The continuous improvement of solar thermal technologies is essential to meet the growing demand for sustainable heat generation and to support global decarbonization efforts.This study presents the design,implementat...The continuous improvement of solar thermal technologies is essential to meet the growing demand for sustainable heat generation and to support global decarbonization efforts.This study presents the design,implementation,and validation of a real-time monitoring framework based on the Internet ofThings(IoT)and cloud computing to enhance the thermal performance of evacuated tube solar water heaters(ETSWHs).A commercial system and a custom-built prototype were instrumented with Industry 4.0 technologies,including platinum resistance temperature detectors(PT100),solar irradiance and wind speed sensors,a programmable logic controller(PLC),a SCADAinterface,and a cloud-connected IoT gateway.Data were processed locally and transmitted to cloud storage for continuous analysis and visualization via amobile application.Experimental results demonstrated the prototype’s superior thermal energy storage capacity−47.4 vs.36.2 MJ for the commercial system,representing a 31%—achieved through the novel integration of Industry 4.0 architecture with an optimized collector design.This improvement is attributed to optimized geometric design parameters,including a reduced tilt angle,increased inter-tube spacing,and the incorporation of an aluminum reflective surface.These modifications collectively enhanced solar heat absorption and reduced optical losses.The framework effectively identified thermal stratification,monitored environmental effects on heat transfer,and enabled real-time system diagnostics.By integrating automation,IoT,and cloud computing,the proposed architecture establishes a scalable and replicable model for the intelligent management of solar thermal systems,facilitating predictive maintenance and future integration with artificial intelligence for performance forecasting.This work provides a practical,data-driven approach to digitizing and optimizing heat transfer systems,promoting more efficient and sustainable solar thermal energy applications.展开更多
基金funded by the National Council of Science,Technology,and Technological Innovation(CONCYTEC)the National Program of Scientific Research and Advanced Studies(PROCIENCIA)under the E041-2022-“Applied Research Projects”competition.Contract number:PE501078609-2022-PROCIENCIA.
文摘The continuous improvement of solar thermal technologies is essential to meet the growing demand for sustainable heat generation and to support global decarbonization efforts.This study presents the design,implementation,and validation of a real-time monitoring framework based on the Internet ofThings(IoT)and cloud computing to enhance the thermal performance of evacuated tube solar water heaters(ETSWHs).A commercial system and a custom-built prototype were instrumented with Industry 4.0 technologies,including platinum resistance temperature detectors(PT100),solar irradiance and wind speed sensors,a programmable logic controller(PLC),a SCADAinterface,and a cloud-connected IoT gateway.Data were processed locally and transmitted to cloud storage for continuous analysis and visualization via amobile application.Experimental results demonstrated the prototype’s superior thermal energy storage capacity−47.4 vs.36.2 MJ for the commercial system,representing a 31%—achieved through the novel integration of Industry 4.0 architecture with an optimized collector design.This improvement is attributed to optimized geometric design parameters,including a reduced tilt angle,increased inter-tube spacing,and the incorporation of an aluminum reflective surface.These modifications collectively enhanced solar heat absorption and reduced optical losses.The framework effectively identified thermal stratification,monitored environmental effects on heat transfer,and enabled real-time system diagnostics.By integrating automation,IoT,and cloud computing,the proposed architecture establishes a scalable and replicable model for the intelligent management of solar thermal systems,facilitating predictive maintenance and future integration with artificial intelligence for performance forecasting.This work provides a practical,data-driven approach to digitizing and optimizing heat transfer systems,promoting more efficient and sustainable solar thermal energy applications.
