Real-time optimal scheduling of smart power distribution systems using integrated receding horizon control and convex conic programming

In this paper, we propose a convex Optimal Power Flow (OPF) formulation integrated within Receding Horizon Control (RHC) method using Second Order Conic Programming (SOCP). The main advantages of the proposed method are a) global optimal scheduling with faster computation time b) dynamic equation models with real-time control c) integration of uncertain resources and measurements. The effectiveness of this method is evaluated using a 32 bus power distribution test system, considering various network constraints that include market interaction, energy storage dynamics and uncertain model of wind generation. The efficiency of the proposed method compared to RHC AC Optimal Power Flow (RHC-ACOPF) architecture is also evaluated. The results show that the proposed architecture outperforms the RHC-ACOPF in computation time and guaranties the global optimal solution. Also the proposed method provides effective usage of energy storage system as the RHC integration allows including dynamic modeling of energy storage within the optimization algorithm.

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