State Grid Corporation of China

State Grid Tianjin Electric Power Company

Electric Power Science & Research Institute of State Grid Tianjin Electric Power Company

Jikeng Lin

Xudong Wang

Tao Liu

Yi Ding

Shiqian Ma

Yan Qi

Guodong Li

Tianchun Xiang

Gaomeng Wang

Guangyu Wu

Jian Zhuang

Provided are a method and a device for identifying a distribution network topology error. The method includes: calculating a voltage of a coupling node to which each load belongs and obtaining a voltage sample space of coupling nodes to which all loads belong; calculating a current of a branch to which each load belongs and obtaining a current sample space of branches to which all loads belong; calculating a voltage correlation coefficient and a current correlation coefficient respectively between different loads according to the obtained voltage sample space and the current sample space; and completing verification and correction of the distribution network topology.

Method and device for identifying distribution network topology error

The present invention discloses an extremum seeking-based control method for maximum output tracking of a wind turbine generator, mainly comprising three steps of first closed-loop feedback, second closed-loop feedback, and third closed-loop feedback. The method for resisting mechanical fatigue of a double-fed variable speed constant frequency wind turbine generator by controlling mechanical torque while capturing maximum wind energy provided in the present invention is applied to a double-fed variable speed constant frequency wind turbine system by improving the control based on sliding mode extremum seeking with the following effects that, with regard to the maximum wind energy tracking effect, the rotating speed can be quickly adjusted to keep the tip speed ratio &#x3bb; as its optimum value after the wind speed changes, so that the wind energy utilization coefficient is restored to the maximum value.

Extremum seeking-based control method for maximum output tracking of a wind turbine generator

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Shanghai, China

Jikeng Lin