Abstract
To support the utilization of renewable energies, an optimized operation of energy systems is important. In recent years, many different optimization methods have been used in this field, including exact solvers and metaheuristics. Quite often, evolutionary algorithms yield good optimization results and allow for a flexible formulation of the optimization problem. Nevertheless, most approaches do not respect the dynamic nature of energy systems with time-dependent properties and stochastic variations. In this work, typical uncertainties are categorized and appropriate measures that help handling uncertainties in energy systems are presented and evaluated using an implementation of a building energy management system that may be used in simulation and practical application.
About the author
Jan Müller received his Dipl.-Phys. from the Karlsruhe Institute of Technology (KIT) in Karlsruhe, Germany. He majored in data analysis in experimental particle physics. In 2014, he joined the research group for efficient algorithms at the Institute for Applied Informatics and Formal Description Methods (AIFB) at the KIT. His research is focusing on optimization methods in energy systems and in particular on the integration of storage systems.
Karlsruhe Institute of Technology, Institute of Applied Informatics and Formal Description Methods, 76131 Karlsruhe, Germany
Acknowledgement
The author thanks Michael Sonnenschein for his support during the creation of this work and in the shepherding process of the Energy Informatics Conference 2016.
©2016 Walter de Gruyter Berlin/Boston
