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All Journal International Journal of Electrical and Computer Engineering ASEAN Journal of Systems Engineering ELKHA : Jurnal Teknik Elektro Teknofisika Journal of Engineering and Technological Sciences JPSE (Journal of Physical Science and Engineering) Jurnal Ilmiah Universitas Batanghari Jambi Jurnal Bakti Saintek: Jurnal Pengabdian Masyarakat Bidang Sains dan Teknologi Journal of Appropriate Technology for Community Services International Journal Of Science, Technology & Management (IJSTM) Journal of Social Research
Mohammad Kholid Ridwan
Department Of Nuclear And Physics, Faculty Of Engineering Universitas Gadjah Mada, Yogyakarta, Yogyakarta 55281, Indonesia.
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Physics Social Sciences Transportation Other

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XAI Implementation for Inverter-Level Underperformance Analysis of the PV Power Plant from Actual Operational Data Saputra, Reza Adisetia; Suroso, Dwi Joko; Ridwan, Mohammad Kholid
ELKHA Vol. 18 No.1 April 2026
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v18i1.104850

Abstract

Photovoltaic (PV) power plants installed on uneven terrain often experience spatially non-uniform operating conditions that lead to performance disparities among inverters, which may not be detected through conventional system-level monitoring. This study presents an inverter-level performance analysis of the Nusa Penida PV power plant using one year of operational data with a 30-minute resolution. A data-driven framework integrating Extreme Gradient Boosting (XGBoost) classification and explainable artificial intelligence was developed to detect underperforming inverters and interpret the contributing factors affecting system performance. The analysis identified significant performance variations among the 18 inverters, with seven units categorized as underperforming based on a relative performance ratio threshold of 0.80 compared to the highest-performing inverter at the same timestamp. The proposed XGBoost classification model achieved an AUC of approximately 0.79 on the test dataset, indicating reliable discrimination between normal and underperforming inverter conditions. Further analysis shows that the detected underperformance corresponds to annual energy losses ranging from approximately 81,000 kWh to 119,000 kWh per inverter when compared with the best-performing reference unit. Explainable analysis using SHapley Additive exPlanations (SHAP) reveals that irradiance and temporal variables are the dominant contributors affecting inverter performance, while persistent negative feature contributions in several inverters indicate location-related constraints beyond natural environmental variability. These results demonstrate that inverter-level monitoring combined with interpretable machine learning provides deeper diagnostic insight than aggregated performance indicators and can support more effective identification of structural performance limitations in PV power plants installed on non-uniform terrain.
Co-Authors Abram Perdana Adyta Pradana Nurrachman Ahmad Agus Setiawan Ahmad Agus Setiawan Ahmad Agus Setiawan Anita Yuan Arif Darmawan Bakti Setiawan Bayu Ardiyanto Bertha Maya Sopha Boni Sena Budy Wiryawan Defi Rizkasari Dwi Joko Suroso Dyah R. Hizbaron Fachry Abda El Rahman Fadli Kasim Feikal Aprieza Fitri Yakub Hendra Budiono Putra Parapa Hizbaron, Dyah R. Junun Sartohadi M. Yayan Adi Putra Maria E. I. Shrestha Nelidya Md Yusoff Rachmawan Budiarto Ramadhan, Aska Resistentio Vembre Franika Robbani, Farisan Saputra, Reza Adisetia Sasongko Pramono Hadi Sheikh Ahmad Zaki Shrestha, Maria E. I. Subur Priyono Utami, Sentagi Sesotya Wahyu Wilopo Widiyanto, Syam Zulkifli Zulkifli