Short-Term Load Forecasting Using Generalized Regression and Probabilistic Neural Networks in the Electricity Market

For the economic and secure operation of power systems, a precise short-term load forecasting technique is essential. Modern load forecasting techniques – especially artificial neural network methods – are particularly attractive, as they have the ability to handle the non-linear relationships between load, weather temperature, and the factors affecting them directly. A test of two different ANN models on data from Australia’s Victoria market is promising.