1. A method for forecasting short term power system load in a power supply system, comprising: by a processor, for a plurality of input features, computing a plurality of respective correlation scores using training data, each correlation score representing a strength of correlation between an input feature and the power system load; by a processor, computing, using the training data, a kernel matrix defining mappings of the plurality of input features for use in a non-linear support vector regression framework, the kernel matrix including a weighting of each of the plurality of input features using the respective correlation scores; and by a processor, computing a short term power system load forecast from a set of input data, using the non-linear support vector regression framework.