Research on Intelligent Traceability Method for High Voltage Electric Energy Measurement Values Based on B+Search Tree Algorithm

Traditional traceability methods store energy measurement data in a simple structure. When searching for specific traceability data in large high-voltage power grids with a large amount of data, a large amount of traversal may be required, and the query response may be slow under sequential search. However, the B+search tree algorithm has good balance characteristics, with a height proportional to the logarithm of the data volume. When tracing with measurement related information as the index key, leaf nodes can be quickly located, and the query efficiency is high. Therefore, this study proposes an intelligent traceability method for high-voltage electric energy measurement values based on the $B+$ search tree algorithm. Firstly, collect data from various devices of the high-voltage electric energy metering system, and after cleaning and standardization, construct a storage structure based on the characteristics of the B+search tree. Then build a B+search tree, starting from the initial data insertion, continuously inserting energy metering data and maintaining the balance of the tree. When conducting traceability queries, first determine the traceability target, including measurement values, traceability depth and scope, and then use relevant key information as search keywords to determine the search path in the $\mathbf{B}+$ tree to find the leaf node where the target measurement value is located. After obtaining data, trace the measurement data of various levels of equipment or data sources based on the associated information. The experimental results indicate that this method helps to improve the efficiency and accuracy of tracing high-voltage electrical energy measurement values.