Abstract:
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.
Abstract:
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.
Abstract:
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 acquisitor 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-swam 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.
Abstract:
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.