Statistical model checking for distributed probabilistic-control hybrid automata with smart grid applications

Authors:
João Martins;André Platzer;João Leite
Affiliations:
Computer Science Department, Carnegie Mellon University, Pittsburgh PA and CENTRIA and Departamento de Informática, FCT, Universidade Nova de Lisboa;Computer Science Department, Carnegie Mellon University, Pittsburgh PA;CENTRIA and Departamento de Informática, FCT, Universidade Nova de Lisboa
Venue:
ICFEM'11 Proceedings of the 13th international conference on Formal methods and software engineering
Year:
2011

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Abstract

The power industry is currently moving towards a more dynamical, intelligent power grid. This Smart Grid is still in its infancy and a formal evaluation of the expensive technologies and ideas on the table is necessary before committing to a full investment. In this paper, we argue that a good model for the Smart Grid must match its basic properties: it must be hybrid (both evolve over time, and perform control/computation), distributed (multiple concurrently executing entities), and allow for asynchronous communication and stochastic behaviour (to accurately model real-world power consumption). We propose Distributed Probabilistic-Control Hybrid Automata (DPCHA) as a model for this purpose, and extend Bounded LTL to Quantified Bounded LTL in order to adapt and apply existing statistical model-checking techniques. We provide an implementation of a framework for developing and verifying DPCHAs. Finally, we conduct a case study for Smart Grid communications analysis.