Forecasting Power Demand Using Artificial Neural Networks For Sri Lankan Electricity Power System

Accurate models for electricity power load forecasting are essential to the operation and planning of an electricity company. Neural Networks are considered as a computational model that is capable of doing nonlinear curve fitting. In this research, the application of neural networks to study the design of Short Term load Forecasting (STLF) Systems for Sri Lanka was explored. Three layered neural network architecture with back propagation algorithm is proposed to model STLF. The results show that neural network gives the minimum forecasting error compared to the statistical forecasting models and hence it can be considered as an effective method to model the STLF systems for Sri Lankan electricity power system.