Voltage control method and device, terminal equipment and storage medium
The embodiment of the invention discloses a voltage control method and device, terminal equipment and a storage medium. The method comprises the following steps: establishing a power distribution network voltage control model for cooperative voltage regulation of a distributed roof photovoltaic inve...
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| creator | HUANG HAOLIN WU ZHENHUANG CHEN XIXUN QUAN HUAN LIU YANG DU SHUZHUANG LIU HANYU CHEN GUANDAN ZHENG WANJIE HOU JIANWEI LIN MUQUN CUI MIAOMIAO PENG XIANGANG LIN LIXUAN HE JIE GAO JIE SU YUTIAN |
| description | The embodiment of the invention discloses a voltage control method and device, terminal equipment and a storage medium. The method comprises the following steps: establishing a power distribution network voltage control model for cooperative voltage regulation of a distributed roof photovoltaic inverter; establishing a distributed partially observable Markov decision model according to the power distribution network voltage control model; a graph convolutional neural network is embedded in a multi-agent actor-attention-commentator algorithm, and the multi-agent actor-attention-commentator algorithm is utilized to solve the Markov decision model so as to perform offline centralized training; and the online intelligent agent executes a real-time reactive power scheduling strategy in a distributed manner. State information and topological information in a power grid environment can be better captured; the optimal strategy is mined through a large number of samples in the off-line learning stage and stored in the |
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The method comprises the following steps: establishing a power distribution network voltage control model for cooperative voltage regulation of a distributed roof photovoltaic inverter; establishing a distributed partially observable Markov decision model according to the power distribution network voltage control model; a graph convolutional neural network is embedded in a multi-agent actor-attention-commentator algorithm, and the multi-agent actor-attention-commentator algorithm is utilized to solve the Markov decision model so as to perform offline centralized training; and the online intelligent agent executes a real-time reactive power scheduling strategy in a distributed manner. 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The method comprises the following steps: establishing a power distribution network voltage control model for cooperative voltage regulation of a distributed roof photovoltaic inverter; establishing a distributed partially observable Markov decision model according to the power distribution network voltage control model; a graph convolutional neural network is embedded in a multi-agent actor-attention-commentator algorithm, and the multi-agent actor-attention-commentator algorithm is utilized to solve the Markov decision model so as to perform offline centralized training; and the online intelligent agent executes a real-time reactive power scheduling strategy in a distributed manner. State information and topological information in a power grid environment can be better captured; the optimal strategy is mined through a large number of samples in the off-line learning stage and stored in the</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTINGELECTRIC POWER CONVERSION OR DISTRIBUTION OF ELECTRIC POWER ELECTRICITY GENERATION SYSTEMS FOR STORING ELECTRIC ENERGY |
| title | Voltage control method and device, terminal equipment and storage medium |
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