Optimal Reconfiguration for Active Distribution Networks Incorporating a Phase Demand Balancing Model
Long Fu, Wei Wang, Zhao Yang Dong, Yaran Li
Abstract
Optimally reconfiguring an active distribution network (ADN) during power outages has been regarded as a reasonable approach to facilitate system secure operation and reliability. Nevertheless, most existing studies for the reconfiguration virtually focus on taking actions from the generationand network-side, in which the potential achievement from the demand-side is underestimated. Moreover, the phase-unbalance and voltage violation in ADNs should be restricted to avoid extreme conditions of distributed generators (DGs) that jeopardize system reliability. To bridge the gap, a new approach to reconfigure ADNs under multiple faults is proposed in this paper, incorporating a phase demand balancing (PDB) model to improve dispatch performance. The model regulates asymmetrical loads to mitigate the phase-unbalance issue from the demand-side, cooptimized with step voltage regulators (SVRs) and DG dispatching to enhance reliability and flexibility in reconfiguring ADNs. The derived optimization is a challenging mixed-integer nonconvex programming (MINCP), which is reformulated as an efficiently solvable mixed-integer second-order cone programming (MISOCP) via exact equivalence and accurate approximation techniques. Case studies based on modified IEEE benchmark systems validate the effectiveness and advantages of the proposed method.