Adaptive HVDC supplementary damping controller based on reinforcement learning

An adaptive supplementary damping controller of HVDC is presented based on reinforce-ment learning algorithm,which is mainly composed of neuro-fuzzy network using reinforcement signal to train the parameters of controller. Contrary to conventional fuzzy controller,the reinforcement signal,transformed from the output performance index of power system by the adaptive heuristic assessment algorithm,is fed back to the controller to update the key parameters, which effectively reduces the dependence of damping controller on accurate mathematical model. Simulation results show that this supplementary controller efficiently damps the power oscillation among areas,improves system stability,and has better robustness in various operation modes than the conventional supple-mentary damping controller.