Optimal power flow with storage integration -

Abstract

This research considers the optimal power flow (OPF) problem in a power system with storage integration. The classical problem formulation requires minimizing the cost of conventional generation by taking into consideration the different time periods over which the renewable generation output varies in addition to the physical and technical constraints of the network. However, the uncertainty associated with the renewable power production forecast is substantial; it can be modeled by an interval set. Affinely adjustable robust optimization is therefore proposed to account for uncertainties in the OPF formulation. The base-point generation is calculated to serve the load when the renewable power production is at its forecasted value, and the participation factors control the generators to ensure a feasible solution for all instances of renewable power output in the predefined uncertainty set. The affinely adjustable robust problem is formulated as a convex quadratic program and tested on standard IEEE networks having 14 and 118 nodes that consider uncertainties over a 24-hour study horizon.