Abstract
One of the Internet of Things promises is interoperability where data is shared and understood between things and applications. Such interoperability aims to achieve a common goal with better efficiency, optimization, and a better user experience. However, these things produces data in different formats and semantics making interoperability a real challenge still to be tackled. Linked data is currently positioned as a promising technology capable of addressing the heterogeneity challenge. In this paper, we present an efficient energy storage system which relies on a multi-system semantic representation of several data sources. Our approach analyzes data collected from external services such as weather and billing systems and our internal systems such as the building management system, power monitoring system, and data center system. The aim of the analyzed data coupled with our model enables efficient energy storage usage through forecasting and model predictive control for various purposes such as reducing energy consumed by a utility provider. In this present work, we detail the application model and then demonstrate the capability of this approach through a case study in a large office building.