Self-Healing Control to improve reliability for the Smart Grid Distribution System

Abstract
A Smart Grid is a modernised future electric power network that uses various modern technologies, intelligence and approaches in order to provide sustainable, reliable and secure renewable and distributed energy resources. In the contrary, the emergence of time-variant and non-deterministic renewable and distributed energy resources are continuously causing new challenges to the Smart Grid across the world. Optimal control and efficient operation of renewable & distributed energy resources are one of the greatest challenges that are spontaneously leading the Smart Grid to an unstable state from its steady-state. Frequent and large instability results brown-out of the grid equipment which leads plant failure as well as power outage of the grid. Thus, the overall reliability of the power system reduces. Consequently, this thesis focuses on the factors that affect the reliability of the Smart Grid particularly its Distribution System. It has been identified through a literature research that voltage instability is one of the main reasons to brown-out of grid equipment and caused power outage hence reduced reliability of the grid. It has also been identified through research that voltage instability is the direct result of supply-demand unbalance. For example, Photovoltaic solar panel is historically at maximum power generation mode while demand of the system is below the average magnitudes. This results in surplus power to supply to the grid network and causes overvoltage. In addition to Photovoltaic, recently emerged Hybrid Electric Vehicle and small-scale Electric Energy Storage charge and discharge across the consumer terminals. These introduce additional supply-demand unbalances hence voltage instability due to State-of-Charge and Depth-of-Discharge of such distributed energy resources. Consequently, the control and operation of Smart Grid Distribution System are becoming critical day by day. This thesis, therefore, developed a Self-Healing Control Algorithm to improve reliability of a proposed Smart Grid Distribution System. Self-Healing Control is developed as a form of intelligent control technique by integrating modern robust control theory (i.e.: state-variable approach) together with various computer-based artificial intelligence approaches (i.e.: Genetic Algorithm and Bayesian Probability). The Self-Healing Control was implemented to a secondary distribution system in order to improve reliability for mitigating impact of integration of renewable and distributed energy resources focusing voltage instability due to supply-demand unbalance. Two experiments were carried out and results were presented by implementing Self-Healing Control Algorithm in chapter-5. It was also showed in chapter-5 that supply-demand balance was achieved while node voltages remain steady. The experiments and results were simulated and critically analysed in MATLAB Simulink and evaluated by identifying the contribution to knowledge for Ph.D.