The fundamental goal of electric grids is to generate and distribute the electricity to all end users. One of the necessary properties an electric grid should possess for normal functioning is stability. In this paper we will evaluate the local stability of an existing electric grid data as stable or unstable using classification algorithms and calculate performance measures namely Accuracy, Precision, Recall and F1-Score and compare the performance measures of the classifiers. Also, the proposed system evaluates the correctness of stability values using regression algorithms and calculates the performance measures namely Mean Square Error (MSE), Mean Absolute Error (MAE) and r^2 Score and compare the performance measures of regression algorithms.
G. S. Keerthanna, Abishek, S., Annapoorani, V., Singh, C., and Radhika, N., “Comparison of classification and regression algorithms for evaluating the performance of electric grid stability”, Journal of Advanced Research in Dynamical and Control Systems, vol. 11, no. 4, pp. 1292-1296, 2019.