Implementation and Characterization of a High-Precision Monitoring System for Photovoltaic Power Plants Using Self-Made Phasor Measurement Units
Implementación y caracterización de un sistema de monitoreo de alta precisión para plantas fotovoltaicas utilizando unidades de medición fasorial (PMU) de fabricación propia

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Author
Arenas Ramos, Victoria
Pallarés López, Víctor
Real Calvo, Rafael Jesús
González Redondo, Miguel Jesús
Santiago Chiquero, Isabel
Publisher
IEEEDate
2025Subject
Edge-computingIEEE C37.118-2011
Photovoltaic (PV) plants
Real-time monitoring
Synchrophasor sensors
Time sensitive networking (TSN)
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The increasing integration of photovoltaic (PV) plants into the power grid presents an ongoing challenge to prevent the instability caused by atmospheric conditions from affecting the power distribution network. To adequately control the network and implement such techniques, monitoring has been considerably improved in recent years. Due to the vast number of measurements generated, efficient management of this data has become a significant challenge. This article outlines a procedure used for simultaneously storing synchronized measured data from phasor measurement units (PMUs) and PMU-like data from acquisition data acquisition (DAQ) devices through self-made extended-PMUs (ePMUs). Throughout this article, a communication and storage environment that complies with the IEEE C37.118.2 standard for Synchrophasor Data Transfer for Power Systems will be characterized based on criteria established in the IEC 61850-90-5 standard for power utility automation. In addition, it justifies the chosen storage method through a comprehensive study of data volume and reading accessibility. The procedure and the ePMUs have been experimentally validated in field tests in two grid-connected PV plants. The procedure was proven to be valid for quasi-real-time applications for data registered and sent both in a local area network (LAN) and a wide area network (WAN). Thanks to the dataframes synchronize up to the millisecond, data can also be studied offline seamlessly.
