New auxiliary variable-based ADMM for nonconvex AC OPF

•Distributed computing of nonconvex AC OPF through consensus ADMM.•Developed a new information exchange scheme or new auxiliary variable to achieve better convergence.•The proposed scheme is compared with a scheme proposed in the literature and shows improvement in convergence.•The proposed ADMM algorithm is tested for power grids with sizes ranges from 30 buses to 1354 buses.•Robust performance is demonstrated for the partitioning algorithm based on graph spectral clustering. The main challenge in implementing alternating direction method of multipliers (ADMM) for nonconvex alternating current optimal power flow (AC OPF) is that ADMM method does not guarantee convergence for nonconvex problems. Using auxiliary variables for information exchange among subareas play a critical role in convergence improvement. This paper proposes a new auxiliary variable-based ADMM for nonconvex AC OPF. The proposed approach can improve convergence with less iterations compared with the existing method. The proposed ADMM algorithm is tested for power grids with sizes ranges from 30 buses to 1354 buses. Subareas are generated using spectral clustering based on a graph Laplacian representing network connectivity. The numerical results are compared with those based on the existing auxiliary variables-based method in the literature. Case studies demonstrate improvement in convergence due to the new auxiliary variables.