Synergistic Day-Ahead Scheduling Framework for Smart Distribution Grid Under Uncertainty

Under the smart grid environment, implementation of load management programs, integration of active elements, and associated uncertainties have increased the complexity in operation and management of the existing distribution networks many folds as before. Therefore, for optimal operation of such a complicated distribution network, this article proposes a synergistic day-ahead scheduling scheme emphasizing the combined impact of network reconfiguration, active elements, and demand response. Minimizing the overall cost associated with the operation and management of distribution system, the formulation is proposed as a mixed-integer second-order cone programming problem. This formulation captures the exact characteristics of power flow in network and ensures its fast convergence to global optima. Further, the Benders decomposition method is employed to deal with computational complexities in achieving a solution. Test results on a modified IEEE 33-bus network show notable enhancement in the techno-economic performance of the network.