Optimal Technology Selection Between String and Central Inverters for a 100 MW Solar PV Plant in Tehran Province Using AHP, TOPSIS, and VIKOR Methods

Document Type : Research Paper

Authors

Tehran Regional Electric Company, Tehran, Iran.

Abstract

This study focuses on the critical decision of selecting an optimal inverter technology for a 100 MW solar photovoltaic plant in Tehran province, Iran. Recognizing the complexity of this task, which involves multiple conflicting technical, economic, and qualitative criteria, the paper employs three well-established multi-criteria decision-making (MCDM) methods: The Analytical Hierarchy Process (AHP), the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. Two specific inverter models from Sungrow, the SG350HX string inverter and the SG8800UD-MV-20 central inverter, are evaluated against a comprehensive set of criteria, including efficiency, total cost of ownership, reliability, warranty, grid support features, compatibility, protection features, environmental condition tolerance, smart features, and brand reputation. The AHP method is utilized to determine the weights of these criteria. Subsequently, TOPSIS and VIKOR are applied to rank the inverter alternatives based on hypothetical performance data. The results from both TOPSIS and VIKOR analyses, under the assumed scenario, indicated a preference for the Sungrow SG8800UD-MV-20 central inverter. The study also emphasizes the importance of conducting thorough sensitivity analyses for AHP criteria weights, TOPSIS performance values, and the VIKOR compromise strategy parameter to ensure the robustness of the decision. Environmental conditions and grid connection requirements specific to Tehran province are also considered as vital factors in the selection process. The paper concludes by recommending further investigation of the central inverter, contingent on detailed real-world data and expert judgments, and suggests future research avenues, including the incorporation of more extensive data and additional MCDM techniques.

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References

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History

  • Receive Date: 22 September 2025
  • Revise Date: 06 November 2025
  • Accept Date: 10 November 2025

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