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 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:
An intelligent cooperative control system and method thereof. A parallel structure for low-voltage multi-module permanent magnet synchronous motor cooperative control units is adopted to realize control of low-voltage high power, control of low-speed large torque and system redundancy control; a double-parallel PWM rectifier circuit structure is used, when the system is in unbalanced power supply network environments; a resonant pole-type three-phase soft-switching inverter circuit is used as an inverter unit to improve utilization of DC bus voltage and to greatly reduce device switch losses at high frequencies; a current control and speed estimation unit is used, so that rotor speed and phase angle information is accurately estimated with low cost and high reliability; a controlled object is the multi-module permanent magnet synchronous motor, so that the problems of difficulties in motor installation, transportation and maintenance of a high-power electric drive system and the like are solved.
Abstract:
Provided is an intelligent inversion method for pipeline defects based on heterogeneous field signals. The method includes the following steps: firstly, acquiring heterogeneous field signals, performing an abnormality judgement, then correcting base values of the heterogeneous field signals, and performing denoising treatment; padding the denoised heterogeneous field signals corresponding to the pipeline defects, unifying the heterogeneous field signals of different sizes into the heterogeneous field signals of same sizes, and performing a nonlinear transformation on signal amplitudes; designing a sparse autoencoder with an axisymmetric structure, and obtaining primary characteristics of the heterogeneous field signals; classifying the pipeline defects according to lengths, widths and depths to obtain category labels of the pipeline defects; designing a multi-classification neural network to classify the heterogeneous field signals, and extracting deep characteristics containing defect size information; and constructing a random forest regression model to realize intelligent inversion for sizes of the pipeline defects.
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:
Provided are a double auxiliary resonant commutated pole three-phase soft-switching inverter circuit and a modulation method. The circuit includes a three-phase main inverter circuit and a three-phase double auxiliary resonant commutator circuit. An A-phase double auxiliary resonant commutator circuit, an A-phase main inverter circuit, a B-phase double auxiliary resonant commutator circuit, a B-phase main inverter circuit, a C-phase double auxiliary resonant commutator circuit and a C-phase main inverter circuit are connected in parallel in sequence and simultaneously connected with a DC power supply in parallel. The present invention can achieve the separation of the resonant current of the double auxiliary resonant commutator circuit from the load current at the moment of current commutation, thereby effectively reducing the current stress of the auxiliary switching tubes and the efficiency can be greatly increased particularly under light load condition.
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.