Addressing the challenges of topological design and the limitations of global optimization for large-scale photovoltaic (PV) plants in complex terrains, this paper proposes a topology optimization method based on mixed-integer linear programming (MILP). The innovation of the proposed method lies in its use of a MILP framework to integrate complex terrain modeling, quantification of construction difficulty, and coordinated configuration of conductor cross-sections into a single equivalent annual cost optimization model. First, equivalent mathematical models tailored to diverse environmental features—including flat, mountainous, and hilly terrains—are developed to enable accurate spatial identification. Second, aimed at minimizing the total equivalent annual cost (EAC), a MILP model is formulated. This model comprehensively incorporates physical construction difficulties and strict electrical constraints, such as active power flow balance, cable current-carrying capacity, and node voltage deviations. A high-performance solver is then utilized to achieve global optimization for radial topologies. Furthermore, the cross-sectional areas of the conductors are dynamically configured to compensate for power quality losses caused by path detours. Case studies demonstrate that the proposed method significantly reduces the EAC and enhances the overall economic benefits of PV plants while ensuring strict electrical safety across various complex environments.
Ye et al. (Thu,) studied this question.