MESSE – Model-based Engineering and Validation Support for Cyber-Physical Energy Systems
The massive deployment of distributed generators from renewable sources in recent years has led to a fundamental paradigm change in terms of planning and operation of the electric power system. MESSE develops of a concept for a model-based engineering and validation support system, covering the overall engineering process for smart grid applications – from use case design to validation and deployment.
Motivation and problems: The rollout of smart grid solutions has already started and new methods are deployed to the power system today. At the same time the massive deployment of distributed generators from renewable sources in recent years has led to a fundamental paradigm change in terms of planning and operation of the electric power system. Automation and control systems, using advanced information and communication technology, are key elements to handle these new challenges. The electric energy system is moving from a single system to a system of systems. The implementation and deployment of these complex systems of systems are associated with increasing engineering complexity resulting also in increased total life-cycle costs. However, with the usage of proper methods, automation architectures, and corresponding tools there is a huge optimization potential for the overall engineering process. Until now such a method has been missing.
Goals and approaches: MESSE addresses these shortcomings with the development of a concept for a model-based engineering and validation support system, covering the overall engineering process for smart grid applications – from use case design to validation and deployment. Based on a model-driven development approach, the methodology consists of three main parts: specification and use case design, automated engineering and validation, and deployment. Furthermore, accompanying the engineering and validation approach, a cognitive learning of the user design experience is used to additionally increase the overall efficiency.
Expected results: The main expected result is a formal approach for the specification, automatic generation and deployment of target code and configurations for smart grid applications (e.g., control, communication, SCADA), improving the overall engineering process of cyber-physical energy systems. This approach will be combined with an automatic testing and validation methodology for smart grid applications, in order to improve the general quality and mitigate the current risk of developing smart grid applications. Furthermore a concept and basis for a cognitive learning system for user design experience will be developed.
The developed automated model-driven engineering and validation framework will be validated for selected smart grid applications and use cases in a laboratory environment. This validation will reveal the main benefits of this highly innovative approach which is expected to drastically reduce the engineering and validation complexity, error rate and effort and at the same time increase the rapidness and scalability of current engineering methods.
