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Medium and long term power load forecasting using CPSO-GM model

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成果类型:
期刊论文
作者:
Pan, Guo;Ouyang, Aijia
通讯作者:
Ouyang, A.(ouyangaijia@163.com)
作者机构:
[Pan, Guo] College of Information Science and Engineering, Hunan University, Changsha 410131, China
[Ouyang, Aijia] School of Information Science and Engineering, Hunan City University, Yiyang, Hunan 413000, China
[Ouyang, Aijia] College of Computer, Hunan Science and Technology economy trade vocation college, Hengyang 421001, Hunan, China
[Pan, Guo] Logistics Information Dept, Hunan Vocational College of Modern Logistics, Changsha 410082, China
语种:
英文
期刊:
Journal of Networks
ISSN:
1796-2056
年:
2014
卷:
9
期:
8
页码:
2121-2128
机构署名:
本校为其他机构
院系归属:
信息与电子工程学院
摘要:
To overcome the low precision of the basic grey model (GM) in forecasting power loads of medium and longterm, a co-evolutionary particle swarm optimization (CPSO) Grey Model (CPSO-GM) is proposed in this paper. This is done by employing the CPSO to optimize the parameters of the grey model based on the modified formula of the background value. They conduct the simulation experiments on the power load data of medium and long-term by applying the CPSO-GM. The experimental results show that the proposed algorithm is superior to the three different grey prediction models and better to forecast pow...

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