A simulation platform for distributed energy optimization algorithms

Optimizing the energy system is vital for supply safety and efficient operation. One part of such optimization efforts are demand side measures. This article discusses a simulation platform for automated demand side management, i.e. automated load management. Up to now, the strategies and algorithms that decided where and when to take influence on the loads were very primitive. The complexity of the system did not allow for intuitively designing smarter algorithms. As the energy system is a wide area distributed system, questions about system stability, SCADA (supervisory control and data acquisition), reaction times or the relation to the wider environment (customer processes, energy market, etc.) are very difficult to research. The presented prototype is intended to offer a research platform for evaluating potential algorithms for their real-world usage. All relevant parts of the overall process ldquointelligent gridrdquo are modeled into the world of discrete event simulation and first implementation results are discussed.

[1]  P. Palensky,et al.  Integral resource optimization network - a new solution on power markets , 2005, INDIN '05. 2005 3rd IEEE International Conference on Industrial Informatics, 2005..

[2]  Helfried Brunner,et al.  INTELLIGENT DISTRIBUTION GRIDS IN RESPECT OF A GROWING SHARE OF DISTRIBUTED GENERATION , 2007 .

[3]  D.G. Infield,et al.  Stabilization of Grid Frequency Through Dynamic Demand Control , 2007, IEEE Transactions on Power Systems.

[4]  J. Ostergaard,et al.  Design and Modelling of Thermostatically Controlled Loads as Frequency Controlled Reserve , 2007, 2007 IEEE Power Engineering Society General Meeting.

[5]  F. Kupzog,et al.  DG DemoNet-Concept - A new Algorithm for active Distribution Grid Operation facilitating high DG penetration , 2007, 2007 5th IEEE International Conference on Industrial Informatics.

[6]  Sila Kiliccote,et al.  Participation through Automation: Fully Automated Critical Peak Pricing in Commercial Buildings* , 2006, Handbook of Web Based Energy Information and Control Systems.

[7]  P. Kundur,et al.  Power system stability and control , 1994 .