基于AM-RFR-PSO混合算法的燃煤机组变负荷速率优化

赵子淳; 李晓博; 陈衡; 任硕; 姚磊; 李昱; 张俊姣

doi:10.19805/j.cnki.jcspe.2026.250141

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基于AM-RFR-PSO混合算法的燃煤机组变负荷速率优化

煤电机组清洁低碳高效运行与智能调峰专题 | 更新时间：2026-07-16

- 基于AM-RFR-PSO混合算法的燃煤机组变负荷速率优化
- Optimization of Variable Load Rate for Coal-fired Units Based on AM-RFR-PSO Hybrid Algorithm
- 动力工程学报 2026年46卷第7期页码：152-160
- 作者机构：
  
  1. 华北电力大学能源动力与机械工程学院,北京,102206
  2. 青海电力交易中心有限公司,青海,西宁,810008
  3. 华能岳阳发电有限责任公司,湖南,岳阳,414002
- 作者简介：
  
  赵子淳(2001—),男,辽宁铁岭人,硕士研究生,研究方向为燃煤机组运行优化,E-mail:zzc13591612997@126.com。
- 基金信息：
  
  国家自然科学基金资助项目(52276006)
- DOI：10.19805/j.cnki.jcspe.2026.250141
  中图分类号： TK37
- 纸质出版：2026
- 稿件说明：
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赵子淳, 李晓博, 陈衡, 任硕, 姚磊, 李昱, 张俊姣. 基于AM-RFR-PSO混合算法的燃煤机组变负荷速率优化[J]. 动力工程学报, 2026, 46(7): 152-160.
赵子淳, 李晓博, 陈衡, 任硕, 姚磊, 李昱, 张俊姣. 基于AM-RFR-PSO混合算法的燃煤机组变负荷速率优化[J]. 动力工程学报, 2026, 46(7): 152-160. DOI： 10.19805/j.cnki.jcspe.2026.250141.

DOI： 10.19805/j.cnki.jcspe.2026.250141

摘要

在深度调峰背景下

火电机组出现升降负荷速率慢、无法及时响应调峰要求的问题

为提高机组变负荷速率

提出了一种融合注意力机制的随机森林-粒子群混合算法(AM-RFR-PSO)的燃煤机组运行优化方法。首先使用相关性分析选出与机组输出功率相关的运行参数作为模型特征变量

引入注意力机制对随机森林算法进行改进

使用改进后的算法对火电机组输出功率进行预测建模

并与其他算法进行对比

最后使用粒子群算法对主要特征变量进行优化

提高火电机组的升降负荷速率。结果表明:与其他算法相比

AM-RFR预测模型的均方根误差、平均绝对误差最低

回归系数最高

证明该模型的预测精度较高

经过PSO优化后的运行参数可以使机组的升降负荷速率提升接近5%

可以有效提升机组的响应速度。

Abstract

Under the deep peak regulation background

thermal power units encounter such problems as slow load variation rate and inability to respond promptly to peak regulation requirements. To improve the unit's variable load rate

an operational optimization method for coal-fired power units based on a hybrid random forest-particle swarm optimization algorithm incorporating an attention mechanism (AM-RFR-PSO) was proposed. Firstly

correlation analysis was used to select the operation parameters related to unit output power as the model feature variables. Then attention mechanism was introduced to improve the random forest algorithm

and the improved algorithm was used to model the output power prediction of thermal power unit and compared with other algorithms. Finally

particle swarm algorithm was used to optimize the main feature variables to improve the load variation rate of the thermal power unit. The results show that compared with other algorithms

the AM-RFR prediction model has the smallest root mean square error

average absolute error

and the highest regression coefficient

which proves that the prediction model has high prediction accuracy

and the PSO-optimized operating parameters can improve the unit's variable load rate by close to 5%

which can effectively improve the unit's response speed.

关键词

Keywords

references

刘吉臻, 胡勇, 曾德良, 等. 智能发电厂的架构及特征[J]. 中国电机工程学报, 2017, 37(22): 6463-6470.LIU Jizhen, HU Yong, ZENG Deliang, et al. Architecture and feature of smart power generation[J]. Proceedings of the CSEE, 2017, 37(22): 6463-6470.

高飞, 张强, 甄志广, 等. 风煤比、水煤比预测电煤比及在燃煤发电机组运行优化中的性能[J]. 洁净煤技术, 2024, 30(9): 123-130.GAO Fei, ZHANG Qiang, ZHEN Zhiguang, et al. Predicting the electricity coal ratio using the wind coal ratio and water coal ratio and its application in coal-fired generating unit operation optimization[J]. Clean Coal Technology, 2024, 30(9): 123-130.

许德昌. 基于大数据分析的电站锅炉性能预测及优化[D]. 北京: 华北电力大学, 2021.

金秀章, 张瑾, 陈佳政. 基于麻雀搜索算法优化TPA-LSTM的火电厂NOx排放预测[J/OL]. 控制工程, 2026: 1-9. (2024-03-18)[2026-04-19]. https://doi.org/10.14107/j.cnki.kzgc.20230640.JIN[KG(-1x]Xiuzhang, ZHANG Jin, CHEN Jiazheng. NOx emission prediction of thermal power plant based on sparrow search algorithm optimized TPA-LSTM[J]. Control Engineering of China, 2026: 1-9. (2024-03-18)[2026-04-19]. https://doi.org/10.14107/j.cnki.kzgc.20230640.[KG)]

林伟俊, 李敏, 赵畅, 等. 基于延迟特性的NOx浓度软测量与喷氨优化[J]. 动力工程学报, 2023, 43(10): 1352-1362.LIN Weijun, LI Min, ZHAO Chang, et al. NOx concentration soft measurement and ammonia injection optimization based on delay features[J]. Journal of Chinese Society of Power Engineering, 2023, 43(10): 1352-1362.

