Kernel density estimation-based non-invasive power load identification method

Abstract

The invention relates to a kernel density estimation-based non-invasive power load identification method. The method comprises the following steps of: selecting a common household power load as a research object, acquiring power consumption data of the research object, carrying out sub-state division and extraction power distribution; generating a household working state set according to the power distribution, and calculating simulation power consumption data under each state; carrying out kernel density estimation to obtain probability distribution reference model of each state simulation data; identifying household working state transition points in the reference models, and dividing each household working state data segments; and for each data segment, searching a household working state which is closest to the probability distribution of the data segment, and comparing the household working state with the probability distribution so as to complete an identification task. According to the method, the main data features of power load power consumption can be effectively extracted, the main data distribution features are highlighted, and the influences of random power consumption data and abnormal fluctuation are weakened, so that effect can be well decomposed in the aspect of non-invasive identification, and the method is suitable for the changing and complicated working environment of the current household power grid.

Description

Technical field [0001] The invention relates to a home power grid management technology, in particular to a non-intrusive power load identification method based on nuclear density estimation. Background technique [0002] The research of household energy management system originated in the 1970s. The United States and some European countries started research in this field in order to improve the efficiency of electricity consumption on the residential side and realize "energy saving and emission reduction". In recent years, with the development of sensor technology, information communication technology, and control technology, especially the rise of smart grids, the tasks of household energy management systems have gradually increased. As an extension of the smart grid on the residential side, such as figure 1 As shown, in addition to meeting the requirements of improving electricity efficiency, energy saving and emission reduction, the home energy management system also provides...

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Problems solved by technology

[0005] Aiming at the deficiencies in the prior art of using non-intrusive detection to realize the effective management of the household power grid, the detection has low decomposition accuracy, high cost, and difficulty in popularization. The technical problem to be solved by the present invention is to provide a power monitoring system that minimizes the Non-intrusive electric load identification method based on kernel density estimation based on the hardware requirements of electric meters, reducing the cost of electric meters, and convenient for users

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