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

Meng Zhang, Jixuan Wei, Rong Tang, Qin Hu, Yang Wang, Li Chang, Xingcheng Gan and Ji Pei ()
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Meng Zhang: Power China Guiyang Engineering Corporation Limited, Guiyang 550081, China
Jixuan Wei: Power China Guiyang Engineering Corporation Limited, Guiyang 550081, China
Rong Tang: Power China Guiyang Engineering Corporation Limited, Guiyang 550081, China
Qin Hu: Power China Guiyang Engineering Corporation Limited, Guiyang 550081, China
Yang Wang: Power China Guiyang Engineering Corporation Limited, Guiyang 550081, China
Li Chang: Power China Guiyang Engineering Corporation Limited, Guiyang 550081, China
Xingcheng Gan: National Research Center of Pumps, Jiangsu University, Zhenjiang 212013, China
Ji Pei: National Research Center of Pumps, Jiangsu University, Zhenjiang 212013, China

Energies, 2025, vol. 18, issue 19, 1-14

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.

Keywords: Standardized Photovoltaic Power Unit; inverter placement optimization; Enhance Swarm Intelligence; cable cost minimization; combiner-unit partitioning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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