Generation of Experimental Data for Sag+Transient Disturbance in Smart Grid Systems

Smart grids are a more efficient and safer electricity grid that includes today's technology. The biggest problem for smart grid systems is power quality disturbances. If power quality disturbances are not monitored and detected, they can cause major problems. For this reason, many researchers use signal processing methods and artificial intelligence tools on power quality disturbance data. Obtaining the data, which is the basis of the studies, is a separate subject of study. Since it is not possible to obtain data from the field, synthetic data or limited experimental data are mostly used in studies. In this study, the data of sag+transient signal, which is one of the complex data of power quality disturbances, was obtained from the experimental setup established in the laboratory environment. The similarity of experimental data associated with synthetic data to real data was compared through error rates. The results gave similarity values of 0.9492, 0.9477 and 0.8358 for Pearson, Spearman and Kendall respectively. It has been a result that will be a source for future studies.