高明明, 郭炯楠, 于浩洋, 等. 适应深度调峰的循环流化床NOx排放建模[J]. 洁净煤技术, 2023, 29(6): 24-31.GAO Mingming, GUO Jiongnan, YU Haoyang, et al. Modeling of nitrogen oxide emission in circulating fluidized bed for deep peak regulation[J]. Clean Coal Technology, 2023, 29(6): 24-31.

KE Xiwei, ZHU Shahong, HUANG Zhong, et al. Issues in deep peak regulation for circulating fluidized bed combustion: variation of NOx emissions with boiler load[J]. Environmental Pollution, 2023, 318: 120912.

张冲冲. 循环流化床锅炉变负荷过程中污染物排放动态特性研究[D]. 太原: 太原理工大学, 2019.

LABIDI M, EYNARD J, FAUGEROUX O, et al. A new strategy based on power demand forecasting to the management of multi-energy district boilers equipped with hot water tanks[J]. Applied Thermal Engineering, 2017, 113: 1366-1380.

赵征, 马毅杰. 基于多模型γ增量型阶梯式GPC的SCR脱硝系统优化控制研究[J]. 动力工程学报, 2023, 43(6): 735-741.ZHAO Zheng, MA Yijie. Research on optimal control of SCR denitrification system based on multi-model γ incremental stepped GPC[J]. Journal of Chinese Society of Power Engineering, 2023, 43(6): 735-741.

TAHIR M F, YOUSAF M Z, TZES A, et al. Enhanced solar photovoltaic power prediction using diverse machine learning algorithms with hyperparameter optimization[J]. Renewable and Sustainable Energy Reviews, 2024, 200: 114581.

LÜ You, YANG Tingting, LIU Jizhen. An adaptive least squares support vector machine model with a novel update for NOx emission prediction[J]. Chemometrics and Intelligent Laboratory Systems, 2015, 145: 103-113.

WAN Anping, CHANG Qing, AL-BUKHAITI K, et al. Short-term power load forecasting for combined heat and power using CNN-LSTM enhanced by attention mechanism[J]. Energy, 2023, 282: 128274.

卫治廷, 张敏, 周兴野, 等. 基于黏菌算法的热电联产机组负荷优化分配[J]. 动力工程学报, 2022, 42(4): 380-386.WEI Zhiting, ZHANG Min, ZHOU Xingye, et al. Optimal load distribution of cogeneration units based on slime mould algorithm[J]. Journal of Chinese Society of Power Engineering, 2022, 42(4): 380-386.

马尧, 曹越, 陈然璟, 等. 基于MLP-MINLP的发电机组干湿联合冷却系统运行优化[J]. 热力发电, 2025, 54(3): 121-130.MA Yao, CAO Yue, CHEN Ranjing, et al. Operation optimization of dry-wet joint cooling, system of generator set based on MLP-MINLP[J]. Thermal Power Generation, 2025, 54(3): 121-130.

罗智凌, 姚琦, 刘吉臻. 直接空冷系统风机群入口流量特性实验研究[J]. 动力工程学报, 2023, 43(10): 1294-1302.LUO Zhiling, YAO Qi, LIU Jizhen. Experimental study on inlet flow performance of fan array in the direct air-cooling system[J]. Journal of Chinese Society of Power Engineering, 2023, 43(10): 1294-1302.

YUAN Liang, WANG Xiangting, SUN Yao, et al.[KG(2x]Multistep photovoltaic power forecasting based on multi-timescale fluctuation aggregation attention me-chanism and contrastive learning[J]. International[KG)] Journal of Electrical Power & Energy Systems, 2025, 164: 110389.

GAO Zhanpeng, ZHANG Dingye, YI Wenjun. Projectile trajectory and launch point prediction based on CORR-CNN-BiLSTM-attention model[J]. Expert Systems with Applications, 2025, 275: 127045.

李昊, 罗云, 李瑞东, 等. 基于粒子群优化算法优化BP神经网络模型的间接空冷散热器性能监测[J]. 动力工程学报, 2019, 39(12): 973-980.LI Hao, LUO Yun, LI Ruidong, et al. Performance monitoring of indirect air-cooled radiators based on particle swarm optimization BP neural network model[J]. Journal of Chinese Society of Power Engineering, 2019, 39(12): 973-980.

ZAMAN E A K, AHMAD A, MOHAMED A. Adaptive threshold optimisation for online feature selection using dynamic particle swarm optimisation in determining feature relevancy and redundancy[J]. Applied Soft Computing, 2024, 156: 111477.

WANG Jiangjiang, FENG Yingsong, YE Shaoming, et al. NOx emission prediction of coal-fired power units under uncertain classification of operating conditions[J]. Fuel, 2023, 343: 127840.

任少君, 朱保宇, 翁琪航, 等. 基于物理信息神经网络的燃煤锅炉NOx排放浓度预测方法[J]. 中国电机工程学报, 2024, 44(20): 8157-8165.REN Shaojun, ZHU Baoyu, WENG Qihang, et al. Forecasting method for NOx emission in coal fired boiler based on physics-informed neural network[J]. Proceedings of the CSEE, 2024, 44(20): 8157-8165.

王仲平, 何黎黎, 丁更乾. 基于EMD-LSTM-ARMA模型短期发电量组合预测[J]. 现代电子技术, 2023, 46(3): 151-155.WANG Zhongping, HE Lili, DING Gengqian. Short-term power generation combination prediction based on EMD-LSTM-ARMA model[J]. Modern Electronics Technique, 2023, 46(3): 151-155.

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