Synopsis of Phasor Monitoring Applications for Wide Area Control and Protection

The phenomenon of voltage collapse in electric power systems has received a considerable amount of attention in the last decade. Although the occurrences of the voltage blackouts have decreased in the recent years, the problem of voltage stability still poses a considerable threat to the security and the reliability of modern electricity grids. The ultimate objective of this thesis is to further investigate and expand upon the existing body of knowledge on the voltage collapse phenomenon and develop protection and control schemes for mitigating such undesirable events in modern electric grids. In doing so, the research done in this thesis work builds on an earlier work done in the area of Voltage Instability Prediction (VIP). Although proven to be a successful metric in determining the proximity of large nonlinear systems to a potential voltage instability event, much remains to be explored in the area of Voltage Instability Prediction. In particular the issues of estimating the static stability margins, the locational dependence of accuracy of such VIP derived margins, the exploitation of redundant local measurements and a compelling argument in favor of combining/fusing the individual VIP margins into a single system-wide measure of voltage collapse margin form the main focus of investigation of this work. To lower the individual entropy of the VIP derived margins, a data fusion algorithm built on the foundations of Dempster-Shafer’s evidential reasoning method is proposed. The research is concluded on a positive note with the final results further pushing the envelope of knowledge in the field of voltage stability studies in power systems

A Probabilistic Modeling Framework for Integration of Distributed Energy Resources

The emergence of distributed energy resources has led to new challenges in the operation and planning of power networks. Of particular significance is the introduction of a new layer of complexity that manifests in the form of new uncertainties that could severely limit the resiliency and reliability of modern power networks. Some of the new uncertainties that emerge as a direct consequence of the integration of distributed energy resources include generation uncertainties typical of solar and wind power, uncertain consumer demand patterns due to the increasing adoption of un-conventional loads such as Plug-in Hybrid Electric Vehicles, topological uncertainties that include outages of one or many components of a power system. To facilitate the widespread adoption of distributed energy resources, it is thus essential to develop robust methodologies that would adequately capture and quantify the uncertainties associated with using them. Such decision-making problems that involve uncertainties embedded in the input data naturally lend themselves to be addressed by statistical decision-theoretic methods. A natural advantage of using statistical decision theory in addressing power system uncertainties is using sample information to make inferences about the unknown quantities. Thus, using computational methods like Bayesian statistics and Markov Chain Monte Carlo is natural within the context of decision-making under uncertainty in energy systems. This research proposes the use of computational methods such as scenario generation techniques, probabilistic mixture models, Bayesian analysis, and Markov Chain Monte Carlo to model the complex stochastic processes such as solar generation, power system load, and various topological uncertainties like accelerated aging and the premature failing of components such as On-load Tap Changers and switched capacitor banks. Furthermore, this research work is also concerned with investigating the impact of modern reactive power compensation in the form of a solid-state-based capacitor-less power quality compensator to further the integration of distributed resources, particularly distributed roof-top solar generation in low voltage distribution networks. To that end, a stochastic cost-benefit equation is developed, considering the uncertainties associated with distributed energy resources. The cost-benefit study investigates the economic viability of deploying such power electronics-based reactive power compensation devices in low-voltage distribution networks