A stochastic model for scheduling energy flexibility in buildings. (August 2015)

• Record Type: Journal Article
• Authors: Ottesen, Stig Odegaard; Tomasgard, Asgeir
• Is Part Of: Energy. Volume 88(2015)
• Page Start: 364
• Page End: 376
• Publication Date: 2015-08
• Subjects: Demand side management -- Smart grids -- Scheduling -- Short-term flexibility -- Stochastic programming; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2015.05.049
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Due to technological developments and political goals, the electricity system is undergoing significant changes, and a more active demand side is needed. In this paper, we propose a new model to support the scheduling process for energy flexibility in buildings. We have selected an integrated energy carrier approach based on the energy hub concept, which captures multiple energy carriers, converters and storages to increase the flexibility potential. Furthermore, we propose a general classification of load units according to their flexibility properties. Finally, we define price structures that include both time-varying prices and peak power fees. We demonstrate the properties of the model in a case study based on a Norwegian university college building. The study shows that the model is able to reduce costs by reducing peak loads and utilizing price differences between periods and energy carriers. We illustrate and discuss the properties of two different approaches to deal with uncertain parameters: Rolling horizon deterministic planning and rolling horizon stochastic planning, the latter includes explicit modeling of the uncertain parameters. Although in our limited case, the stochastic model does not outperform the deterministic model, our findings indicate that several factors influence this conclusion. We recommend an in-depth analysis in each specific case. Highlights: We propose a new model for the scheduling of energy flexibility in buildings. We cover multiple energy carriers and include converter, storage and load units. We classify load units according to their flexibility properties. Our price structure covers different price regimes including peak fees. We perform a case study and discuss two approaches to handle uncertain parameters.