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 load forecast solution for greenhouses is an offline model structure built on data from energy consumption and weather observations. The load forecast solution for greenhouses, is build on the collection of data from greenhouse consumers and weather observations to derive an offline model structure for load forecasting in greenhouses. Thus, the solution established an …
In connection with the Nordic Clean Energy Week, CITIES participates in an exciting policy workshop in Copenhagen. In the UN City of Marmormolen in Copenhagen, CITIES participates with professor Henrik Madsen as chair of a policy workshop under the heading “How to get a 100% renewable energy system? Developing the flexibility we need by integrating …
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.
