Short-term multi-region load forecasting based on weather and load diversity analysis

In a Power system covering large geographical area, a single forecasting model for overall load of the whole region sometimes can not guarantee satisfactory forecasting accuracy. One of the major reasons is because the existence of load diversity, usually caused by weather diversity. In such a system, multi-region load forecasting will be a feasible and effective solution to provide more accurate forecasting results. This paper aims to demonstrate the existence of weather and demand diversity within the control area of an electric utility in Midwest US. Based on the analysis, an Artificial Neural Network (ANN) based multi-region load forecasting system has been developed and tested by using the actual data. Simulation results validate the superiority of the proposed multi-region load forecasting system to the single aggregate forecasting model.