Work

Enhanced Swarm-Intelligence Optimization of Inverter Placement for Cable Cost Minimization in Standardized Photovoltaic Power Units

Year: 2025

Type: article

Abstract: This study addresses the problem of minimizing cable costs in Standardized Photovoltaic Power Units (SPPUs) by proposing an integrated inverter placement optimization framework. A high-precision economic model is first established to quantify the cost of both direct current (DC) and low-voltage alternating-current (LV-AC) cables as a function of inverter location. To improve solution accuracy and efficiency, an enhanced particle swarm optimization algorithm, termed the Adaptive Classification Method PSO (ACM-PSO), is developed, featuring population classification strategies as well as adaptive inertia weighting and neighborhood learning strategies. The optimization process incorporates hierarchical trench planning, dynamic combiner-unit partitioning, and multi-scheme layout generation, ensuring that both spatial and economic factors are systematically considered. A case study on Unit 19 of a 350 MW flat-ground PV plant in Xinjiang, China, demonstrates that the proposed method reduces total cable investment to CNY 292,945, achieving a cost saving of 2.3–3.8% compared with conventional layouts. These results confirm not only the methodological innovation of ACM-PSO for constrained nonlinear PV layout problems, but also its practical generalizability, offering a replicable and scalable design paradigm for large-scale PV plants.

Source: Energies

DOI: 10.3390/en18195111