Load Capability for Smart Distribution Systems

The load capability problem has traditionally been associated with long-term system planning, but as distribution networks become increasingly strained, load capability is becoming a daily challenge for grid operators. In a smart grid environment, operators can measure system states remotely and in real-time, which would allow real-time load capability assessment if desired. Utilities could benefit from smarter measurement schemes, in which data collection frequencies adapt to thecondition of the circuit. This thesis presents the implicit temporal load capability formulation, which, given circuit parameters and a load forecast, identifies times when the system would benefit from closer measurement monitoring. In addition to the new formulation, this thesis presents an updated version of general load capability, which includes new equations to compute load capability with respect to power factor limits, clarifies the units of the problem, and introduces time as a solution parameter. Corresponding solution algorithms are proposed and implemented in a MATLAB-based software package that solves both problems. Simulation results were obtained on 21- and 105-bus distribution networks. One set of simulations solved general load capability for the 105-bus system with respect to both positive and negative load variations. These simulations successfully demonstrate efficient computation of currentand power factor-limited load variation factors as a part of the updated general formulation. A second set of simulations solved implicit temporal load capability for both circuits with a given load forecast,and various loading conditions and control settings. These simulations efficiently identify critical times and lull periods in a load forecast, where utilities may benefit from modified data collection schemes.