摘要
针对目前人工决策基础上的制粉系统一键启停技术存在决策主观经验性强、操盘劳动强度大、节能优化潜力难以发掘等问题,提出了一种综合考虑制粉系统能耗与机组负荷跟踪性能的制粉系统启停决策评价模型,以安全引入网调负荷计划指令信号作为输入,研究了基于深度强化学习的制粉系统自启停智能决策方法,开发了制粉系统自启停决策闭环控制系统。研究结果通过仿真验证,并已在某超超临界1000 MW机组常用磨煤机上成功应用,节能降耗效果显著。研究结果可为火电机组少人、无人化运行技术提供有效借鉴。
A comprehensive evaluation model for the start-up and shutdown decision-making of the milling system,taking into account the energy consumption and tracking performance of the unit load,has been proposed to address issues such as subjective decision-making based on manual experience,high labor intensity in operation,and difficulty in exploring energy-saving optimization potential.This model safely incorporates the grid load scheduling command signal as input.Furthermore,a milling system start-stop intelligent decision-making method based on deep reinforcement learning has been studied,and a closed-loop control system for the automatic start-stop of the milling system has been developed.The research results have been verified through simulation and successfully applied to a commonly used coal milling system in a certain ultra-supercritical 1000 MW unit,achieving energy savings.The findings of this study can provide effective reference for the development of unmanned or minimally manned operation techniques for thermal power units.
作者
蔡佳辰
李军
高明
高林
高耀岿
昌鹏
CAI Jiachen;LI Jun;GAO Ming;GAO Lin;GAO Yaokui;CHANG Peng(Xi’an Thermal Power Research Institute Co.,Ltd.,Xi’an 710054,China;Shaanxi Yanchang Petroleum Fuxian Power Generation Co.,Ltd.,Yan’an 727502,China)
出处
《热力发电》
CAS
CSCD
北大核心
2024年第3期146-152,共7页
Thermal Power Generation
基金
国家重点研发计划项目(2022YFB4100700)
陕西省重点研发计划项目(2023-YBGY-274)。
关键词
深度强化学习
制粉系统
自启停控制
智能决策
deep reinforcement learning
milling system
autonomous start-up and shutdown control
intelligent decision-making
