摘要
Daily power load forecasting plays a significant role in electrical power system operation and planning. Therefore, it is necessary to find automatic interrelations of data and select the optimal structure of model. However, obtaining high accuracy by using single model for short-term load forecasting (STLF) is not easy. In this paper, Group Method of Data Handling (GMDH) is applied to forecast electric load demand of New South Wales (NSW) in Australia from January 17, 2009 to January 18, 2009. Compared with outcomes obtained by ARIMA, we demonstrate that GMDH is a better method for STLF.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | Advances in Intelligent Systems - Selected Papers from 2012 International Conference on Control Systems, ICCS 2012 |
| 页 | 27-32 |
| 页数 | 6 |
| DOI | |
| 出版状态 | 已出版 - 2012 |
| 已对外发布 | 是 |
| 活动 | 2012 International Conference on Environment Science, ICES 2012 and 2012 International Conference on Computer Science, ICCS 2012 - Melbourne, VIC, 澳大利亚 期限: 15 3月 2012 → 16 3月 2012 |
出版系列
| 姓名 | Advances in Intelligent and Soft Computing |
|---|---|
| 卷 | 138 AISC |
| ISSN（印刷版） | 1867-5662 |
会议
| 会议 | 2012 International Conference on Environment Science, ICES 2012 and 2012 International Conference on Computer Science, ICCS 2012 |
|---|---|
| 国家/地区 | 澳大利亚 |
| 市 | Melbourne, VIC |
| 时期 | 15/03/12 → 16/03/12 |
指纹
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Xu, H., Dong, Y., Wu, J., & Zhao, W. (2012). Application of GMDH to short-term load forecasting. 在 Advances in Intelligent Systems - Selected Papers from 2012 International Conference on Control Systems, ICCS 2012 (页码 27-32). (Advances in Intelligent and Soft Computing; 卷 138 AISC). https://doi.org/10.1007/978-3-642-27869-3_4