Toward More Accurate and Robust Optimal Power Flow for Distribution Systems

TL;DR

This paper enhances the accuracy and robustness of optimal power flow in distribution systems by incorporating worst-case load and renewable generation forecasts, sensitivities, and detailed component models, validated through realistic simulations.

Contribution

It introduces a novel approach that accounts for load and renewable uncertainties using worst-case forecasts and sensitivities, improving OPF reliability in distribution systems.

Findings

Improved voltage regulation under uncertainty.

Validated approach on realistic distribution feeder.

Enhanced modeling of split-phase components and transformer losses.

Abstract

The objective of this paper is to improve the accuracy and robustness of optimal power flow (OPF) formulations for distribution systems modeled down to the low-voltage point of connection of individual buildings. An approach for addressing the uncertain switching behavior of building loads(e.g., air conditioners, water heaters, or pool pumps) and variable renewable generation (e.g., rooftop solar) in the OPF is proposed. Rather than using time-averaged forecasts to determine voltage magnitude constraints, we leverage worst-case minimum and maximum forecasts of loads and distributed energy resource generation. Sensitivities of the power flow equations are used to predict how these deviations in load and renewable generation will impact system voltages, and the voltage constraints in the OPF are dynamically adjusted to mitigate voltage violations due to this uncertainty. A methodology for incorporating models of split-phase components and transformer core losses in the OPF formulation is also proposed. The proposed approach is validated through numerical case studies on a realistic distribution feeder using GridLAB-D, a distribution system simulation software.