Method to accelerate the processing of multiperiod optimal power flow problems

A method for optimizing the power flow in an electric power network, said electric power network including a plurality of buses interconnected by transmission lines, and locally connected to loads, generators, and storage devices,

• the method executes an interior point optimisation algorithm in a computer system to solve an optimal control problem defined over a time period of interest T, where an objective function associated with said optimal control problem represents a total fuel consumption of the generators for said time period of interest T,
• said objective function depending on a plurality of parameters of said network, bus voltages, generator, and storage devices powers, said parameters of the network allowed to vary over a number N of predefined time intervals each of duration δt obtained by subdivisions of said time period of interest T, wherein said objective function is subject to constraints of said network, bus voltages, generator, and storage devices powers,
• characterized by the fact that said interior point algorithm includes the steps of:
• storing a KKT system associated with the optimality conditions for the Lagrangian associated with said objective function and said constraints defined for said time period T, the KKT system including a Hessian matrix H;
• reordering the KKT system to obtain a reordered KKT system where the Hessian matrix H after the reordering has an arrowhead structure with diagonal blocks An, and off diagonal blocks Bn comprising several identical copies of constant in time matrix B of charging and discharging ratios of said storages device which are:
• executing a direct Schur complement based factorisation and solution algorithm on said reordered KKT system;
• returning output parameters for said network, buses, loads, generators, and storages devices as a solution of said optimal control problem for each of said time intervals, wherein 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 said Schur complement algorithm of the repetition of constant in time block matrices B of charging and discharging ratios of the storage devices inside the off diagonal blocks Bn in the reorder KKT system.