Ensemble Forecasting Applied to Power Systems

• Main Author: Bracale, Antonio (auth)
• Other Authors: Falco, Pasquale De (auth)
• Format: Electronic Book Chapter
• Language: English
• Published: MDPI - Multidisciplinary Digital Publishing Institute 2020
• Subjects: History of engineering & technology; forecast combination; solar energy; electricity price forecasting; calibration window; heuristic algorithm; deep learning; electric load forecasting; smart grids; hierarchical load forecasting; predictive distribution; solar PV; solar farm; microgrid; energy management; lower and upper bound estimation; solar power prediction; interval prediction; kernel density estimation; average probability forecast; probabilistic forecasting; forecasting; distributed energy resources; photovoltaic power; conditional predictive ability; clearness index; Fourier series; combining forecasts; weather station combination; distributed generation; clear sky index; extreme learning machine; ensemble methods; pinball score; autoregression
• Online Access: DOAB: download the publication; DOAB: description of the publication

Modern power systems are affected by many sources of uncertainty, driven by the spread of renewable generation, by the development of liberalized energy market systems and by the intrinsic random behavior of the final energy customers. Forecasting is, therefore, a crucial task in planning and managing modern power systems at any level: from transmission to distribution networks, and in also the new context of smart grids. Recent trends suggest the suitability of ensemble approaches in order to increase the versatility and robustness of forecasting systems. Stacking, boosting, and bagging techniques have recently started to attract the interest of power system practitioners. This book addresses the development of new, advanced, ensemble forecasting methods applied to power systems, collecting recent contributions to the development of accurate forecasts of energy-related variables by some of the most qualified experts in energy forecasting. Typical areas of research (renewable energy forecasting, load forecasting, energy price forecasting) are investigated, with relevant applications to the use of forecasts in energy management systems.