Kabushiki Kaisha Toshiba

Tadahiro Yanagisawa

Teruyuki Ishizuki

Kiyoshi Kusunoki

Takahisa Kageyama

Yuichi Shiozaki

Kazuteru Ono

In one embodiment, a control system of a variable speed pumped storage hydropower system includes an optimization processing unit configured to calculate a flow rate adjusting valve opening demand value and a first command value, a speed control unit configured to generate a secondary current active power component command value of a secondary excitation device based on the first command value, a mechanical (pump-turbine) output compensation unit configured to calculate a compensation value of the opening of the flow rate adjusting valve and/or a compensation value of the generator-motor output, and an output control unit configured to generate a flow rate adjusting valve opening command value based on the generator-motor output command value, the flow rate adjusting valve opening demand value, the compensation value calculated by the mechanical output compensation unit, and the output detection value of the generator-motor.

Control system of variable speed pumped storage hydropower system and method of controlling the same

A variable velocity apparatus includes a wound-rotor induction machine having a primary winding connected to a power system having a power system frequency, a secondary winding excited by an alternating current (AC), a generator-motor shaft, and a load united with the generator-motor shaft. The apparatus includes a frequency detection element for detecting a change in the power system frequency, and a controller for changing a rotational speed of the induction machine based on the detected change in the power system frequency. The change in the rotational speed is made substantially equivalent to the detected change in the power system frequency, so as to maintain a slip frequency of the induction machine essentially constant when the power system frequency changes.

Variable speed induction generator-motor with controllable excitation

A simulator includes a modelling simulate section in which properties of an apparatus to be controlled are modelled. In addition, this simulator includes a neural network in which learning is performed depending on a real control quantity for the apparatus to be controlled. A correction value relative to a simulation control quantity for the modeling simulate section is calculated in the neural network based on a process quantity output from a controlling unit. Thereafter, the simulation control quantity is corrected depending on the calculated correction value. In practice, learning is performed in the neural network by changing a synapse load based on a real quantity for the apparatus to be controlled. As a result of the foregoing correction, the simulator can simulate the real apparatus more accurately.

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Tokyo, Japan

Tadahiro Yanagisawa