基于改进Bi-LSTM的虚回路自动校验方法研究

Research on Virtual Circuit Automatic Verification Method Based on Improved Bi-LSTM

针对智能变电站中虚回路人工校验效率低下、依赖于变电站配置描述(Substation configuration description,SCD)文件中虚端子定义不规范等问题,提出一种基于改进双向长短时记忆网络(Bi-directional long short-term memory,Bi-LSTM)的虚回路自动校验方法。首先,利用Word2vec模型对虚端子描述文本进行向量化编码,解决了虚端子描述文本的非结构化问题,使其能够在后续处理中被有效识别和分析。然后,引入了注意力机制与Bi-LSTM网络相结合的方式,以更全面地提取虚端子描述文本的语义特征。通过对比非标准虚端子与标准虚端子之间的相似度,实现了非标准虚端子的智能匹配,并建立了一个标准虚端子库作为基础数据支持。接着,利用经过验证的SCD文件与标准虚端子库,构建了虚回路模板库,该模板库能够有效存储并管理各类智能变电站设备的虚回路信息。最终,基于虚回路模板库实现了虚回路的自动校验,显著提升了虚回路校验过程的效率和准确性。试验结果表明,所提方法不仅提升了智能变电站虚回路校验的自适应性和精确度,还能够有效降低人工校验的工作量,显著提高智能变电站的自动化运行水平。该研究为未来智能变电站的虚回路校验和管理提供了重要的技术参考。

To address the challenges of low efficiency in manual verification and reliance on non-standard virtual terminal definitions in substation configuration description(SCD)files in intelligent substations,an automatic verification method for virtual circuits based on an improved Bi-directional long short-term memory(Bi-LSTM)network is proposed.Firstly,the Word2vec model is used to vectorize virtual terminal description texts,effectively resolving the issue of unstructured text in virtual terminal descriptions and enabling their efficient recognition and analysis in subsequent processes.Secondly,an attention mechanism combined with the Bi-LSTM network is incoporated to comprehensively extract the semantic features of the virtual terminal description texts.By calculating the similarity between non-standard and standard virtual terminals,intelligent mapping of non-standard virtual terminals is achieved and a standard virtual terminal library is constructed as foundational data support.Subsequently,verified SCD files and the standard virtual terminal library are used to build a virtual circuit template library,which effectively stores and manages virtual circuit information for various intelligent substation devices.Finally,based on the virtual circuit template library,automatic verification of virtual circuits are realized,significantly improving the efficiency and accuracy of the verification process.Experimental results demonstrate that the proposed method not only enhances the adaptability and accuracy of virtual circuit verification in intelligent substations,but also substantially reduces the workload associated with manual verification,greatly improving the level of automation in intelligent substation operations.This research provides crucial technical reference for the future verification and management of virtual circuits in intelligent substations.