Comparative study on load forecasting technologies for different geographical distributed loads

Abstract

For a power system covering large geographical area, a single forecasting model for the entire region cannot guarantee the satisfactory forecasting accuracy. One of the major reasons is because the load diversity and weather diversity throughout the region. For such a system, multi-region load forecasting will be a feasible and effective solution to generate more accurate forecasting results. However, some technical issues arise when performing the multi-region load forecasting, the major challenge is how to optimally partition/combine the regions to achieve better forecasting results, especially under transient weather conditions. On the other hand, load forecasting for small areas, especially for a distribution feeder or micro grid, is also difficult because load variation in local areas is larger than that of a large system. In addition, the correlation between weather variables and small area loads would be unstable. Therefore, a two-stage load forecasting module could be utilized to improve the forecasting accuracy, and the risk assessment of local load forecasting uncertainty could be studied. This paper discusses respectively a large geographical load forecasting in Midwest US and a small area load forecasting in a UK distribution feeder. For the load forecasting at the large geographical area, a multi-region forecasting system that can find the optimal region partition in both stationary and transient weather and load conditions is discussed. For the load forecasting at the small feeder, a two-stage combination module is discussed; furthermore, risk evaluation technologies based on time-domain and frequency-domain methods are also proposed to assess the uncertainty of load forecasting.