Forecasting short-term electricity consumption using the adaptive grey-based approach-An Asian case

Der Chiang Li, Che Jung Chang, Chien Chih Chen, Wen Chih Chen

研究成果: Article

142 引文 斯高帕斯(Scopus)

摘要

The overall electricity consumption, treated as a primary guideline for electricity system planning, is a major measurement to indicate the degree of a nation's development. The electricity consumption forecast is especially important with regard to policy making in developing countries (Asian countries in this work). However, since the economic growth rates in these countries are usually high and unstable, it is difficult to obtain accurate predictions using long-term data, and thus forecasting with limited (short-term) data is more effective and of considerable interest. Grey theory is one approach that can be used to construct a model with limited samples to provide better forecasting advantage for short-term problems. The forecasting performance of AGM(1,1), based on grey theory, has been confirmed using the Asia-Pacific economic cooperation energy database, and the results, compared with those obtained from back propagation neural networks (BPN) and support vector regression (SVR), show that the proposed approach can effectively deal with the problem of forecasting electricity consumption when the sample size is limited.

原文English
頁(從 - 到)767-773
頁數7
期刊Omega
40
發行號6
DOIs
出版狀態Published - 2012 十二月 1

    指紋

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Information Systems and Management

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