Application of Big Data Technology in Lean Analysis of Power Grid Equipment Load

With the continuous increase and development of energy transformation needs, intelligent and sustainable new power systems are rapidly developing. Their complex grid structures and diversified participants lead to the generation of massive amounts of operational data in power systems. Big data analysis technology can efficiently process and mine the value of massive data, thereby improving the operation efficiency and stability of power grids, especially new power systems. In view of the current insufficient ability of big data analysis technology in mining the value of power system data, this paper takes a substation in a certain area as the case analysis object. The proposed big data analysis method for power systems based on the LOF algorithm is applied to process and analyze a large amount of historical operation data of substations, with a focus on calculating the load rate of transformers in substations in this area. Furthermore, through the big data visualization system, the main transformer load change trend of substations in the entire area is displayed. Driven by data, targeted operation and maintenance strategies are proposed to improve substation operation and maintenance efficiency and optimize resource allocation.