Abstract
This contribution advocates the use of formal methods to verify and certifiably control the behaviour of computational devices interacting over a shared infrastructure. Formal techniques can provide compelling solutions not only when safety-critical goals are the target, but also to tackle verification and synthesis problems on populations of such devices: we argue that alternative solutions based on classical analytical techniques or on approximate computations are prone to errors with global repercussions, and instead propose an approach based on formal abstractions, error-based refinements, and the use of interface functions for the synthesis of abstract controllers and their concrete implementation. Two applicative areas are elucidated, dealing respectively with thermal loads and electricity-generating devices interacting over a smart energy network or over a local power grid. We discuss the aggregation of large populations of thermostatically-controlled loads and of photovoltaic panels, and the corresponding problems of energy management in smart buildings, of demand-response on smart grids, and respectively of frequency stabilisation and grid robustness.
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Notes
- 1.
In this context we do not distinguish between computations performed over the cloud (fog computing) or the edge of this platform.
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Acknowledgments
This is a position article accompanying a keynote talk at NSV 2016. It exclusively portrays the perspective of the author, without claims of generality or comprehensiveness. As such, references are limited to own work.
The author would like to thank former and current students involved in this specific area of work, particularly Sofie Haesaert, Sadegh E.S. Soudjani, and Majid Zamani; and collaborators on these topics, particularly Martie Fränzle, Joost-Pieter Katoen, Daniel Kroening, Marta Kwiatkovska, John Lygeros, Rupak Majumdar, Maria Prandini, and Claire Tomlin.
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Abate, A. (2017). Verification of Networks of Smart Energy Systems over the Cloud. In: Bogomolov, S., Martel, M., Prabhakar, P. (eds) Numerical Software Verification. NSV 2016. Lecture Notes in Computer Science(), vol 10152. Springer, Cham. https://doi.org/10.1007/978-3-319-54292-8_1
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