New technique of load forecasting for an isolated area

Abstract

Forecasted electrical loads are the core information required in many processes, especially in power system expansion planning process. Several techniques are available to forecast the loads of an area for a future period. The pattern of load growth over the past are the basic requirements for all of these techniques. However, in an isolated rural area historical load data may not be available either because, the electricity might not be a source of energy in the past in that area or the available data may not be representative ones, rather suppressed load demands. First, research presents a technique [27, 28] offorecasting loads for an isolated area. This technique identifies the factors responsible for the development of electrical loads. The correlation of each of these factors with the load growth is determined. The technique selects one or more areas with the characteristics similar to those of an isolated area. The forecasted loads of this area are derived from the selected area should be such that its history must be known. It develops a relation between the load dependent factors of the selected area/areas with those of an isolated area. The forecasted loads of the selected area/areas using the relation developed from the load dependent factors. The methodology is applied to an isolated area of Bangladesh. However, there is no conceptual difficulty in applying the methodology to forecast the loads of any isolated area. To realize a relationship between the load dependent variables and the demand which may be highly nonlinear, a relatively new technique, using artificial neural network, capable of solving a non-linear mapping, is investigated. The inherent parallelism of neural network captures the past trend of the event and make projection of the best guess. The study shows encouraglllg result on forecasting the loads of an isolated area, using the neural network method.