基于AI的配电网稳态作业行为嵌入式感知系统设计
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引用本文:王晓东,王加臣,张 明,马志强,刘 伟.基于AI的配电网稳态作业行为嵌入式感知系统设计[J].计算技术与自动化,2022,(4):179-184
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王晓东,王加臣,张 明,马志强,刘 伟 (国网江苏省电力有限公司苏州供电分公司江苏 苏州 215400) 
中文摘要:配电网稳态感知系统受到感知模型的影响,导致系统感知结果RMSE值较高,对此,提出了基于AI的配电网稳态作业行为嵌入式感知系统设计。设计前端感知器和无线网关。根据配电网稳态作业工作特点,构建稳态数据采集体系。结合数据统一和数据辨识等多种算法,提取智能感知计算参数。依托于AI领域的深度学习技术,设计自适应稳态感知模型。系统测试结果表明:所提出的系统感知结果的RMSE值仅为0.028,满足了配电网稳态作业行为感知精度要求。
中文关键词:AI  配电网  稳态作业  嵌入式系统  行为感知  计算参数
 
Design of AI Based Embedded Sensing System for Steady-state Operation Behavior of Distribution Network
Abstract:The distribution network steady-state sensing system is affected by the sensing model, resulting in the high RMSE value of the system sensing result. Therefore, an AI based embedded sensing system design for distribution network steady-state operation behavior is proposed. The front-end perceptron and wireless gateway are designed. According to the characteristics of steady-state operation of distribution network, the steady-state data acquisition system is constructed. Combined with a variety of algorithms such as data unification and data identification, the intelligent sensing calculation parameters are extracted, and the adaptive steady-state sensing model is designed based on the deep learning technology in the AI field. The system test results show that the RMSE value of the proposed system sensing result is only 0.028, which meets the sensing accuracy requirements of steady-state operation behavior of distribution network.
keywords:AI  distribution network  steady-state operation  embedded system  behavioral perception  calculation parameters
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