IMPROVING THE ACCURACY OF SHORT-TERM LOAD FORECASTING OF DELIVERY POINT CLUSTER OF THE SECOND LEVEL DEFAULT PROVIDER

IMPROVING THE ACCURACY OF SHORT-TERM LOAD FORECASTING OF DELIVERY POINT CLUSTER OF THE SECOND LEVEL DEFAULT PROVIDER

Relevance of the discussed issue is caused by the need to improve the accuracy of short-term load forecasting of delivery point cluster of the second level default provider. The system operator uses the result of forecast when forming power system dispatch load curve. Usually, prediction errors lead...

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Bibliographic Details
Main Authors:	Stanislav O. Khomutov, Vasiliy I. Stashko, Nikolay A. Serebryakov
Format:	Article
Language:	Russian
Published:	Tomsk Polytechnic University 2020-06-01
Series:	Известия Томского политехнического университета: Инжиниринг георесурсов
Subjects:	short-term load forecasting artificial neural networks learning algorithm wholesale electricity market delivery point cluster gradient descent
Online Access:	http://izvestiya.tpu.ru/archive/article/view/2682/2248

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