With the power grid getting greener and smarter by the day, a slew of new challenges arise to overcome. Distributed sources of energy like solar panels and batteries are being added to the grid right from the household level. While they are desirable for reducing our need for traditional sources of energy, the addition of these resources has been shown to cause issues in the quality of the power grid. This is particularly observed at the low-voltage domestic part of the grid where the resources cause issues with the voltage quality. The distribution grid is unbalanced by nature and adding these resources only amplifies this problem. To help mitigate voltage quality issues grid operators are starting to require voltage regulation capabilities from resources to be connected to the grid and a lot of work has been conducted to find the optimal strategies for operating these resources. However, existing paradigms for these sources only focus on fixing the voltage magnitude part of the power quality and neglect phasor relationships. This thesis aims to bridge this gap by developing a method to determine the optimal operation of these resources by using the voltage regulation capability to address both voltage magnitude and voltage unbalance issues in addition to optimal operation.

The integration of distributed generators (DGs) into the distribution grid has exacerbated voltage unbalance issues leading to greater risks of reducing equipment lifetime, equipment damages, and increased ohmic losses. Most approaches to regulating voltage in distribution systems only focus on voltage magnitude and neglect phasor discrepancies and do little to remedy voltage unbalance. To combat this, a novel Optimal Power Flow (OPF) is designed to help operate these resources in a manner that curtails voltage unbalance using the reactive power compensation capabilities of inverters. The OPF was run for a wide variety of loading conditions on a pair of systems using MATLAB and was shown to improve the voltage profile of the system in addition to minimizing losses in most cases. However, it is noted that the OPF loses exactness in highly stressed conditions and is unable to provide meaningful solutions

Master of Science