Research on safety and energy efficiency monitoring technology for substation power system based on load holography perception

Substations are an important component of the power grid, and their energy consumption and operational reliability are crucial for the safe and stable operation of the power grid. This article aims to enhance the reliability of electrical equipment in substations and reduce energy consumption levels, which is of great significance. The AC and DC systems utilized in substations play a vital role in ensuring the safe and stable operation of substations. Currently, there is no intelligent method for monitoring the operating conditions and energy efficiency and providing abnormal warnings for various equipment in the station power system. This article is based on an integrated monitoring technology that combines measurement and sensing technology, big data applications, and artificial intelligence. It extracts the electrical characteristic parameters of all station electrical equipment and identifies and detects the type, electrical information, operation time, operation status, and energy consumption indicators of station electrical equipment through pattern recognition, feature matching, and machine learning. This enables holographic visual perception of load equipment in the station electrical system, significantly improving the safety management level of substations.