Modeling load forecast uncertainty using generative adversarial networks
Sign Up to like & getrecommendations! Published in 2020 at "Electric Power Systems Research"
DOI: 10.1016/j.epsr.2020.106732
Abstract: Abstract The integration of distributed energy resources (DER) increase the uncertainty of the load. Probabilistic load forecasting (PLF) is able to model these uncertainties in the form of quantile, interval, or density. However, the uncertainties… read more here.
Keywords: generative adversarial; uncertainty; forecast uncertainty; load forecast ... See more keywords
Computationally efficient modeling of load dynamics in turbocharged internal combustion engines
Sign Up to like & getrecommendations! Published in 2024 at "Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering"
DOI: 10.1177/09544070241272773
Abstract: Hybridization of non-road mobile machinery offers benefits for energy efficiency and decarbonization tasks. Hybrid electric power trains combine combustion engines with electric machines and batteries. Thus, it is important to model engine dynamics accurately so… read more here.
Keywords: modeling load; efficient modeling; computationally efficient; combustion ... See more keywords