Optimizing Renewable Energy Using Scalable Solutions: IoT Integration in Renewable Energy Laboratories

This article presents one of the work results from the Cloud Energy Lab (CBEN) research project. The study explores how integrating Internet of Things (IoT) technology into laboratory devices enhances research efficiency, reduces equipment costs, and accelerates experimental processes without additional expenses. The project supports the development of scalable energy systems like electrical grids by enabling cloud-based data exchange between electrical resources, such as fuel cells and E-Drive test benches. It describes the project's IoT structure, showcasing test benches in different labs: a high-voltage battery simulator, an E-Drive test bench in the Electric Drives Lab, and a fuel cell test bench in the Vehicle Drives Lab. Data exchange between these test benches is facilitated by IoT technology, specifically OPC UA and MQTT, for cloud and inter-bench communication. Each test bench has defined interfaces, with equipment modeled as distinct components in MATLAB/Simulink software. This setup connects OPC UA server hardware via test benches or HTTP interfaces to the cloud for parameter setting and data capture, integrating models to form an automotive system for investigating electric and fuel-cell vehicles. Finally, the efficiency of various power scales between E-Drive and fuel cell test benches is evaluated. Key results show improved fuel cell design area, optimized energy flow, and significant cost savings through reduced equipment needs enabled by IoT and cloud technologies. These advancements contribute to the scalability of microgrids and simplify renewable energy integration without requiring co-located labs or large-scale power devices.

I. Introduction

The rapid advancement of IoT technologies has opened new avenues for enhancing research and development in laboratories, particularly engineering laboratories. Traditional laboratories often face high equipment costs, limited accessibility, and inefficient data management. Integrating IoT in laboratories offers a powerful solution for efficient data collection and access across diverse devices and test benches in multiple locations. This approach enhances the ability to manage and analyze data, facilitating more effective research and development processes and ensuring seamless integration of diverse systems. To achieve this, a common challenge is that different test benches often have varying power classes. This issue can be improved by combining cloud connectivity, storing data in a database, and ultimately exchanging data between laboratories using scalable energy. Consequently, research efficiency and effectiveness can be significantly enhanced without incurring additional costs.