Credibility forecasting in short-term load forecasting and its application

Canbing Li; Yijing Li; Yijia Cao; Jin Ma; Yonghong Kuang; Zhikun Zhang; Lijuan Li; Jing Wei

Credibility forecasting in short-term load forecasting and its application

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Author(s): Canbing Li ¹ ; Yijing Li ¹ ; Yijia Cao ¹ ; Jin Ma ² ; Yonghong Kuang ¹ ; Zhikun Zhang ^{1, 3} ; Lijuan Li ¹ ; Jing Wei ¹
- Affiliations: 1: College of Electrical and Information Engineering, Hunan University, Changsha 410082, Hunan Province, People's Republic of China ;
  2: School of Electrical and Information Engineering, University of Sydney, Sydney, NSW 2006, Australia ;
  3: Tangshan Power Supply Company, Tangshan 063009, Hebei Province, People's Republic of China
Source: Volume 9, Issue 13, 01 October 2015, p. 1564 – 1571
DOI: 10.1049/iet-gtd.2014.0729 , Print ISSN 1751-8687, Online ISSN 1751-8695

Received 25/07/2014, Accepted 27/01/2015, Revised 11/01/2015, Published 12/05/2015

It is very helpful for power system operation to assess and forecast the uncertainty of the load forecasting. The improved credibility assessment index of the short-term load forecasting results is presented to assess the uncertainty in this study. The forecasting method for credibility of short-term load forecasting is also proposed by adopting genetic algorithm-based back propagation neural network. In the case study, it is proved that the improved credibility assessment can evaluate the short-term load forecasting results and the forecasting methods. Meanwhile, the credibility forecasting can contribute to optimise reserve capacity in power system scheduling.

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Credibility forecasting in short-term load forecasting and its application

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