Assessment of Functional Risks for Engineering Adaptive Smart Grid Applications

Established engineering procedures for developing smart grid applications adopt the Use-Case Methodology in combination with the Smart Grid Architecture Model (SGAM). This methodology has so far been adapted to include risk assessment for guaranteeing system security i.e. non-functional requirements. Recent work on engineering use cases that require specific adaptivity processes to make the system resilient against unexpected, rare events indicated the necessity to refine the established methodologies. In this paper, we propose an extension to the established engineering methodology that guides development teams to quantify such functional risks during requirements engineering phase. This enables inferring the suitable operating principles and system architectures for appropriate adaptive application designs. For demonstration, we consider the risks that arise from operating a virtual power plant under rare environmental conditions that are usually treated by manual trading activities. The methodology is validated in a case study for risk-aware balancing of renewable energy via flexible prosumers thereby reproducing the ad-hoc workflow used for particular flexibility use cases in earlier work. Altogether, we show how, at design time, the use of the proposed methodology supports the development of risk-aware adaptive systems.