Modern SCADA for CSP Systems Based on OPC UA, Wi-Fi Mesh Networks, and Open-Source Software

This study presents a methodology for the development of modern Supervisory Control and Data Acquisition (SCADA) systems aimed at improving the operation and management of concentrated solar power (CSP) plants, leveraging the tools provided by industrial digitization. This approach is exemplified by its application to the CESA-I central tower heliostat field at the Plataforma Solar de Almería (PSA), one of the oldest CSP facilities in the world. The goal was to upgrade the control and monitoring capabilities of the heliostat field by integrating modern technologies such as OPC (Open Platform Communications)) Unified Architecture (UA), a Wi-Fi mesh communication network, and a custom Python-based gateway for interfacing with legacy MODBUS systems. Performance tests demonstrated stable, scalable communication, efficient real-time control, and seamless integration of new developments (smart heliostat) into the existing infrastructure. The SCADA system also introduced a user-friendly Python-based interface developed with PySide6, significantly enhancing operational efficiency and reducing task complexity for system operators. The results show that this low-cost methodology based on open-source software provides a flexible and robust SCADA architecture, suitable for future CSP applications, with potential for further optimization through the incorporation of artificial intelligence (AI) and machine learning.

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Publication Details

Journal
Energies
Published
2024-12-13
DOI
https://doi.org/10.3390/en17246284
Citations
4
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.41

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article

Modern SCADA for CSP Systems Based on OPC UA, Wi-Fi Mesh Networks, and Open-Source Software

Javier Bonilla, Jesús Fernández‐Reche, Antonio L. Ávila-Marín, Jose A. Carballo et al.
4 citations
Energies
Photovoltaic System Optimization Techniques
0.41
article

Modern SCADA for CSP Systems Based on OPC UA, Wi-Fi Mesh Networks, and Open-Source Software

Javier Bonilla, Jesús Fernández‐Reche, Antonio L. Ávila-Marín, Jose A. Carballo, Blas Díaz
article en
4 citations

Abstract

This study presents a methodology for the development of modern Supervisory Control and Data Acquisition (SCADA) systems aimed at improving the operation and management of concentrated solar power (CSP) plants, leveraging the tools provided by industrial digitization. This approach is exemplified by its application to the CESA-I central tower heliostat field at the Plataforma Solar de Almería (PSA), one of the oldest CSP facilities in the world. The goal was to upgrade the control and monitoring capabilities of the heliostat field by integrating modern technologies such as OPC (Open Platform Communications)) Unified Architecture (UA), a Wi-Fi mesh communication network, and a custom Python-based gateway for interfacing with legacy MODBUS systems. Performance tests demonstrated stable, scalable communication, efficient real-time control, and seamless integration of new developments (smart heliostat) into the existing infrastructure. The SCADA system also introduced a user-friendly Python-based interface developed with PySide6, significantly enhancing operational efficiency and reducing task complexity for system operators. The results show that this low-cost methodology based on open-source software provides a flexible and robust SCADA architecture, suitable for future CSP applications, with potential for further optimization through the incorporation of artificial intelligence (AI) and machine learning.

EnergiesVol. 17(24)
Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (ES), University of Almería (ES)
Ministerio de Ciencia e Innovación, HORIZON EUROPE Framework Programme
Industry, innovation and infrastructure
Openalex Percentile: Top 46%
Photovoltaic System Optimization Techniques
0.41
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Modern SCADA for CSP Systems Based on OPC UA, Wi-Fi Mesh Networks, and Open-Source Software — Javier Bonilla, Jesús Fernández‐Reche, et al. · Energies (2024) | TGRS Research Map | TGRS