Load forecasting is at the core of nearly all decisions made in energy markets. The electricity load demand is influenced by numerous factors - ranging from weather conditions over seasonal effects to socio-economic influences. In this paper, we present first computational results using a linear approach supported by support vector machines for robust regression.
['Sonia De Cosmis', 'Renato De Leone', 'Erik Kropat', 'Silja Meyer-Nieberg', 'Stefan Pickl']
Electric load forecasting using support vector machines for robust regression