Middleware platforms are key technology in any Internet of Things (IoT) system, considering their role in managing the intermediary communications between devices and applications. In the energy sector, it has been shown that IoT devices enable the integration of all network assets to one large distributed system. This comes with significant benefits, such as improving energy efficiency, boosting the generation of renewable energy, reducing maintenance costs and increasing comfort. Various existing IoT middlware solutions encounter several problems that limit their performance, such as vendor locks. Hence, this paper presents a literature review and an expert survey on IoT middleware platforms in energy systems, in order to provide a set of tools and functionalities to be supported by any future efficient, flexible and interoperable IoT middleware considering the market needs. The analysis of the results shows that experts currently use the IoT middleware mainly to deploy services such as visualization, monitoring and benchmarking of energy consumption, and energy optimization is considered as a future application to target. Likewise, non-functional requirements, such as security and privacy, play vital roles in the IoT platforms’ performances.

The integration of volatile, decentralized energy into building energy systems requires intelligent algorithms that are capable of controlling the augmented complexity and the interactions of subsystems efficiently. Not only do the algorithms require computing capacity, but also a feasible information and communication infrastructure. One possibility to provide computing power on demand is cloud computing that forms together with an extended connectivity of physical devices the Internet of Things (IoT). We present a customizable open-source IoT platform setup using FIWARE. For the integration of existing building automation networks, we extend an OpenMUC gateway with BACnet functionality and connect it to our platform via MQTT. We successfully demonstrate the overall setup with a web-based visualization of high resolution energy monitoring and a control loop as basic requirements for the integration of more advanced control algorithms in future building energy management systems. We find our setup generally feasible for both use cases and, hence, will aim for the integration of more advanced control algorithms in the future using the presented platform components.