Fault Diagnosis for Photovoltaic Systems: A Validated Industrial SCADA Framework

The growing integration of photovoltaic (PV) systems in modern energy infrastruc-tures calls for advanced and application-specific monitoring tools. This article intro-duces a comprehensive method for operational monitoring of PV installations using Supervisory Control and Data Acquisition (SCADA) s...

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Autores: Snytko , Anastasiia, Jiménez-Castillo, Gabino, Muñoz Rodríguez , Francisco José, Catalina Rus Casas , Catalina
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Universidad de Jaén
Repositorio:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
OAI Identifier:oai:ruja.ujaen.es:10953/6403
Acceso en línea:https://doi.org/10.3390/app152312656
https://www.mdpi.com/2076-3417/15/23/12656
https://hdl.handle.net/10953/6403
Access Level:acceso abierto
Palabra clave:SCADA
Photovoltaic Monitoring
Energy Management
Self-Consumption
Performance Indicators
Energy&Fuel
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spelling Fault Diagnosis for Photovoltaic Systems: A Validated Industrial SCADA FrameworkSnytko , AnastasiiaJiménez-Castillo, GabinoMuñoz Rodríguez , Francisco JoséCatalina Rus Casas , CatalinaSCADAPhotovoltaic MonitoringEnergy ManagementSelf-ConsumptionPerformance IndicatorsEnergy&FuelThe growing integration of photovoltaic (PV) systems in modern energy infrastruc-tures calls for advanced and application-specific monitoring tools. This article intro-duces a comprehensive method for operational monitoring of PV installations using Supervisory Control and Data Acquisition (SCADA) systems. It presents both stand-ard and innovative performance indicators designed to improve energy management in self-consumption and grid-connected configurations. To address limitations in cur-rent standards such as IEC 61724-1, a new set of parameters is proposed. These include the self-consumption ratio (SCR), self-sufficiency ratio (SSR), and dedicated perfor-mance ratios for self-consumption (PR_SC) and grid export (PR_TG). Together, these metrics provide a clearer understanding of system efficiency and energy flow. The ar-ticle explores the use of WinCC Unified, a modern SCADA platform developed by Siemens, to implement these indicators. WinCC Unified offers advanced tools for re-al-time visualization, cloud and edge connectivity, historical data management, and user-friendly interface design. Its open architecture supports the integration of custom KPIs and analytics, enabling the creation of dynamic and informative dashboards. By leveraging digital tools like WinCC Unified, the proposed approach contributes to the development of intelligent, standardized monitoring solutions for PV systems, aligned with the evolving demands of smart grids and distributed generation. SCADA dash-board, designed in this work, offers more than just an attractive interface – it delivers real operational value. It brings together 21 key performance indicators along with the current date and time in a single, streamlined display, updated every 0.1 seconds for near-instant data visibility, which allows operators to instantly assess overall system health at a glance. This intuitive layout not only simplifies daily monitoring but also speeds up anomaly detection and response times, supporting quicker interventions and improving overall system reliability through complete real-time awareness.The authors would like to thank the program which finances projects aimed at ecological and digital transition (Grant No. TED2021-131137B-IO0: “Contribution to the Ecological Transition of the Industrial Sector through Photovoltaic Self-consumption”). The authors also acknowledge the support provided by the Thematic Net-work 723RT0150 “Red para la integración a gran escala de energías renovables en sistemas eléctricos (RIBIERSE-CYTED)” financed by the call for Thematic Networks of the CYTED (Ibero-American Program of Science and Technology for Development) for 2022.MDPI202520252025info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.3390/app152312656https://www.mdpi.com/2076-3417/15/23/12656https://hdl.handle.net/10953/6403reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaéninstname:Universidad de JaénInglésApplied SciencesAttribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:ruja.ujaen.es:10953/64032026-06-24T12:41:07Z
dc.title.none.fl_str_mv Fault Diagnosis for Photovoltaic Systems: A Validated Industrial SCADA Framework
title Fault Diagnosis for Photovoltaic Systems: A Validated Industrial SCADA Framework
spellingShingle Fault Diagnosis for Photovoltaic Systems: A Validated Industrial SCADA Framework
Snytko , Anastasiia
SCADA
Photovoltaic Monitoring
Energy Management
Self-Consumption
Performance Indicators
Energy&Fuel
title_short Fault Diagnosis for Photovoltaic Systems: A Validated Industrial SCADA Framework
title_full Fault Diagnosis for Photovoltaic Systems: A Validated Industrial SCADA Framework
title_fullStr Fault Diagnosis for Photovoltaic Systems: A Validated Industrial SCADA Framework
title_full_unstemmed Fault Diagnosis for Photovoltaic Systems: A Validated Industrial SCADA Framework
title_sort Fault Diagnosis for Photovoltaic Systems: A Validated Industrial SCADA Framework
dc.creator.none.fl_str_mv Snytko , Anastasiia
Jiménez-Castillo, Gabino
Muñoz Rodríguez , Francisco José
Catalina Rus Casas , Catalina
author Snytko , Anastasiia
author_facet Snytko , Anastasiia
Jiménez-Castillo, Gabino
Muñoz Rodríguez , Francisco José
Catalina Rus Casas , Catalina
author_role author
author2 Jiménez-Castillo, Gabino
Muñoz Rodríguez , Francisco José
Catalina Rus Casas , Catalina
author2_role author
author
author
dc.subject.none.fl_str_mv SCADA

