5 results about "Quadratic nonlinearity" patented technology

The invention relates to the technical field of power system transformers, and discloses a converter transformer oil paper insulation electrical strength prediction method, which comprises the following steps: S01, setting the temperature of a converter transformer oil paper insulation sample, S02, applying voltage to the converter transformer oil paper insulation sample to generate breakdown, S03, collecting breakdown strength data, and S04, determining the electrical strength of the converter transformer oil paper insulation sample. S04, analyzing breakdown strength data, S05, fitting breakdown data according to a quadratic nonlinear regression equation, and S06, predicting the electrical strength of the oil paper insulation of the converter transformer, namely predicting the breakdown strength of the oil paper insulation material under different temperature and harmonic frequency conditions, and determining the electrical strength of the oil paper insulation according to the influence of the temperature and the frequency on the electrical strength of the oil paper insulation. The method can more comprehensively reflect the insulation state under the actual operation condition, and provides a theoretical basis for the evaluation of the insulation performance of the converter transformer equipment in the actual operation.

The present invention relates to a laser induced breakdown spectroscopy quantitative analysis method, which belongs to the technical field of infrared and plasma emission spectroscopy measurement methods. The technical solution of the present invention is: determining a series of samples to be tested, obtaining laser induced breakdown spectra, using three models of Lasso, ridge and quadratic nonlinear regression as stacking ensemble learning model inputs, and utilizing the preferred spectral lines of each element and the best matching normalized spectral line combination pairs. The beneficial effects of the present invention are: the input spectral lines used by each element model can remain stable after verification and normalization, and the sample preparation is simple, fast and convenient in combination with the laser induced breakdown spectroscopy material discrimination technology, eliminating the unstable disadvantages of a single model, combining weak learners into a strong learner, and combining the laser induced breakdown spectroscopy material discrimination technology to make the sample preparation simple, fast and convenient, thereby realizing rapid and high-precision quantitative detection of steel samples.

This invention discloses a reactive power optimization method for distribution networks based on probabilistic power flow sensitivity analytical transformation, belonging to the field of power system optimization and dispatching technology. The method includes: considering the impact of source-load power uncertainty on distribution network dispatching, constructing a reactive power optimization model based on chance constraints, and using probabilistic power flow sensitivity to characterize the probability distributions of voltage and branch power random variables respectively; linearizing the quadratic nonlinear branch security constraints using a regular polygon approximation method to decouple the optimization variables from the random variables; establishing analytical expressions for voltage and branch security chance constraints through affine transformation of probabilistic power flow sensitivity; and analytically transforming the nonlinear chance constraints into deterministic constraints based on probability transformation theory, transforming the original problem into a mixed-integer second-order cone programming model for solution. This invention can fully tap the potential of photovoltaic reactive power regulation, significantly improve voltage stability and reduce network losses, while also having a computational efficiency advantage over the traditional sample mean method.

The application discloses a kind of solving method and device of quadratic nonlinear equations based on quantum circuit, method includes: obtaining target linear equation group, target linear equation group is determined according to initial quadratic nonlinear equation group conversion, constructs the quantum circuit corresponding to quantum linear solver, runs quantum circuit and measures, to solve target linear equation group, based on the solution of the solved target linear equation group, determine the solution of initial quadratic nonlinear equation group, using the relevant characteristics of quantum, realize a kind of can satisfy quadratic nonlinear equation solving technique, reduce the complexity and difficulty of solution.

The invention relates to a complex terrain wind resource assessment method, and the method comprises the steps: carrying out the downscaling of obtained 3km WRF simulation data into a 100m refined meteorological element wind field through employing CALMET, and obtaining 100m WRF / CALMET simulation data; the 100m WRF / CALMET simulation data and the 3km WRF simulation data are respectively compared with the actually measured data of the weather station, and regional wind resource evaluation is carried out; aiming at a wind speed difference found in wind energy resource evaluation, correcting a wind speed deviation by respectively using an LSTM neural network and a VMD-LSTM model, and selecting an optimal wind speed deviation correction scheme; aiming at wind direction differences found in wind energy resource evaluation, a BP neural network and a multivariate quadratic nonlinear regression model are respectively used for correcting wind direction deviation, and an optimal wind speed deviation correction scheme is selected. Compared with the prior art, the method has the advantages that the simulation precision is effectively improved on the premise of keeping certain physical consistency, a theoretical basis and technical support are provided for wind energy development of a complex terrain area, and the target of carbon emission reduction in green development of the area is achieved.