| Popis: |
Power grid is a common platform connecting all the generating stations and demand centres (loads), where the energy is generated and consumed instantaneously. The demand varies from minute to minute, and the generation needs to be adjusted accordingly to meet the demand. However, with large intermittent renewable power plants coming online, this balancing becomes even more complicated. Although there is a growing emphasis on predicting the renewable generation, prediction of demand also can help in grid-level energy management. In this paper, we compare the prevalent demand forecasting practice with the model developed using multivariable regression technique. This simple model shows an improvement of 3% over the present demand prediction scenario, with respect to the mean absolute error. In future, use of more precise data for model training and addition of further variables may increase the accuracy level. This model does not need any large computational set-up or capacity building. We have used electricity demand data of Karnataka to train and test the model. However, it can be replicated for any other state. |
