Elective module in the master specialization area (energy computer science).
Associated with the modules:
Energieinformationssysteme
Smart Grid Management
Time of examination
At the end of the semester
Module examination
Oral exam
Skills to be acquired in this module
Successfully completing this lecture will enable the students to mathematically model simple controllable electrical generators and consumers and to simulate them together with appropriate control algorithms within smart grid scenarios. To achieve this goal, students will start with deriving computational models from physical models and evaluate them. In order to manage the integration of control algorithms, students are taught the principles of cosimulation using the "mosaik" smart grid co-simulation framework as an example.
Students will be able to understand and apply distributed, agent-based control schemes to decentralized energy generators and/ or consumers. As a result, students are able to analyze the requirements for successful application to real power balancing regarding capacity utilization, robustness, and flexibility. In addition, students learn the foundations of planning and conducting simulation based experiments as well as the interpretation of the results. Special attention will be paid on establishing a balance between the results' precision and robustness and the necessary effort (design of experiments) in order to gain as much insight into interdependencies with as few experiments as possible.
Professional competence The students:
derive and evaluate computational models from physical models
use the "mosaik" smart grid co-simulation framework
analyze the requirements for successful applications to real power balancing regarding capacity utilization, robustness, and flexibility
name the foundations of planning and conducting simulation based experiments as well as the interpretation of the results
are aware of the balance between the results' precision and robustness and the necessary effort (design of experiments) in order to gain as much insight into interdependencies with as few experiments.
Methodological competence The students:
model simple controllable electrical generators and consumers
simulate simple controllable electrical generators and consumers with appropriate control algorithms within smart grid scenarios
apply distributed agent-based control schemes to decentralized energy generators and/ or consumers
evaluate simulation results
search information and look into methods to implement models
propose hyphothesis and check their validity with design of experiments methods
Social competence The students:
apply the pair progamming development technique
discuss design decisions
identify work packages and are responsible for it
Self-competence The students:
reflect on their own use of power as a limited resource
accept and use criticism to develop their own behaviour
