Model-based Self-adaptive Management in a Smart Grid Substation

Salim Chehida (1) , Karim Fellah (1) , Eric Rutten (1) , Guillame Giraud (2) , Stéphane Mocanu (1)

1 CTRL-A - Control for Autonomic computing systems
2 RTE - Réseau de Transport d'Electricité [Paris]

The design of Cyber Physical Systems (CPS) is becoming increasingly complex due to the dynamic changes in their environments and infrastructures, requiring them to be self-adaptive. An important class of CPS is Industrial Control Systems (ICS), where a major trend is to upgrade from historically specific hardware and technologies towards more softwaredefined, virtual approaches involving the Could-Fog-Edge continuum. In this work, we propose a modelbased approach for the design of the self-adaptation in ICS, inspired by, and applied to an industrial case study in Smart Grids, more particularly an electrical substation from RTE (the French Energy Transmission company). The problem is to allocate and reallocate dynamically a set of control functions upon a distributed computing infrastructure, with self-adaptation to variations and perturbations. We define and implement the model-based autonomic management feedback loop using constraint programming, to describe the space of possible configurations, as well as the constraints and objectives formalizing the operators strategies. This model is used in simulation, calling the constraints solver at each cycle of the loop.

Mots clés: Self-adaptive Systems; CPS; Electrical Substation; Constraint Programming; Autonomic Manager; Energy; Smart Grid

Domaines: Informatique [cs]; Sciences de l'ingénieur [physics]

Salim Chehida, Karim Fellah, Eric Rutten, Guillame Giraud, Stéphane Mocanu. Model-based Self-adaptive Management in a Smart Grid Substation. ETFA 2023 - IEEE 28th International Conference on Emerging Technologies and Factory Automation, Sep 2023, Sinaia, Romania. pp.1-8. ⟨hal-04224198⟩