Construction and Application of Power Data Operation Monitoring Platform Based on Knowledge Map Reasoning

Introduction

Under this background, the traditional power industry has changed. Various power data operation monitoring platforms are constantly put into production. These platforms can provide power equipment information for managers and are also responsible for displaying relevant data on the power system in different states. However, the traditional power data operation monitoring platform cannot meet the development requirements. The core of optimising the monitoring platform is to build a knowledge map and optimise and simulate the experimental environment. This knowledge map can accurately match, identify, and classify the target information in the database. The present study analyses the power system by building a knowledge map. It also ensures the safe operation of the power system by establishing a perfect power data processing platform, which has important practical value for the subsequent development of the power system.

Given the rapid development of power systems, many scholars have accelerated research on power system data platforms. Wang (2019) believed that the input of false data would seriously threaten the safe operation of a power system; thus, he comprehensively discussed the attack target, construction method, and consequences of false data. Hou (2019) proposed a data-driven method based on a power system to analyse the impact of renewable energy penetration on the power system. Ren and Yan (2019) proposed a fully data-driven power system security assessment method for the problem of incomplete data measurement. Koronen, Åhman, and Nilsson (2020) believed that the growth of the number of data centres would lead to an increase in power demand and the emergence of new power-intensive industries. Their analysis showed that demand response and the integration of energy systems promote the development of power market design. While the above studies have achieved good results, their methods are too traditional and not convincing enough (Liu, 2022).

Other scholars have different views about the research on power system data platforms. Mouassa, Tarek, and Ahmed (2017) analysed collected data through the Ant Lion Optimiser algorithm and solved the optimal reactive power dispatching problem of a large-scale power system. Pan, Teixeira, Cvetkovic, and Palensky (2018) performed a risk analysis on comprehensive data integrity and availability attacks of power system state estimation and proposed a security index for vulnerability assessment of such attacks. Liu’s (2020) measurement data source authentication algorithm based on feature extraction technology automatically measured data and realised power system situation awareness. Netto and Mili (2018) estimated the rotor angle and speed of the synchronous generator based on the Kalman filter of robust generalised maximum likelihood Koopman operator, which was used to estimate the dynamic state of the power system. However, the above research on power system data platforms lacks in-depth analysis and discussion of knowledge map reasoning technology. Thus, the high integration and advantages of knowledge map reasoning technology and power system data platform are hindered (Man, Wang, & Liu, 2021).