WP Leader: John Bagterp, email@example.com
Objective: Develop tools for short term (probabilistic) forecasting and control of integrated energy systems with flexible geographic scope.
|WP5.1||Statistical characterisation of resources will be conducted with a focus on the possibilities for forecasting. The interactions, dynamics, dependencies and correlations between resources will be specified (with contributions from WP3 and WP4).|
|WP5.2||Establish methods for probabilistic forecasting of consumption and production. Multi-variate forecasts will account for the relationships between, e.g. wind and solar.|
|WP5.3||Develop controllers and operational strategies for direct control of system states (e.g. temperature control in district heating systems), taking probabilistic forecasts as an input.|
|WP5.4||Develop controllers and operational strategies for economic based control for an indirect control of the system states, for example, by sending out a price signal.|
|WP5.5||An operations and forecasting portal will be developed to provide forecasts and set-points to devices and subsystems operating as defined in WP5.3 and WP5.4. A special focus will be placed on solutions for demand side management.|
SDE-modelling for smart energy systems
PhD student: Rune Grønborg Junker, firstname.lastname@example.org
This PhD project aims at making mathematical models for the production and consumption of electricity. The purpose of the models being the making of control strategies such as to improve efficient usage of electricity. Since large parts of the production and consumption of electricity are well understood physically, the models are based on physical laws. On the other hand, human behaviour and phenomenon too complicated to model introduce uncertainty that has to be taken into account in the models, which is why this project uses SDE’s (stochastic differential equations) as models. This combination of physical laws and statistical techniques is usually referred to as grey-box modelling, which is an established field of study. If successful, this PhD project will not only contribute to the CITIES project with appropriate mathematical models but also to the theoretical understanding of SDE-models.