Integration of cloud computing and real time simulation systems for validating energy management solutions

This paper presents a Cloud-in-the-Loop (CIL) architecture that integrates cloud computing services with real-time simulation and Hardware-in-the-Loop (HIL) technologies to support the development, testing and validation of advanced energy management solutions for microgrids and energy communities. Developed within the Horizon Europe DEDALUS project, the proposed framework addresses the need for reliable validation environments capable of assessing cloud-based control strategies before their deployment in real-world energy systems. By bridging digital and physical infrastructures, the architecture enables realistic and interoperable testing of distributed energy management applications. The proposed architecture combines four complementary layers: real-time simulation, cloud computing services, communication infrastructure and external data sources. A detailed HIL model of an energy community—including photovoltaic generation, battery energy storage systems and residential loads—is connected to cloud-hosted optimisation algorithms through MQTT-based communications. The framework supports the integration of real operational data, weather information and energy market signals, while maintaining a clear separation between data acquisition and physical system modelling. This flexible design enables the validation of cloud-based Energy Management Systems (EMS) under realistic operating conditions without modifying the underlying simulation model. The architecture is validated through an experimental case study involving the optimisation of battery operation within a residential energy community. Results demonstrate that the proposed CIL framework enables simultaneous assessment of high-level energy management strategies and low-level electrical behaviour, including transient responses, inverter performance and power quality. By providing a safe environment for testing optimisation algorithms, communication reliability and fault scenarios, the proposed approach offers a scalable validation platform for future digital twins, cloud-based energy services and resilient smart grid applications.