Modern energy systems are highly interconnected. Grid stability depends on real-time balancing of supply and demand, weather-dependent renewable generation, and cross-border energy flows. Disruptions in one part of the system – whether caused by weather, cyber incidents, or logistical bottlenecks – can trigger cascading effects that overwhelm the grid. In such situations, operators may be forced to curtail energy production or initiate controlled shutdowns to prevent total system collapse.
Organisms differ from mechanism by their capability for information processing and the causal efficacy of information over the material substrate it emerged from. In other words, to deal with such high levels of complexity that not just originate from interconnected interdependencies but also from these ofttimes far-from-equilibrium open systems that interact heavily with their surroundings, solutions are needed that use information and software applications not mere for monitoring purposes, or analysis, but that help define their behaviour. Industrial control systems do so, but are not well suited for dealing with unknown unknowns.
