Computational Analysis and Intelligent Control of Load Forecasting Using Time Series Method

摘要

Electrical demand forecasting is a nonlinear and complex process for intelligent control of large-scale electrical power system and computational analysis and intelligent control of load forecasting. The research attempts for increasing accuracy of load forecasting. The time series method (TMS) is implemented for the midterm load forecasting for higher accuracy. It reflects the natural growth of the load. Here, the results show that the predication is better for midterm load forecasting (MTLF), which is most important parameter for seasonal planning and intelligent generation control of electric power using autoregressive and Box-Jenkins method by System Identification Tool (SIT) in MATLAB environment. Experimental support for the proposed work has been granted from State Load Dispatch Center (SLDC), Gotri, Gujarat, for forecasting the load. Here, load forecasting is carried out for Uttar Gujarat Vij Company Ltd. (UGVCL), India.