Northeastern University

Other

Huaguang Zhang

Qiuye Sun

Zhenwei Liu

Tieyan Zhang

Xiangping Meng

Qingqi Zhao

Jianguo Zhou

Jun Yang

Dazhong Ma

Yan Zhao

Xinrui Liu

Jing Guo

Zhiliang Wang

Fei Teng

Bonan Huang

Gang Wang

Jian Feng

Dongsheng Yang

Guotao Hui

Yingchun Wang

Yanhong Luo

Zhanshan Wang

Bin Jiang

Jinhai Liu

Rui Wang

Junsheng Liang

Jingwei Hu

Zhenning Wu

Xiaoyu Li

Lei Chen

Heng Du

Jie Bai

Lianzhi Wang

Zhiqiang He

Xintong Li

Feiye Wu

Zhenao Sun

Yushuai Li

Jin Cui

The invention provides an electric grid state estimation system and method based on a boundary fusion. The system includes an electric grid data acquisition module, a communication module including a local data unit and a state estimation unit, and a data fusion module, wherein the state estimation unit includes a memory storing a state estimation program and a display displaying a program running and outputting a state variable; the state estimation program is performed to realize an electric grid state estimation; the estimation method includes the following steps of dividing a regional electric grid, then establishing a measurement equation for each region, solving an internal quantity and a boundary quantity, fusing the boundary quantities of two regions, correcting the boundary quantity, performing a non-linear transformation on the intermediate variable, solving the estimated values of the state variable by the least square method, and performing outputting.

Electric grid state estimation system and method based on boundary fusion

The invention provides a reactive power optimization system and a method of a power grid based on a double-fish-swarm algorithm. The system includes a power grid state data acquiring module, a reactive power regulating module and a reactive power executing module. The power grid state data acquiring module includes a power grid state data acquiring processor and a relay transmitter. The reactive power regulating module is a control terminal. The reactive power executing module includes generator terminal voltage regulators, transformer tap regulators and reactive power compensation regulators. The method is used for acquiring the initial data to be optimized in the current network; and optimizing the initial data to be optimized in the current network based on a double-fish-swarm algorithm so as to obtain optimal value of control variables in the power grid. According to the method, the distribution network to be optimized can realize reasonable reactive power flow distribution.

Reactive power optimization system and method of power grid based on the double-fish-swarm algorithm

The present invention relates to an intelligent adaptive system and method for monitoring leakage of oil pipeline networks based on big data. The present invention effectively analyzes a large amount of data collected on site within a reasonable time period and obtains a state of a pipeline network by an intelligent adaptive method, thereby obtaining a topological structure of a pipeline network. The present invention specifically adopts a flow balance method in combination with information conformance theory to analyze whether the pipeline network has leakage; small amount of leakage and slow leakage can be perfectly and accurately alarmed upon detection; as a generalized regression neural network is adopted to locate a leakage of the pipeline network, an accuracy of a result is increased. Therefore, the present invention adopts a policy and intelligent adaptive method based on big data to solve problems of detecting and locating leakage of the pipeline network.

Intelligent adaptive system and method for monitoring leakage of oil pipeline networks based on big data

The present invention relates to an energy resource-grid-load automatic control system of smart microgrid and control methods thereof, which belong to the field of microgrid control and electrical technology. The energy resource-grid-load automatic control system includes a distributed renewable energy power generation module, a distributed renewable energy inverter module, a conventional power generation module, a user load module, a bidirectional grid-connected control module, a distributed renewable energy intelligent optimizing power generation control module, an energy storage module, an intelligent energy storage unit adjuster and a storage battery pack. Compared with the conventional microgrid including a distributed renewable energy power generation system, the present invention guarantees the stability and the high energy utilization of the power generation system and effectively solves the problem of non-uniform frequency of use of storage batteries to unify the service life of the storage battery pack.

Energy resource-grid-load automatic control system of smart microgrid and control methods thereof

The present invention relates to an energy router for an energy internet, which comprises a three-phase three-level bi-directional rectifying unit, a six-phase interleaved DC/DC bi-directional conversion unit, a self-excitation soft start push-pull full-bridge DC/DC bi-directional conversion unit, a three-phase resonant soft switching bi-directional inversion unit, a single-phase full-bridge bi-directional inversion unit, a high-voltage DC bus and a low-voltage DC bus. The three-phase three-level bi-directional rectifying unit, the six-phase interleaved DC/DC bi-directional conversion unit, the self-excitation soft start push-pull full-bridge DC/DC bi-directional conversion unit, the three-phase resonant soft switching bi-directional inversion unit and the single-phase full-bridge bi-directional inversion unit each have three energy flow operating modes: a forward conduction, a reverse conduction and a non-conduction. According to the energy flow operating mode of each unit, different operating modes of the energy router for the energy internet are formed.

Energy router for energy internet

Disclosed is a transformer control device and method based on a three-dimensional zone diagram policy. The method includes: setting transformers, including a transformer A and a transformer B; collecting three-phase voltage data and three-phase current data in a power system; rectifying the collected three-phase voltage data and the three-phase current data; transferring the data to the latches in a time-transfer method; transferring the data to an A/D converter of a processor to convert analog signals to digital signals; constructing a three-dimensional zone diagram in the processor; determining transformer operating conditions according to positions of points formed by voltage, reactive power factor and substation load; and adjusting the transformers. This invention adopts a simple, easy and clear three-parameter control policy including voltage, power factors and substation loads, so as to simplify analysis of transformer operating conditions, realize optimal substation operation, reduce transformer loss, and increase economic benefits.

Transformer control device and method based on three-dimensional zone diagram policy

An automatic three-phase unbalanced load compensation experimental device includes an automatic compensation device, a load simulation part, and detection, display and control parts. The automatic compensation device includes power capacitors and intelligent grouping compound switches. The detection, display and control part includes a plurality of current transformers, molded case circuit breakers, a three-phase digital display ammeter, a three-phase electric power monitoring instrument, a protocol conversion module, RS-485 buses, Ethernet cables and an upper computer. The load simulation part includes phase A, B and C loads which are in star connection and are same in component and circuit connection, an analog output module and a relay output module. A power monitoring instrument and digital ammeter are connected to the grid by circuit breaker and the plurality of current transformers. The automatic compensation device and load simulation part are connected to the grid in parallel.

Automatic three-phase unbalanced load compensation experimental device and its control method

Growing community of inventors

Shenyang, China

Qiuye Sun