Alternating-current transformer substation reactive voltage control method based on deep neural network
The invention discloses an AC transformer substation reactive voltage control method based on a deep neural network, and the method comprises the steps: obtaining the real-time SCADA measurement information of a power grid in a controlled region; according to the measurement information, judging whe...
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Main Authors | , , , , , , , , , , , , , , , |
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Format | Patent |
Language | Chinese English |
Published |
13.12.2022
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Subjects | |
Online Access | Get full text |
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Summary: | The invention discloses an AC transformer substation reactive voltage control method based on a deep neural network, and the method comprises the steps: obtaining the real-time SCADA measurement information of a power grid in a controlled region; according to the measurement information, judging whether the alternating-current transformer substation in the controlled area has a voltage power line crossing problem or not; if yes, determining all feasible control strategies according to the existing problems, inputting substation operation data in the measurement information as input values into a pre-constructed and trained deep neural network model corresponding to the feasible control strategies, and outputting AC substation bus voltage amplitudes corresponding to the feasible control strategies; determining AC transformer substation bus voltage and power factors corresponding to each feasible control strategy; and determining an optimal control strategy according to a safety evaluation result. The method ef |
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Bibliography: | Application Number: CN202211142634 |