Grid Operation Enhancement via Network Topology Optimization With Sparse Tableau Formulation

초록

This study delves into network topology optimization (NTO) as a corrective switching mechanism, designed to effectively manage congestion within power system networks. Our proposed model employs an exact node-breaker representation of the network by utilizing sparse tableau formulation (STF), and incorporates a full set of network switching actions that include both bus and line switching. NTO is formulated with nonlinear AC power flow constraints, capturing the physical behavior and engineering limits of the network comprehensively. Solving the NTO problem that incorporates AC power flow constraints presents significant challenges. To tackle this computational issue, a modified STF representation has been introduced, which reduces both the number of variables and constraints and also eliminates the non-convexity inherent in power balance equations. This modification, which alters the geometry of the STF, reduces the computational complexity of the problem. The revised NTO model is subsequently tackled through an iterative algorithm. Our numerical results demonstrate the effectiveness of the proposed model in managing network congestion by reducing congestion/overloads in the branches, under both base case and contingency scenarios, through strategic bus/line switching actions. In particular, it shows that the proposed method has a better convergence rate compared to the existing STF-based method. Furthermore, the reconfigured network topologies proposed by our method result in fewer congested branches than those proposed by other exiting techniques examined in this study.

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