A New Generation of PV Monitoring System with High-Grade Remote Diagnostics Based on Module Level Monitoring and Integrated Yield Simulation

Behrens, G.; Yılmaz, Serkan; Maydell, Karsten von; Tapia, Miguel Angel Partida; Peters, Dorothee; Kirstein, U.; Feser, C.; Kruse, I.; Kilper, T.

doi:10.4229/eupvsec20152015-5bo.12.4

Cited by 3 publications

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An embedded microcontroller unit for PV module monitoring and fault detection

Borza

Kaplani

2019

2019 8th International Conference on Renewable Energy Research and Applications (ICRERA)

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This paper presents the architectural layout and functional design details of a microcontroller embedded electronic monitoring system (e-EMS). According to the design, this unit is integrated into the PV module junction box. It can be scaled up to form part of a complex PV power plant control system. The communication topology follows a 3-tier structure. It uses two processors, one dedicated for data acquisition and the other for communication purposes. The e-EMS provides a complete set of data associated to PV module performance characteristic parameters, including current and voltage of the PV module and each sub-string of cells, operation of the bypass diodes along with the corresponding current and voltage measurements, PV temperature and environmental parameters. The sampling rate can be programmed in a large range from 1 to 65s along with the number of samples used for averaging signal values. The power output is determined every hour, as a basic output of the system. Comparison of the determined values with the expected ones when normalized to the PV operating conditions provides reliable information on deviation trends, the degree of degradation that the PV module experiences, while the analysis of the sampled data may identify the cells or modules which experience degradation and disclose types of factors which affect their operation.

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An embedded microcontroller unit for PV module monitoring and fault detection

Borza

Kaplani

2019

2019 8th International Conference on Renewable Energy Research and Applications (ICRERA)

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Cloud-Based Platform for Photovoltaic Assets Diagnosis and Maintenance

Livera

Tziolis

Franquelo³

et al. 2022

Energies

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A cloud-based platform for reducing photovoltaic (PV) operation and maintenance (O&M) costs and improving lifetime performance is proposed in this paper. The platform incorporates a decision support system (DSS) engine and data-driven functionalities for data cleansing, PV system modeling, early fault diagnosis and provision of O&M recommendations. It can ensure optimum performance by monitoring in real time the operating state of PV assets, detecting faults at early stages and suggesting field mitigation actions based on energy loss analysis and incidents criticality evaluation. The developed platform was benchmarked using historical data from a test PV power plant installed in the Mediterranean region. The obtained results showed the effectiveness of the incorporated functionalities for data cleansing and system modeling as well as the platform’s capability for automated PV asset diagnosis and maintenance by providing recommendations for resolving the detected underperformance issues. Based on the DSS recommendations, approximately 7% of lost energy production could be recovered by performing field mitigation activities (e.g., corrective actions).

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