In an uncertain and complex environment, to ensure secure and stable
operations of large-scale power systems is one of the biggest challenges
that power engineers have to address today. Traditionally, power system
operations and decision-making in controls are based on power system
computations of physical models describing the behavior of power
systems. Largely, physical models are constructed according to some
assumptions and simplifications, and such is the case with power system
models. However, the complexity of power system stability problems,
along with the system's inherent uncertainties and nonlinearities, can
result in models that are impractical or inaccurate. This calls for
adaptive or deep-learning algorithms to significantly improve current
control schemes that solve decision and control problems.
Cyberphysical Infrastructures in Power Systems: Architectures and
Vulnerabilities provides an extensive overview of CPS concepts and
infrastructures in power systems with a focus on the current
state-of-the-art research in this field. Detailed classifications are
pursued highlighting existing solutions, problems, and developments in
this area.