Hierarchical Power Systems Control

Power quality is necessary for electrical systems to operate in their intended manner without any deterioration of performance. This book highlights the new emerging challenges of power quality due to the penetration of large-scale renewable energy generation technologies, the advances in nonlinear loads, the increased electricity demands in the deregulated market, and the recent requirements of smart grids that need better hierarchical design with enhanced quality, improved controllability, higher reliability, and security.

This book brings together emerging objectives and paradigms in the control of both AC and DC microgrids; further, it facilitates the integration of renewable-energy and distribution systems through localization of generation, storage and consumption. The control objectives in a microgrid are addressed through the hierarchical control structure.

This book introduces several novel contributions into the current literature. Firstly, given that microgrid topologies are paramount in theoretical analysis, the author has proposed a rigorous method of computing the network’s admittance matrix and developed to facilitate the stability analysis of DC microgrids supplying nonlinear loads. This unique approach enabled the factorisation of the admittance matrix in a particular way that facilitates a rigorous theoretical analysis for deriving the stability conditions.

Microgrids have emerged as a promising solution for accommodating the integration of renewable energy resources. But the intermittency of renewable generation is posing challenges such as voltage/frequency fluctuations, and grid stability issues in grid-connected modes. Model predictive control (MPC) is a method for controlling a process while satisfying a set of constraints. It has been in use for chemical plants and in oil refineries since the 1980s, but in recent years has been deployed for power systems and electronics as well.