State Grid Tianjin Electric Power Company

State Grid Corporation of China

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

Other

Wuhan University

Shiqian Ma

Yi Ding

Xianxu Huo

Xudong Wang

Guodong Li

Lei Wu

Tianchun Xiang

Yan Qi

Tianhao Wang

Yigang He

Tao Liu

Kai Wang

Jingjing Yan

Yun Liu

Xiaoyu Liu

Ke Xu

Lu Sun

Xuejun Shang

Jikeng Lin

Zihao Li

Bin Wu

Jiancheng Yu

Baoguo Zhao

Chenyang Zhao

Jian Zhuang

Qingshan Xu

Aidong Zeng

Gaomeng Wang

Jianfeng Wang

Jian Zhang

Honglei Zhao

Qingwu Gong

Zhishuang Wang

Ling Jiang

Chao Pang

A method for diagnosing transformer fault based on a deep coupled dense convolutional neural network, includes: obtaining datasets of dissolved gas in oil of a transformer in normal and fault states; expanding the datasets by using an adaptive synthetic oversampling method; performing, in a form of a two-dimensional matrix, feature reconstruction on characteristic gas dissolved in the oil; building a transformer fault diagnosis model based on a deep coupled dense convolutional neural network; and dividing an expanded dataset into a training set and a test set, and taking the two-dimensional matrix as an input of the deep coupled dense convolutional neural network and a set label as an output to train the network to obtain a fault diagnosis model. The present disclosure can resolve a problem that a fault diagnosis accuracy rate of the transformer is low due to insufficient and unbalanced fault samples in the dissolved gas in the oil.

Method for diagnosing transformer fault based on deep coupled dense convolutional neural network

Provided are a method for optimizing system energy efficiency and apparatus based on an integrated energy requirement, an electronic device, and a storage medium. The method includes, in response to a received target integrated energy requirement, constructing the energy efficiency optimization function of a target system according to an integrated energy requirement parameter, the operating parameter of the target system, and the environment loss parameter of the target system; constructing a constraint condition for optimizing the energy efficiency of the target system based on the balance relationship between energy supply and energy consumption and a device operating requirement for transmitting energy; and based on the energy efficiency optimization function and the constraint condition, using a target algorithm, using operating parameters of multiple devices in the target system as population individuals.

Method and apparatus for optimizing system energy efficiency based on an integrated energy requirement, electronic device, and storage medium

A method for making a spatio-temporal combined optimal scheduling strategy of a mobile energy storage (MES) system includes: inputting data of a power system, a traffic system, and an MES system; setting a time interval, and initializing a time interval counter; inputting real-time fault, traffic, and MES data; and performing rolling optimization and solving, and delivering regulation decision instructions of the MES system, till a fault is removed. The core of the present disclosure is to propose a spatio-temporal combined optimal model of the MES system to describe spatio-temporal coupling statuses of an energy storage vehicle, a traffic network, and a power distribution network. The present disclosure provides guidance for an optimal scheduling decision of the MES system by properly regulating a traveling path and charging and discharging power of the MES system, thereby supporting high-reliability operation of the power distribution network.

Method for making spatio-temporal combined optimal scheduling strategy of mobile energy storage (MES) system

A control method and system for a distribution network with distributed mobile energy storage systems is disclosed which relates to the power field. The present invention manages the multiple distributed mobile energy storage systems in the distribution network in a unified way, to improve the flexibility of the distribution network, and enable the distributed mobile energy storage systems to fully smooth new energy generation fluctuations, implement peak cut, facilitate grid auxiliary services, and improve the power quality. The control method includes: acquiring, by a sub-station coordination system, data of the distributed mobile energy storage systems; receiving, by a master-station dispatching system, the data of the distributed mobile energy storage systems, and obtaining external data; generating, by the master-station dispatching system, a control instruction; and controlling, by the sub-station coordination system, the distributed mobile energy storage systems. The control system includes the master-station dispatching system and the sub-station coordination systems.

Control method and system for distribution network with distributed mobile energy storage systems

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 invention relates to a method for real-time scheduling of multi-energy complementary micro-grids based on a Rollout algorithm, which is technically characterized by comprising the following steps of: Step 1, setting up a moving-horizon Markov decision process model for the real-time scheduling of the multi-energy complementary micro-grids with random new-energy outputs, and establishing constraint conditions for the real-time scheduling; Step 2, establishing a target function of the real-time scheduling; Step 3, dividing a single complete scheduling cycle into a plurality of scheduling intervals, and finding one basic feasible solution meeting the constraint conditions for the real-time scheduling based on a greedy algorithm; and Step 4, finding a solution to the moving-horizon Markov decision process model for the real-time scheduling of the multi-energy complementary micro-grids by using the Rollout algorithm based on the basic feasible solution from Step 3. With the consideration of the fluctuations in the new-energy outputs, the present invention solves the problems of low speed and low efficiency of a traditional algorithm at the same time, enabling high-speed efficient multi-energy complementary micro-grid real-time scheduling.

Method for real-time scheduling of multi-energy complementary micro-grids based on rollout algorithm

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Tianjin, China

Shiqian Ma