Flexible power consumption requires fully automated devices
Professor Henrik Madsen from DTU Compute believes that researchers and practitioners under the CITIES-project have broken the code for how electricity companies and other actors can enable flexible consumption. In an interview with ienergi.dk, published in July 2018, Madsen talks about automation, artificial intelligence, software and big data in the cloud. In Intelligent Energy, these research results are translated into in the process of designing future net tariffs, so they reward flexible customers.
The solution software for Model Predictive Control (HPMPC) is a toolbox for High-Performance implementation of solvers for Model Predictive Control (MPC). The tool contains routines for fast solution of MPC and MHE (Moving Horizon Estimation) problems on embedded hardware. Further description and insights into the project is coming soon. The software is available on GitHub.
The project on continuous time stochastic modelling (CTSM) is very useful for grey-box modelling of physical systems using data. The grey-box modelling approach bridges the gap between physical and statistical modelling. The solution is widely used for estimating and identifying models for physical systems, like the heat dynamics of a building, the hydraulics in a …
CITIES, University of Zagreb (Faculty of Mechanical Engineering) & The City of Zagreb are organizing a joint workshop on: Data intelligent operation of district heating and district cooling systems In recent years, there has been a growing interest in using big data to improve district heating and district cooling systems. Sensors are becoming cheaper, and …
