An optimization model proposal to achieve the PV inverter distribution solution and use based on the new column generation algorithm and constraints to solve the proposed two-stage inverter optimal distribution model based on the second-order cone programming

Optimally dispatching Photovoltaic (PV) inverters is an efficient way to avoid overvoltage in active distribution networks, which may occur in the case of PV generation surplus load demand. Typically, the dispatching optimization objective is to identify critical PV inverters that have the most significant impact on the network voltage level. Following, it ensures the optimal set-points of both active power and reactive power for the selected inverters, guaranteeing the entire system operating constraints (e.g., the network voltage magnitude) within reasonable ranges. However, the intermittent nature of solar PV energy may affect the selection of the critical PV inverters and also the final optimal objective value. In order to address this issue, a two-stage robust centralized-optimal dispatch model is proposed in this paper to achieve a robust PV inverter dispatch solution considering the PV output uncertainties. In addition, the conic relaxation-based branch flow formulation and the column-and constraint generation (CCG) algorithm are employed to deal with the proposed robust optimization model. Case studies on a ۳۳-bus distribution network and comparisons with the deterministic optimization approach have demonstrated the effectiveness of the proposed method.

Keywords:

Two-stage robust optimization , column-and-constraint generation algorithm , network , Photovoltaic generation.