DEEP LEARNING-BASED APPROACH FOR SOLVING OPTIMAL POWER FLOW PROBLEMS WITH FLEXIBLE TOPOLOGY

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United States of America

APP PUB NO 20250015593A1
SERIAL NO

18346923

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Abstract

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A method for solving multiple OPF equations of an AC electrical power system with plural topologies and admittances is provided. The method includes determining a continuous admittance space to embed the plural topologies, determining a plurality of voltage magnitudes and a plurality of voltage phase angles of the plurality of buses by a deep neural network, and reconstructing an active power generation and a reactive power generation using power flow equations according to the plurality of voltage magnitudes, the plurality of voltage phase angles, and the load inputs. The continuous admittance space is an admittance matrix of a plurality of line admittances each having a default admittance computed using a conductance and a susceptance of the plurality of branches. The deep neural network receives the load inputs and the plurality of line admittances as inputs.

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Patent Owner(s)

Patent OwnerAddress
CITY UNIVERSITY OF HONG KONG518057 NO 8 YUEXING 1ST ROAD SOUTH DISTRICT HIGH TECH ZONE NANSHAN DISTRICT SHENZHEN CITY GUANGDONG PROVINCE SHENZHEN CITY GUANGDONG PROVINCE 518057

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
CHEN, Minghua Hong Kong, CN 77 1826
ZHOU, Min Hong Kong, CN 195 1814

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