Photovoltaic Monitoring
Energy Management

Self-Consumption

Performance Indicators
Energy&Fuel
topic SCADA
Photovoltaic Monitoring
Energy Management
Self-Consumption
Performance Indicators
Energy&Fuel
description The growing integration of photovoltaic (PV) systems in modern energy infrastruc-tures calls for advanced and application-specific monitoring tools. This article intro-duces a comprehensive method for operational monitoring of PV installations using Supervisory Control and Data Acquisition (SCADA) systems. It presents both stand-ard and innovative performance indicators designed to improve energy management in self-consumption and grid-connected configurations. To address limitations in cur-rent standards such as IEC 61724-1, a new set of parameters is proposed. These include the self-consumption ratio (SCR), self-sufficiency ratio (SSR), and dedicated perfor-mance ratios for self-consumption (PR_SC) and grid export (PR_TG). Together, these metrics provide a clearer understanding of system efficiency and energy flow. The ar-ticle explores the use of WinCC Unified, a modern SCADA platform developed by Siemens, to implement these indicators. WinCC Unified offers advanced tools for re-al-time visualization, cloud and edge connectivity, historical data management, and user-friendly interface design. Its open architecture supports the integration of custom KPIs and analytics, enabling the creation of dynamic and informative dashboards. By leveraging digital tools like WinCC Unified, the proposed approach contributes to the development of intelligent, standardized monitoring solutions for PV systems, aligned with the evolving demands of smart grids and distributed generation. SCADA dash-board, designed in this work, offers more than just an attractive interface – it delivers real operational value. It brings together 21 key performance indicators along with the current date and time in a single, streamlined display, updated every 0.1 seconds for near-instant data visibility, which allows operators to instantly assess overall system health at a glance. This intuitive layout not only simplifies daily monitoring but also speeds up anomaly detection and response times, supporting quicker interventions and improving overall system reliability through complete real-time awareness.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.3390/app152312656
https://www.mdpi.com/2076-3417/15/23/12656
https://hdl.handle.net/10953/6403
url https://doi.org/10.3390/app152312656
https://www.mdpi.com/2076-3417/15/23/12656
https://hdl.handle.net/10953/6403
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Applied Sciences
dc.rights.none.fl_str_mv Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
instname:Universidad de Jaén
instname_str Universidad de Jaén
reponame_str RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
collection RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
repository.name.fl_str_mv
repository.mail.fl_str_mv
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