Volumetric receivers made of metallic wire meshes are a promising technology that allows different designs and configurations. In this paper the local volumetric heat transfer coefficient for a volumetric absorber with two extreme arrangements, inline and stagger, is presented. The results show that the heat transfer rates for the stagger stack is nearly two times higher than the inline stack. Moreover, the local volumetric heat transfer coefficient is implemented in a Homogeneous Equivalent Model using a Local Thermal Non-Equilibrium model to compare the results. The stagger stack performs better than the inline stack despite their higher frontal losses and pressure drop. Finally, a validation of the Homogeneous Equivalent Model is carried out with experimental data showing a good agreement.

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.