Regional power grid load prediction method and device

Abstract

The invention relates to a regional power grid load prediction method and device, which belong to the technical field of electric power, and solve the problem that data information contained in unstructured meteorological factors is lost when modeling is carried out through structured meteorological data, so that the accuracy of load prediction is influenced. The method comprises the steps of determining meteorological data influencing loads in all meteorological partitions in a regional power grid, wherein the meteorological data comprise air pressure, temperature, precipitation, relative humidity, wind speed, wind direction, date types and cloud picture data obtained through shooting of an all-sky imager, preprocessing the meteorological data, establishing a cloud picture classification and discrimination model of a Gabor filter-convolutional neural network, and performing prediction and classification processing on the preprocessed cloud picture data by using the discrimination model, fusing the classified cloud picture data with other meteorological data to form a meteorological data set, establishing a load prediction model, and predicting the load of each meteorological partition by using the load prediction model. And the accuracy and precision of load prediction are improved.

Description

technical field [0001] The invention relates to the field of electric power technology, in particular to a method and device for load forecasting of a regional power grid. Background technique [0002] Power load forecasting is the basis for guiding power grid planning and arranging power generation plans. High-precision load forecasting plays an important role in improving the safe, stable and economical operation of power grids. Short-term power load is easily affected by various numerical and non-numerical factors such as meteorological conditions and holiday types. The change of load presents a certain degree of randomness and nonlinearity, which affects the accuracy of load forecasting. The accuracy of forecasting needs to be further improved. . [0003] At present, the power load forecasting methods are mainly divided into two categories: traditional forecasting methods and intelligent forecasting methods. Traditional forecasting methods mainly include time series, r...

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Problems solved by technology

[0005] In view of the above analysis, the embodiment of the present invention aims to provide a regional power grid load forecasting method and device to solve the problem that the

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