Method to accelerate the processing of multiperiod optimal power flow problems

Abstract

A method is disclosed for optimizing the power flow in an electric power network including a plurality of buses interconnected by transmission lines, and locally connected to loads, generators, and storage devices, the method executing an interior point optimisation algorithm in a computer system to solve an optimal control problem, which is defined over a time period of interest T, and is associated with an objective function representing the total fuel consumption of the generators for the time period of interest T, wherein the objective function depends on a plurality of parameters of the network, such as bus voltages, generator, and storage device powers. the parameters of the network allowed to vary over a large number N of predefined time intervals, each of duration δt, obtained by subdivisions of the time period of interest T and is subject to network constraints. The time and memory required to achieve the solution to the optimal control problem is drastically reduced over general purpose NLP methods, due to exploitation in the calculations involved in the Schur complement algorithm of the repetition of constant in time block matrices of charging and discharging ratios of the storage devices inside off diagonal blocks in a reorder KKT system.