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PV Monitoring System for a Water Pumping Scheme with a Lithium-Ion Battery Using Free Open-Source Software and IoT Technologies

Author

Listed:
  • Francisco José Gimeno-Sales

    (Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València, 46022 Valencia, Spain)

  • Salvador Orts-Grau

    (Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València, 46022 Valencia, Spain)

  • Alejandro Escribá-Aparisi

    (Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València, 46022 Valencia, Spain)

  • Pablo González-Altozano

    (Departamento de Ingeniería Rural y Agroalimentaria (DIRA), Universitat Politècnica de València, 46022 Valencia, Spain)

  • Ibán Balbastre-Peralta

    (Departamento de Ingeniería Rural y Agroalimentaria (DIRA), Universitat Politècnica de València, 46022 Valencia, Spain)

  • Camilo Itzame Martínez-Márquez

    (Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València, 46022 Valencia, Spain)

  • María Gasque

    (Departamento de Física Aplicada, Universitat Politècnica de València, 46022 Valencia, Spain)

  • Salvador Seguí-Chilet

    (Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València, 46022 Valencia, Spain)

Abstract

The development of photovoltaic (PV) technology is now a reality. The inclusion of lithium-ion batteries in grid-connected PV systems is growing, and the sharp drop in prices for these batteries will enable their use in applications such as PV water pumping schemes (PVWPS). A technical solution for the monitoring and tracking of PV systems is shown in this work, and a novel quasi-real-time monitoring system for a PVWPS with a Li-ion battery is proposed in which open-source Internet of Things (IoT) tools are used. The purpose of the monitoring system is to provide a useful tool for the operation, management, and development of these facilities. The experimental facility used to test the monitoring system includes a 2.4 kW pk photovoltaic field, a 3.6 kVA hybrid inverter, a 3.3 kWh/3 kW lithium-ion battery, a 2.2 kVA variable speed driver, and a 1.5 kW submersible pump. To address this study, data acquisition is performed using commercial hardware solutions that communicate using a Modbus-RTU protocol over an RS485 bus and open software. A Raspberry Pi is used in the data gateway stage, including a PM2 free open-source process manager to increase the robustness and reliability of the monitoring system. Data storage is performed in a server using InfluxDB for open-source database storage and Grafana as open-source data visualization software. Data processing is complemented with a configurable data exporter program that enables users to select and copy the data stored in InfluxDB. Excel or .csv files can be created that include the desired variables with a defined time interval and with the desired data granularity. Finally, the initial results of the monitoring system are presented, and the possible uses of the acquired data and potential users of the system are identified and described.

Suggested Citation

  • Francisco José Gimeno-Sales & Salvador Orts-Grau & Alejandro Escribá-Aparisi & Pablo González-Altozano & Ibán Balbastre-Peralta & Camilo Itzame Martínez-Márquez & María Gasque & Salvador Seguí-Chilet, 2020. "PV Monitoring System for a Water Pumping Scheme with a Lithium-Ion Battery Using Free Open-Source Software and IoT Technologies," Sustainability, MDPI, vol. 12(24), pages 1-28, December.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:24:p:10651-:d:465294
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    References listed on IDEAS

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    Cited by:

    1. José María Portalo & Isaías González & Antonio José Calderón, 2021. "Monitoring System for Tracking a PV Generator in an Experimental Smart Microgrid: An Open-Source Solution," Sustainability, MDPI, vol. 13(15), pages 1-23, July.
    2. Dalibor Dobrilovic & Jasmina Pekez & Eleonora Desnica & Ljiljana Radovanovic & Ivan Palinkas & Milica Mazalica & Luka Djordjević & Sinisa Mihajlovic, 2023. "Data Acquisition for Estimating Energy-Efficient Solar-Powered Sensor Node Performance for Usage in Industrial IoT," Sustainability, MDPI, vol. 15(9), pages 1-22, April.
    3. Sajjad Miran & Muhammad Tamoor & Tayybah Kiren & Faakhar Raza & Muhammad Imtiaz Hussain & Jun-Tae Kim, 2022. "Optimization of Standalone Photovoltaic Drip Irrigation System: A Simulation Study," Sustainability, MDPI, vol. 14(14), pages 1-20, July.

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