Research on Transformer Fault Diagnosis Based on GWO-CS Optimized SVM

A combined Grey Wolf Optimization and Cuckoo Search algorithm, called GWOCS, has been proposed to address the issue of low accuracy in dissolved gas analysis for transformer fault diagnosis. The GWOCS algorithm is applied to optimize the Support Vector Machine (SVM) for transformer fault diagnosis in power systems. The performance of the GWOCS algorithm is tested using two typical test functions, and it has been demonstrated that GWOCS algorithm has stronger stability and search ability. By using GWOCS to optimize the key parameters of SVM, a GWOCS-SVM transformer fault diagnosis model is established. The experimental results show that compared with the traditional GWO-SVM model, the GWOCS-SVM model improves the accuracy of transformer fault diagnosis by 7%. This highlights the convenience, necessity, and effectiveness of using intelligent algorithms to find optimal solutions.