Raimo Nikkilä

Agent-based modeling and simulation of a smart grid: A case study of communication effects on frequency control

Abstract A smart grid is the next generation power grid focused on providing increased reliability and efficiency in the wake of integration of volatile distributed energy resources. For the development of the smart grid, the modeling and simulation infrastructure is an important concern. This study presents an agent-based model for simulating different smart grid frequency control schemes, such as demand response. The model can be used for combined simulation of electrical, communication and control dynamics. The model structure is presented in detail, and the applicability of the model is evaluated with four distinct simulation case examples. The study confirms that an agent-based modeling and simulation approach is suitable for modeling frequency control in the smart grid. Additionally, the simulations indicate that demand response could be a viable alternative for providing primary control capabilities to the smart grid, even when faced with communication constraints.

Spatial inference with an interchangeable rule format

Rule interchange between information systems is expanding as new interoperable rule formats are emerging from research. However, existing spatial inference systems generally operate on locally stored data with an internal rule format. Consequently, their design offers little support or facilities for rule interchange. This article presents the requirements, components and design for a spatial inference system with rule interchange. Computational efficiency and overall functionality of the design are considered separately, with the latter demonstrated using encoded agricultural legislation and data. A spatial inference system with rule interchange is based on three primary components: rule representation, spatial functionality and data integration. Of these, the interoperable rule representation and data integration distinctly differ from existing spatial inference systems. The presented inference system combines a spatial superset of the W3C Rule Interchange Format (RIF) with full Open Geospatial Consortium simple feature access (OGC SFA) functionality and on-demand data integration utilising Resource Deception Framework (RDF). The design was found to be effective with a computational efficiency depending predominantly on the spatial operations. This design could be further adapted to implement spatial extensions for existing inference systems. Considerable benefits were also discovered when RIF was used as the native language for the inference engine, thereby removing the need for rule transformations and facilitating on-demand data integration with the GML.