Novel intelligent fault-tolerant adaptive control methodology for next generation energy systems

In this paper, we propose a novel intelligent fault tolerant adaptive control methodology for next generation energy systems. This architecture augments local controllers connected to energy systems such as renewable energy based power generators based on a robust Fault Tolerant Control (FTC). This local controllers interacts with an area controller for the monitoring and control of energy systems. To this end, a Dual Heuristic Programming (DHP) action-critic neural network architecture coupled with a predictive identifier is designed. The main objective of the area controller is to interact with the local controller to exchange information about the grid status and augment local controller based on an optimal control strategy. The controller performance is tested on a wind generating system two area power grid to control reactive power management at the common point of coupling (CPP). Simulation studies indicate that the proposed architecture is capable of improving the stabilization of the power grid in the presence of renewable energy resources.