Merging Optimization and Control in Power Systems

This book offers a comprehensive look at integrating optimization and control within power systems, presenting innovative solutions for modern challenges.

In Merging Optimization and Control in Power Systems, a skilled team of engineers presents an in-depth exploration of distributed optimal control tailored for modern power systems. This book redefines control design through the lens of cyber-physical systems, addressing critical challenges such as operational constraints, non-smooth objective functions, and the rapid power fluctuations driven by renewable energy sources. It thoughtfully considers issues like partial control coverage, communication delays, and varying sampling rates, making it a vital resource for professionals in the field.

The authors bridge the divide between optimization and control in two significant ways. They delve into optimization-based feedback control, detailing how feedback controllers can effectively steer system states towards desired optimal conditions. Furthermore, they explore feedback-based optimization, proposing a method to solve complex optimization and control problems in real-time, adapting to the ever-changing landscape of power systems.

Readers will appreciate the book's thorough critique of traditional centralized power system control, advocating for the innovative merged approach it presents. It covers fundamental transformations in the power sector, including the rise of renewable energy, the advent of electric vehicles, and growing load demands. With comprehensive data, case studies, and illustrations, Merging Optimization and Control in Power Systems serves as an essential guide for postgraduate students and researchers well-versed in power system dynamics, convex optimization, and control theory.