Abstract

Since a pulsed power load (PPL) consumes a huge amount of energy within very short period of time, its deployment might cause large disturbances even instability to a power system that has limited generation, small inertia, and small ramp rate. To mitigate the strike during PPL deployment, energy storage system (ESS) is usually installed in shipboard power system (SPS) to serve as the sole power supply for PPL. To realise fast charging of the ESS and minimise disturbance during charging, generation control and charging control of SPS should be well coordinated. For this important but not well-studied problem, this study presents an adaptive critic design based control algorithm for a non-linear model integrating the basic dynamics of synchronous generator and supercapacitor, which is a popular type of ESS for PPL application. Through interactive learning of two neural networks for cost-to-go function approximation and optimal control approximation, respectively, near optimal control can be realised even under disturbance and model impreciseness. The algorithm is tested with both detailed single- and multiple-generator SPS models and tested through both real-time digital and power hardware-in-the-loop simulations. Simulation results demonstrate the effectiveness of the developed model and control algorithm.

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