Date of Award
Level of Access
Doctor of Philosophy (PhD)
Electrical and Computer Engineering
Mohamad T. Musavi
Second Committee Member
Third Committee Member
Additional Committee Members
In order to reduce the carbon footprint and the cost of electric energy, the owners of electric power utilities today are faced with the task of reducing the use of expensive and carbon intensive fossil fuels and significantly increasing the amount of energy from renewable sources in their grids while meeting an increase in electricity demand. To deal with increase in demand, electric utilities operate very close to their maximum capacities and this sometimes results in violating security limits. Therefore, the integration of intermittent renewable energy into the utility grids poses serious concerns that must be addressed to ensure grid stability.
In order to improve monitoring of their system, utilities are increasing the number of measurement devices in the system. However, not all collectible data contain important, necessary or unique information about the system, so storing and analyzing them comes at a considerable financial cost to the company. Therefore, identifying parts of the system whose measurements provide information that reflects the general state of the system would help utilities smartly utilize resources.
In this dissertation, a methodology for the identification of critical variables of power systems and their locations using eigenvalue analysis of the measurements of the system variables is developed. This analysis is based on principal component analysis (PCA). The effectiveness of monitoring critical locations of a power system in ensuring steady state system security is demonstrated.
Also, an artificial neural network-based state estimator that utilizes data from regular measurement units and phasor measurement units (PMUs) placed at the critical locations is developed. A technique called state estimation is used to estimate measured and unmeasured electrical quantities. Conventional state estimation techniques require availability of many measurements. The proposed state estimator utilizes fewer measurements, leading to a reduction in the number of expensive PMUs needed and reduction in the cost of electric grid operation. Thus, electric power utilities would be able to assess the state of their grid efficiently and improve their ability to integrate renewable energy without violating the grid’s security constraints.
Onwuachumba, Amamihe, "Identification of Critical Locations and Reduced Model State Estimation for Power System Analysis" (2016). Electronic Theses and Dissertations. 2503.