Srikantha, PirathayiniLiu, Jingyuan2022-12-142022-12-142022-04-262022-12-14http://hdl.handle.net/10315/40599Power Distribution Networks (DNs) deliver electricity from the transmission systems to the consumers. The proliferation of diverse load components and distributed generators in active DNs is drastically changing the power demand and supply patterns in the DN, which in turn has led to significant stress and uncertainty on the voltage profiles of the DNs. Nevertheless, the communication and computation capabilities of the modern DNs have enabled cyber-enabled power components such as DG (Distributed Generator)}devices to make intelligent decisions through information exchanges. As such, in this dissertation we leverage on this novel capability to present algorithms for voltage monitoring, analysis and improvement that allow the system operator to assess the voltage profile of the DN and to take preventative actions for enhancing voltage profiles and preventing undervoltage/overvoltage incidents. In the subsequent chapters, we present performance guarantees and simulation studies on the proposed algorithms, and compare the algorithms introduced in this dissertation with the state-of-the-art.Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.Electrical engineeringEnergyElectronic Thesis or Dissertation2022-12-14Smart GridOptimizationGame theoryConvex relaxationMachine learning