Industrial demand-side flexibility: A benchmark data set


To cope with the new demands of an electrical grid based on mostly renewable energy, more flexibility on the demand-side is needed. To test new demand-side management strategies, energy consumption data sets which come with some information about the inherent flexibility of the processes, are needed. However, such data sets are often commercially sensitive and thus not published or replaced with entirely artificial data. In the present paper, we introduce a new benchmark data set containing scheduling scenarios of industrial processes with flexibility information. The instances are based on a real-world data set of a small scale industrial facility, from which we extract process characteristics using a novel motif discovery technique. We provide an in-depth analysis of the benchmark data set and show that it is suitable to evaluate smart-grid scheduling techniques.

e-Energy 2019 - Proceedings of the 10th ACM International Conference on Future Energy Systems