Hierarchical Decentralized Control for Enhanced Stability of Large-Scale Power Systems
Due to the ever-increasing penetration of distributed generation units connected to the power distribution system, electric power systems, worldwide, are undergoing a paradigm shift with regards to system monitoring, operation and control. We envision that with the emergence of
active' distribution systems consisting of prosumers' and localized energy markets, decentralized control methods in power systems are gaining a growing attention among power researchers. Traditionally, two main types of control schemes have been implemented in power systems: (a) wide-area monitoring based centralized control, and (b) local measurement based primary (machine) level control. By contrast, decentralized control schemes based on local monitoring and control of strategically-determined subsystems (or `areas') of a large-scale power system are not used. The latter control schemes offer several advantages over the former, which include more flexibility, simplicity, economy and scalability for large-scale systems. In this dissertation, we summarize our research work on hierarchical and decentralized control techniques for the enhancement in a unified manner of voltage and rotor angle stability in large-scale power systems subject to large (e.g., short circuits) and small (e.g., small load changes) disturbances. We study system robustness by calculating local stability margins. We derive decentralized control laws that guaranty global asymptotic stability by applying Lyapunov's second method for interconnected systems. Furthermore, we argue that the current centralized control structure must only play a supervisory control role at a higher (tertiary) hierarchical level by processing the decisions taken by the regional control entities regarding the stability/instability of the system. This ensures system-wide situational awareness while minimizing the communication bandwidth requirements. We also develop a multi-agent based framework for this hierarchical control scheme. Finally, we compare different communication protocols using simulation models and propose an efficient communication network design for decentralized control schemes. This work, in principle, motivates the development of fast stability analysis which, in the future, may also account for the non-linear coupling that exist between machine rotor angles and bus voltages in power system models. As a future work, we propose the use of statistical techniques like random-effects regression and saddlepoint approximation method to reliably estimate the type-I and type-II probability errors in the proposed hierarchical, decentralized control decision process.