摘要
在全球能源低碳转型背景下,对1000 MW超临界机组的深度调峰能力提出更高的要求。针对传统监测系统难以适配非线性工况导致调节滞后、能耗增加的问题,提出基于传感器网络的深度调峰实时监测系统。该系统通过传感器网络采集关键参数来解决传统监测数据滞后问题,并利用连续小波变换滤除强电磁干扰噪声,有效提升数据质量。此外,遗传算法(Genetic Algorithm,GA)优化的迭代学习预测控制器通过动态适配非线性工况,在减少调节滞后的同时还可以降低能耗。实验结果表明:系统的皮尔逊相关系数达0.9647,显著优于对比模型。同时研究所构建的深度调峰实时监测系统在各类负荷场景响应速度最优,连续8 h运行控制器参数最大漂移率为0.52%,负荷跟踪误差为1.39%,有效提升了控制精度与稳定性,为机组深度调峰提供可靠的技术支撑。
In the context of global energy transition towards low-carbon,higher requirements have been set for the deep peak regulation capability of 1000 MW ultra-supercritical units.However,traditional monitoring systems are difficult to adapt to non-linear conditions,resulting in lag in regulation and increased energy consumption.Therefore,the study proposes a deep peak shaving real-time monitoring system based on sensor networks,which solves the problem of traditional monitoring data lag by collecting key parameters through sensor networks,and uses continuous wavelet transform to filter out strong electromagnetic interference noise,effectively improving data quality.In addition,the iterative learning predictive controller optimized by genetic algorithm dynamically adapts to nonlinear operating conditions,reducing energy consumption while minimizing regulation lag.Experimental results show that the Pearson correlation coefficient of the proposed system reaches 0.9647,significantly superior to the comparison model.At the same time,the deep peak regulation real-time monitoring system constructed by the research team leads in response speed in various load scenarios.The maximum drift rate of controller parameters during 8 consecutive hours of operation is only 0.52%,and the load tracking error is as low as 1.39%,effectively improving control accuracy and stability,and providing reliable technical support for the deep peak regulation of the units.
作者
范永胜
晋健
王学
于帅
牛天文
蔺明全
FAN Yongsheng;JIN Jian;WANG Xue;YU Shuai;NIU Tianwen;LIN Mingquan(National Energy Group Jiangsu Electric Power Co.,Ltd.,Nanjing 210000,China;Jiangsu Huifeng Renhe Environmental Protection Technology Co.,Ltd.,Taizhou 225300,China)
出处
《国外电子测量技术》
2025年第9期150-155,共6页
Foreign Electronic Measurement Technology
基金
国家能源集团科技项目(GJNY-23-69)。
关键词
传感器网络
超临界机组
深度调峰
实时监测系统
非线性工况
sensor network
ultra-supercritical unit
deep peak regulation
real-time monitoring system
non-linear conditions
