Short-term and medium- and long-term electric power load prediction method based on machine learning model

Abstract

The invention discloses a short-term and medium- and long-term electric power load prediction method based on machine learning model. Firstly, preprocessing is conducted on data, including smootheningabnormal data and filling missing data. Factors of affecting load changes will be analyzed, including historical data, time periodicity, and weather variable characteristics. Domestication will be conducted on all input variables for accelerating learning speed and raising prediction precision. The invention is advantageous in that linear regression is compared, and the performance of the vectorregression and gradient lifting regression in the short-term and medium- and long-term electric power load prediction is supported; with the prolongation of the prediction time, the performance of thegradient lifting regression model is better that that of the other two models; the AdaBoost algorithm which uses the gradient lifting tree as a basic classifier is brought forward, and load prediction is conducted, and the precision of electric power load prediction can be effectively raised.

Description

technical field [0001] The present invention relates to the field of power load forecasting, and more specifically, relates to a short-term and medium- and long-term power load forecasting method based on a machine learning model. Background technique [0002] Power load forecasting is an important part of power research and plays a key role in the effective operation of the power market. With the advancement of science and technology and the needs of economic development, the construction of smart grid has begun, thereby improving the utilization rate of energy and promoting the optimal allocation of resources. [0003] According to different forecast periods, power load forecasting can be divided into short-term, medium-term and long-term forecasting. Short-term load forecasting (STLF) includes load forecasting for the next few minutes, one hour, one day, and one week, and is used for economic dispatch and power system security assessment to ensure safe, economical, and s...

AI Technical Summary

Problems solved by technology

These algorithms are easy to implement on some datasets, but their predictive accuracy is usually lower compared with more complex machine learning algorithms, which can provide higher accuracy and stronger learning ability

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