Current methods for configuring adjustable capacity transformers have several limitations. These include that the consideration of influencing factors is limited, the integration of comprehensive cost analysis is insufficient, and the assessment based on distribution transformer area operation and control results is absent. To address these issues, a configuration evaluation method for adjustable capacity transformers is proposed, which integrates operational control and economic performance. First, a power flow model is built using second-order cone programming. Based on the optimized operation of the distribution area, typical daily net load data are obtained to support capacity selection of adjustable capacity transformers. Then, key factors affecting configuration decisions are analyzed, and a comprehensive cost evaluation index is developed. Case studies using historical load data are conducted under both photovoltaic (PV) and non-PV scenarios. The effectiveness and advantages of the proposed method are demonstrated by comparing different planning periods and capacity margins with traditional configurations.