,郑立军,喻珮,等.热电联产电站复杂供热系统的热电负荷智能分配研究[J].热能动力工程, 2024,39(8):86-93.GAO Xinyong, ZHENG Lijun, YU Pei, et al. Research on intelligent scheduling of heat and power loads for complex heating system of a cogeneration power station[J]. Journal of Engineering for Thermal Energy and Power, 2024,39(8):86-93.

吴涛,赖菲,刘震,等.热电联产机组在深度调峰模式下的负荷智能分配[J].热力发电, 2021, 50(9):119-127.WU Tao, LAI Fei, LIU Zhen, et al. Intelligent load distribution of cogeneration units in deep peak regulation mode[J]. Thermal Power Generation, 2021, 50(9):119-127.

石慧,王洋,马汀山,等.多机组、多模式的热电联产厂级供热优化[J].热力发电, 2022, 51(1):123-129.SHI Hui, WANG Yang, MA Tingshan, et al. Heat load optimal distribution for multi-unit and multi-mode thermal power plant[J]. Thermal Power Generation, 2022,51(1):123-129.

丁衡,胡慧,曹越,等.基于改进灰狼算法的热电联供系统负荷优化分配策略研究[J].动力工程学报, 2023,43(11):1515-1522.DING Heng, HU Hui, CAO Yue, et al. Research on load optimal distribution strategy of combined heat and power system based on improved gray wolf algorithm[J]. Journal of Chinese Society of Power Engineering, 2023, 43(11):1515-1522.

王玮,王子欣,孔德安,等.灵活性驱动下的热电联产机组多目标协同控制策略[J].动力工程学报, 2024,44(12):1907-1915.WANG Wei, WANG Zixin, KONG Dean, et al.Flexibility-driven multi-objective cooperative control strategy for combined heat and power units[J]. Journal of Chinese Society of Power Engineering, 2024, 44(12):1907-1915.

祝令凯,郑威,钟子威,等.基于粒子群算法的热电厂供热负荷分配优化[J].山东电力技术, 2023, 50(7):60-67.ZHU Lingkai, ZHENG Wei, ZHONG Ziwei, et al.Optimization of heating load distribution in combined heat and power plants based on particle swarm optimization algorithm[J]. Shandong Electric Power,2023, 50(7):60-67.

齐结红,潘宇,钱虹,等.自动发电控制优先的厂级多机组供热经济优化调度研究[J].热力发电, 2022,51(9):63-71.QI Jiehong, PAN Yu, QIAN Hong, et al. AGC priority plant level multi-unit heating economic optimal dispatching[J]. Thermal Power Generation, 2022, 51(9):63-71.

王珊,刘明,严俊杰.采用粒子群算法的热电厂热电负荷分配优化[J].西安交通大学学报, 2019, 53(9):159-166.WANG Shan, LIU Ming, YAN Junjie, et al. Optimizing heat-power load distribution of thermal power plants based on particle swarm algorithm[J]. Journal of Xi’an Jiaotong University, 2019, 53(9):159-166.

Views

156

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Online optimization for collaborative treatment of CO and multi-pollutant emission reduction based on particle swarm optimization

Model for predicting SCR flue gas denitration efficiency based on particle swarm optimization and twin support vector machine

Design of flue gas denitration control system based on feedforward constrained dynamic matrix control

GA-SVM-based soft-sensor model for oxygen content in flue gas of utility boilers

Application of fractional-order model in power plant control systems

Related Author

曲培培

金杭良

徐碧涛

吴俊

武燕燕

陈玲红

康子为

DING Chengfu

Related Institution

School of Information Science and Technology, Zhejiang Sci-Tech University

Focused Photonics (Hangzhou) Inc.

Department of Automation, North China Electric Power University

Fujian Electric Power Survey & Design Institute

School of Energy Power and Mechanical Engineering, North China Electric Power University

AI问答

⁰