热力发电2024，Vol.53Issue(3)：146-152,7.DOI:10.19666/j.rlfd.202307118
基于深度强化学习的火电机组制粉系统自启停智能决策
Intelligent decision-making of start-up and shutdown for coal milling system in thermal power plants based on deep reinforcement learning
摘要
Abstract
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 1 000 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.关键词
深度强化学习/制粉系统/自启停控制/智能决策Key words
deep reinforcement learning/milling system/autonomous start-up and shutdown control/intelligent decision-making引用本文复制引用
蔡佳辰,李军,高明,高林,高耀岿,昌鹏..基于深度强化学习的火电机组制粉系统自启停智能决策[J].热力发电,2024,53(3):146-152,7.基金项目
国家重点研发计划项目(2022YFB4100700) （2022YFB4100700）
陕西省重点研发计划项目(2023-YBGY-274)National Key Research and Development Program(2022YFB4100700) （2023-YBGY-274）
Key Research and Development Program in Shaanxi Province(2023-YBGY-274) （2023-YBGY-274）
