Neuro-SVC Controller Based on Energy Function for Damping Enhancement of Power System

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  • エネルギー関数に基づいたニュー口SVC制御系による電力系統のダンピング向上

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Control equipment such as automatic voltage regulator, speed governor, and power system stabilizer is designed for a linearized model of a power system around a given operating condition. Because of nonlinearity of the power system, its control performance deteriorates when the operating condition of the power system changes widely. In order to solve such a problem, many studies have been reported on application of new control methods such as H∞, control, fuzzy control, neuro-control, etc. to generator control and SVC control.<br> In this paper, energy function-based neuro-control system (ENCS) is proposed. Furthermore, ENCS is applied to SVC control in order to verify its control performance. Numerical results and discussions based on Equalarea method make it clear that it is hard to determine what kinds of observed variables and how much values of parameters in adaptive neuro-control system (ANCS) the authors proposed before should be chosen. This is because the relation between the objective function of ANCS and the damping of the power system oscillation is not clear. As the objective function of ENCS is closely related with the damping enhancement, on the other hand, ENCS can be easily designed and suppress the oscillation effectively. Moreover, it is shown that plural operating conditions of the power system can be taken into account easily in the design of ENCS.

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