Stochastic multi-period optimal dispatch of energy storage in unbalanced distribution feeders

TL;DR

This paper introduces a convex, multi-period optimal power flow framework that robustly manages energy storage and demand resources in unbalanced distribution feeders with high solar PV uncertainty, ensuring reliable operation.

Contribution

It presents a novel, convex, AC-feasible robust OPF formulation that accounts for nonlinear power flow constraints and forecast uncertainties in a multi-period setting.

Findings

Effective dispatch of energy storage under PV forecast uncertainty

Ensures system feasibility and reliability with high PV penetration

Receding-horizon implementation demonstrates practical effectiveness

Abstract

This paper presents a convex, multi-period, AC-feasible Optimal Power Flow (OPF) framework that robustly dispatches flexible demand-side resources in unbalanced distribution feeders against uncertainty in very-short timescale solar Photo-Voltaic (PV) forecasts. This is valuable for power systems with significant behind-the-meter solar PV generation as their operation is affected by uncertainty from forecasts of demand and solar PV generation. The aim of this work is then to ensure the feasibility and reliability of distribution system operation under high solar PV penetration. We develop and present a novel, robust OPF formulation that accounts for both the nonlinear power flow constraints and the uncertainty in forecasts. This is achieved by linearizing an optimal trajectory and using first-order methods to systematically tighten voltage bounds. Case studies on a realistic distribution feeder shows the effectiveness of a receding-horizon implementation.