Park power system net load combined prediction method based on adaptive error feedback

An error feedback, power system technology, applied in the field of park power system net load combination forecasting, can solve problems such as unawareness

Active Publication Date: 2020-03-24
XI AN JIAOTONG UNIV
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Problems solved by technology

However, little literature has focused on modeling park power system net loads, failing to appreciate the value of applying error-feedback-based combined forecasting techniques on top of various individual forecasts

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  • Park power system net load combined prediction method based on adaptive error feedback
  • Park power system net load combined prediction method based on adaptive error feedback
  • Park power system net load combined prediction method based on adaptive error feedback

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Embodiment Construction

[0077] The invention provides a net load combination forecasting method of park power system based on adaptive error feedback, which determines sample data according to the date to be forecasted, performs abnormal identification and data preprocessing; then adaptively selects characteristic indicators; based on similarity set, performs training of various methods, and select the individual prediction models under the evaluation system; then combine the selected individual prediction models, and use the particle swarm optimization-least squares support vector machine algorithm to perform combined regression on each independent prediction value, and The error is compared with the actual historical training value to obtain the optimal variable weight value after fitting; finally, an adaptive combination forecasting method is performed based on historical data. The invention can improve the accuracy of forecasting the net load of the power system in the park, and is more reliable a...

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Abstract

The invention discloses a park power system net load combined prediction method based on adaptive error feedback, and the method comprises the steps: determining sample data according to a to-be-predicted date, and carrying out the abnormality recognition and data preprocessing; adaptively selecting characteristic indexes; training various methods based on the similarity set, and selecting an individual prediction model under the evaluation system; respectively combining the selected individual prediction models, performing combined regression on each independent prediction value by using a particle swarm optimization-least square support vector machine algorithm, and comparing an error with an actual historical training value to obtain a fitted optimal variable weight; and finally, executing an adaptive combined prediction method based on historical data. According to the method, the accuracy of predicting the net load of the park power system can be improved, and the method is more reliable and effective than an individual prediction method.

Description

technical field [0001] The invention belongs to the technical field of power load data forecasting, and in particular relates to a net load combination forecasting method of park power system based on adaptive error feedback. Background technique [0002] In recent years, combined prediction technology based on error feedback has become more and more effective in the era of smart grid, especially in power distribution system. Since 2015, China has carried out power system reforms aimed at establishing a market-oriented relationship between supply and demand. With the rapid development of China's electricity market and electricity sales business system, the net demand forecast of electricity sales companies in the distribution network, represented by park power grids, has aroused great concern. To some extent, the reform of electricity sales companies is a key part of this reform, and its main work is in terms of power supply reliability, flexibility and economy. Due to the...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06G06K9/62
CPCG06Q10/04G06Q10/0637G06Q50/06G06F18/23213Y04S10/50
Inventor 王建学鲁泽龙杨蒙张耀赵天辉汤志伟
Owner XI AN JIAOTONG UNIV
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