Multi-Criteria Linear Regression Analysis of Transmission Line Parameters Behaviour Prediction for Optimal Load Dispatch

The transmission system is responsible for conveying bulk energy from generation to the distribution for consumers. Its optimal performance depends on a number of factors ranging from technical to non-technical. One of the technical challenges frequently experience on transmission system is the load dispatch. Effective performance of transmission line requires that the available energy on the system be properly dispatched to avoid severe damages of the system. To achieve this, line parameters must be effectively monitored through the prediction of the line behavior. In this study, transmission line time series data was obtained from a case study preprocessed using normalization to improve the quality of the data Linear regression model was subsequently trained using the preprocessed data whereas the trained model was used for the prediction of transmission feeder behavior. Metrics like root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE), and R2 with heatmap and time series plots have been used to assess the performance of the model in predicting the dynamic behavior of the feeders. It can be concluded from this study based on the results presented that linear regression model is effective in predicting the behavior of Ikorodu1 and Ikorodu2 transmission feeders where the model was ineffective in predicting the behavior of the remaining transmission feeders. The results presented in this study demonstrated that linear regression model cannot be generalized for transmission feeders’ behavior prediction.