Short-term load forecasting method for microgrid based on independent component analysis and support vector machine

Abstract

The invention discloses a microgrid short-term load forecasting method based on independent component analysis and support vector machine, including: using Chebyshevv orthogonal polynomials to perform curve fitting on the historical daily load data of the microgrid area, and adding a penalty function for optimization; updating The historical load data is analyzed independently by using the independent component analysis method to obtain the load independent separation source and mixing matrix of the historical load data; for the meteorological data obtained on the historical day and the forecast day, the principal component analysis method is used to obtain the principal component vector, and combined with The date data are used together to form decision-making data; the mixing matrix of historical load data is used as the target data, combined with the historical daily decision-making data, the support vector machine and the fireworks algorithm are used to optimize its parameter penalty factor and kernel parameters, and obtain the optimal support vector machine training model ; Substitute the forecasted daily decision-making data to obtain the forecasted daily load curve. The invention can remove noise interference, and can effectively and accurately predict the future short-term load of the microgrid.

Description

technical field [0001] The invention relates to a short-term load forecasting method for a micro-grid based on independent component analysis and a support vector machine, and belongs to the technical field of power system scheduling and operation. Background technique [0002] With the continuous development of society, the human demand for energy is also increasing. In the electric power industry, the power generation pattern dominated by traditional fossil energy has also become more and more disadvantageous due to the gradual depletion of resources and environmental problems. With the development of science and technology in recent years, various new energy sources can be used for power generation, such as wind power and photovoltaic power generation, It is gradually applied to the power system, but it also brings problems and challenges to the power system scheduling and operation while solving the problem of energy depletion. [0003] Traditional short-term load forec...

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Problems solved by technology

[0009] The technical problem to be solved by the present invention is to overcome the difficulty of forecasting caused by the uncertainty of the load in the microgrid, and provide a short-term load forecasting method for the microgrid based on independent component analysis and support vector machine, with the regional daily load of the microgrid as the final Predict variables, while taking into account the noise interference in the historical load data, perform adaptive curve fitting to smooth the load curve, remove noise interference, and avoid the unsmooth defect of the load curve caused by the prediction, so as to improve the accuracy of the model Or reduce the computational load of the model

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