2022 - Research.com Engineering and Technology in Denmark Leader Award
Henrik Madsen focuses on Wind power, Mathematical optimization, Meteorology, Econometrics and Estimation theory. He has researched Wind power in several fields, including Probabilistic logic, Probabilistic forecasting and Electricity. Many of his studies on Mathematical optimization apply to Measure as well.
His work carried out in the field of Meteorology brings together such families of science as Climatology, Statistical model and Identification. Henrik Madsen has included themes like Sensitivity analysis, Uncertainty analysis and Bayes estimator, Estimator in his Econometrics study. His Estimation theory research includes elements of Stochastic differential equation, Statistical hypothesis testing, Calibration and Hydrological modelling.
Henrik Madsen mostly deals with Mathematical optimization, Meteorology, Wind power, Econometrics and Stochastic differential equation. Mathematical optimization is closely attributed to Estimation theory in his study. His study on Meteorology is mostly dedicated to connecting different topics, such as Climatology.
His Climatology research is multidisciplinary, relying on both Climate model and Precipitation. His Wind power study focuses on Offshore wind power in particular. Stochastic differential equation is a subfield of Applied mathematics that Henrik Madsen investigates.
Henrik Madsen mainly focuses on Model predictive control, Electricity, Flexibility, Mathematical optimization and Renewable energy. Henrik Madsen focuses mostly in the field of Model predictive control, narrowing it down to matters related to Control theory and, in some cases, Stochastic differential equation and Ventilation. His Stochastic differential equation study incorporates themes from Estimation theory and Extended Kalman filter.
In his study, which falls under the umbrella issue of Electricity, Stochastic programming is strongly linked to Environmental economics. His Flexibility research includes themes of Electric power system, Grid, Smart grid, Heat pump and Demand response. His Mathematical optimization research incorporates themes from Production and Control.
His scientific interests lie mostly in Model predictive control, Electricity, Flexibility, Renewable energy and Bidding. His studies in Model predictive control integrate themes in fields like Aeration, Activated sludge model and Control theory, Control theory. The study incorporates disciplines such as Stochastic differential equation, Artificial pancreas, Ventilation and Estimation theory in addition to Control theory.
The concepts of his Flexibility study are interwoven with issues in Electric power system, Control, Smart grid, Electricity generation and Demand response. His Electricity market study combines topics in areas such as Economic model, Mathematical optimization, Mathematical model, Nonlinear modelling and Operational planning. His Mathematical optimization research is multidisciplinary, incorporating elements of Variety, Drainage and Implementation.
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Time Series Analysis
Automatic calibration of a conceptual rainfall-runoff model using multiple objectives.
Journal of Hydrology (2000)
A review on the young history of the wind power short-term prediction
Alexandre Costa;Antonio Crespo;Jorge Navarro;Gil Lizcano.
Renewable & Sustainable Energy Reviews (2008)
Online short-term solar power forecasting
Peder Bacher;Henrik Madsen;Henrik Aalborg Nielsen.
Solar Energy (2009)
Preoperative Staging of Lung Cancer with Combined PET–CT
Barbara Fischer;Ulrik Lassen;Jann Mortensen;Søren Larsen.
The New England Journal of Medicine (2009)
Parameter estimation in distributed hydrological catchment modelling using automatic calibration with multiple objectives
Advances in Water Resources (2003)
Identifying suitable models for the heat dynamics of buildings
Peder Bacher;Henrik Madsen.
Energy and Buildings (2011)
An evaluation of the impact of model structure on hydrological modelling uncertainty for streamflow simulation
Michael B. Butts;Jeffrey T. Payne;Michael Kristensen;Henrik Madsen.
Journal of Hydrology (2004)
Comparison of annual maximum series and partial duration series methods for modeling extreme hydrologic events: 1. At-site modeling
Henrik Madsen;Peter F. Rasmussen;Dan Rosbjerg.
Water Resources Research (1997)
Integrating Renewables in Electricity Markets: Operational Problems
Juan Miguel Morales González;Antonio J. Conejo;Henrik Madsen;Pierre Pinson.
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