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基于STM32的便携式智能配电一体化移动终端控制系统研究 被引量:3

Research on portable intelligent distribution integrated mobile terminal control system based on STM32
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摘要 针对目前我国偏远地区配电及检修存在的人力依赖性强、便携性较差、缺乏智能化测控设备、无法形成智能化的电力数据流一体化融合机制等问题,开发了基于STM32的便携式智能配电一体化移动终端控制系统。硬件中心面板采用原子科技STM32F103实现一体化控制,结合外围电路进行远程管理,承载了软件层的智能化运行;软件层引入改进深度强化学习算法,对较长周期内的配电及检修信息进行数据深度分析,挖掘潜在规律,为后续相关政策的制定提供数据支撑,构建智能化的电力数据流一体化融合机制。选取国家电网某电力公司进行实际验证,利用VS2016平台开发了验证环境,并对控制系统整机进行了实证分析,结果表明,控制系统运行稳定,功能完整,具有较强的实用性、鲁棒性、适应性,具备在我国偏远地区实际推广的应用价值。 Theportable intelligent mobile terminal controller based on STM32 for distribution and maintenance in remote areas of China is developed to solve the problems of strong human dependence,poor portability,lack of intelligent measurement and control equipment, and unable to form an intellectualized power data flow integration mechanism.At the hardware level,STM32F103 integrated control board of atomic technology is used as the main control center,supplemented by necessary peripheral circuits,to realize intelligent remote control management and provide the running carrier for software. At the software level,an improved deep reinforcement learning algorithm is introduced to analyze the distribution and maintenance information in a longer period of time and tap the potential. In order to provide data support for the formulation of subsequent relevant policies,an intellectualized power data flow integration mechanism is constructed.The power company of the State Grid is selected to carry out the actual verification. The verification environment is developed on VS2016 platform and the whole controller is empirically analyzed. The controller runs stably and has complete functions. It has strong practicability,robustness and adaptability,and has practical application value in remote areas of China.
作者 刘栋 张建鹏 LIU Dong;ZHANG Jianpeng(Xinjiang Institute of Engineering,Urumqi 830023,China)
机构地区 新疆工程学院
出处 《电子设计工程》 2022年第20期61-67,共7页 Electronic Design Engineering
基金 新疆维吾尔自治区经济和信息化委员会计划项目(XJJXW047)。
关键词 STM32 移动终端控制系统 智能配电 改进深度强化学习算法 数据挖掘 STM32 mobile terminal control system intelligent distribution improved deep reinforcement learning algorithms data mining
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