A model-based framework for fault estimation and accommodation applied to distributed energy resources

This paper presents the development and approach of a model-based fault identification and accommodation framework applied to sampled-data controlled distributed energy resources subject to control actuator faults. The main objective of the proposed approach is to handle faults that degrade stability as well as performance, while remaining robust to false alarms. The proposed method allows for dual fault detection and estimation, through the use of an embedded system model that minimizes the residual between the estimated and sampled states at each sampling period by adjusting a fault parameter in the embedded model over a past horizon. The resulting fault parameter estimate is then used by the control system to find an optimal fault accommodation strategy by minimizing a predefined performance metric whilst ensuring closed-loop stability. The developed fault accommodation framework is then applied to a simulated model of a solid oxide fuel cell subject to both stability and performance degrading faults in the control actuators. A discussion of some of the practical implementation issues associated with the developed framework is also included.