Smart grids use digital communications, signal processing, sensing, and control systems technologies to enhance the efficiency, reliability, and security of electrical power systems and contribute to the sustainability of energy with the large penetration of renewable energy sources. Increasing integration of the cutting-edge digital technologies has become the source of new challenges such as cybersecurity and uncertainties, while at the same time being the cornerstone of new opportunities such as real-time control and monitoring systems to enhance the power system stability.

Maintaining the stability of power systems has become an even more challenging problem with the increasing complexity by enabling two-way power flow through active loads and energy storage systems. Fortunately, making real-time data exchange between sensors and control units possible through communication networks allows designing advanced control systems. However, communication delay which is inherent in communication systems limits the capacity of the control systems and introduce uncertainty to the system. On the other hand, cyber-attacks to the various segments of smart grids threat the stability and security of power systems by leading to malfunction of underlying protection and control systems.

In today's world, isolating systems by deploying private networks cannot entirely protect them from cyber-attacks and penetration. The Stuxnet case, for example, led to the malfunctioning of control systems in Iranian's nuclear power station, despite being physically isolated from the global network. Therefore, addressing various form of cyberattacks requires defense-in-depth strategies whereby enabling multiple layers of security in the underlying communication and control systems.

This dissertation presents distributed and decentralized robust control frameworks that aim at enhancing the transient stability and resiliency of smart grids in the face of cyber-physical disturbances by employing phasor measurement units (PMU) and distributed energy storage systems (DESS). Robust controllers introduce a novel time delay compensation technique to mitigate the effect of communication and control input time delay. In addition, uncertainties arising from varying plant parameters and errors in sensor measurements are considered in the robust controller design. Furthermore, the communication delay is addressed in network layer by developing an adaptive medium access control (MAC) protocol to reduce the channel access delay and improve the data throughput with respect to increasing numbers of connected intelligent devices.

The success of robust controllers is proven by conducting several comparative case studies based on IEEE 39 bus 10 machines test power system. The enhanced resiliency to the large time delay and uncertainties highlights the success of robust controllers in comparison to the state-of-the-art controllers. To illustrate, while the parametric feedback linearization (PFL) controller can tolerate up to 160ms communication delay, the designed distributed controller can stabilize a perturbed power system even in the existence of 1s communication delay. Similarly, comparisons between decentralized controller and the well-known multi-band power system stabilizer (MB-PSS) controller shows that decentralized controller can reduce the stabilization time by 80% when the delay is known and by 60% if the delay is unknown with respect to the MB-PSS. It is evident that the robust controller owes this success to the designed novel time delay compensation technique. Moreover, the simulation results with respect to uncertainty in sensor measurements show that the robust controller is resilient up to 10% deviation. Whereas, the measurement uncertainty affect the stabilization performance of the PFL controller significantly.

In addition, the designed MAC protocol is tested in a home area network (HAN) which hosts large numbers of nodes with various applications. Simulation results demonstrate that an 80% MAC efficiency is maintained for up to 100 nodes while the efficiency of standardized HomePlug MAC protocol, for example, reduces down to 10%. Similarly, an 80% reduction in channel access delay is achieved by the adaptive MAC protocol with respect to the HomePlug MAC protocol. It is asserted that tailoring the adaptive MAC protocol for other communication networks such as neighborhood area network (NAN) and wide area networks (WAN) can reduce the channel access delay and improve data throughput.