Towards the Development of the Smart Grid: Fast Electricity Load Forecasting Using Different Hybrid Approaches

Currently, worldwide scientific community is doing a great effort of research in the area of Smart Grids because energy production, distribution, and consumption play a critical role in the sustainability of the planet. In this context, electricity load forecasting methodologies with fast response is a key component for demand-side management and the emergence of prosumers in the electricity grid. In this research it is shown that the computational intelligence techniques presented can deal with real time forecast, cope with incomplete measurement data and forecast signals of great variability, when applied to three real locations, with distinctly different characteristics.