Print Email Facebook Twitter Photovoltaic system monitoring and fault detection using peer systems Title Photovoltaic system monitoring and fault detection using peer systems Author Alcañiz Moya, A. (TU Delft Photovoltaic Materials and Devices) Nikam, Maitheli M. (Student TU Delft) Snow, Yitzi (Solar Monkey) Isabella, O. (TU Delft Photovoltaic Materials and Devices) Ziar, H. (TU Delft Photovoltaic Materials and Devices) Date 2022 Abstract Monitoring residential scale photovoltaic (PV) systems is important for maximizing the energy yield and detecting malfunctions. Analytical-based approaches are not reliable in these systems because of the lack of on-site measurements and detailed PV system specifications. In this paper, a collaborative approach is proposed which does not depend on weather data but on similar PV systems. Based on the so-called performance-to-peer approach, the aim of this work is to improve this baseline model by adding PV systems characteristics and by optimizing with machine learning techniques. The methodology has been tested in a fleet of more than 12,000 PV systems located in the Netherlands with up to 7 years of data per system. The proposed model achieves an average (Formula presented.) of 94.1% and a NRMSE of 0.05, outperforming in terms of (Formula presented.) the baseline model by 1.4 points, and the analytical approach by 3.8. The data requirements of this model are not high: With 1,700 years of PV system data with daily resolution, the maximum performance can be achieved as long as a minimum of 6 months of data per system and 100 PV systems are considered. The application of this model for fault detection and categorization has also been shown. The proposed approach has shown its strengths with respect to other methods through its ability of distinguishing between system mismatch and actual fault and of adapting to new situations via retraining. Subject fault detectiongenetic algorithmmonitoringpeer-to-peerphotovoltaics To reference this document use: http://resolver.tudelft.nl/uuid:db876237-bff8-4504-ae14-8fc8d482bdf8 DOI https://doi.org/10.1002/pip.3558 ISSN 1062-7995 Source Progress in Photovoltaics: research and applications, 30 (9), 1072-1086 Part of collection Institutional Repository Document type journal article Rights © 2022 A. Alcañiz Moya, Maitheli M. Nikam, Yitzi Snow, O. Isabella, H. Ziar Files PDF Progress_in_Photovoltaics ... ystems.pdf 4.33 MB Close viewer /islandora/object/uuid:db876237-bff8-4504-ae14-8fc8d482bdf8/datastream/OBJ/view