Resiliency enhancement of distribution network with distributed scheduling algorithm

Improving the resiliency of power distribution networks (PDN) has garnered the need for reliable operating solutions, especially during natural disasters. This paper proposes a resiliency-based optimal power flow (R-OPF) problem to effectively schedule the critical loads and battery energy storage system (BESS) during an outage by partitioning BESS capacity. The proposed method aims to extend the longevity of higher priority critical loads by providing more flexibility for charging/discharging control of the BESS. To solve the R-OPF problem, this work adopts a distributed approach for making quick decisions. A novel mathematical framework is formulated that combines the proposed modified alternating direction method of multipliers (ADMM) and AA to solve the R-OPF problem in a distributed way. The proposed modified ADMM based distributed algorithm solves the R-OPF problem with a faster convergence rate than the traditional ADMM algorithm. Additionally, an affine arithmetic (AA) based approach incorporated in the proposed algorithm that effectively handles the uncertainties present in the system. The performance of the proposed methodology is tested on the IEEE 13 and IEEE 34 bus networks in the MATLAB environment. Numerical results on IEEE 13-bus network demonstrate that the modified ADMM algorithm converges faster than the traditional ADMM algorithm. Also, the number of simulations taken by the proposed AA-based method to handle the uncertainty is much less than standard methods such as the Monte Carlo Simulation (MCS) method. The quantity and longevity of serving higher priority critical loads are more with the proposed method.