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

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 software-defined, virtual approaches involving the Could-Fog-Edge continuum. In this work, we propose a model-based 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.