A Survey on Short-Term Electricity Price Prediction Models for Smart Grid Applications

被引:1
作者
Vardakas, John S. [1 ]
Zenginis, Ioannis [1 ]
机构
[1] Iquadrat, Barcelona, Spain
来源
WIRELESS INTERNET (WICON 2014) | 2015年 / 146卷
关键词
Electricity pricing; Prediction method; Price forecasting; Computational intelligence; Smart grid; NEURAL-NETWORK APPROACH; FORECAST; MARKET; ALGORITHM;
D O I
10.1007/978-3-319-18802-7_9
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper we present a survey of recent trends on short-term electricity-price prediction models. We classify the proposed price prediction methods based on the forecasting horizon into short-medium- and long-term approaches. We provide the key features of the medium- and long-solutions, while we emphasize on short-term prediction models, by providing their classification into statistical, computational intelligent and hybrid methods. We also highlight the key characteristics of the available prediction methods, while the strengths and weaknesses of these solutions are also discussed and analyzed. These important aspects should be considered by researchers that target on the derivation of more efficient and accurate electricity-price prediction models, especially for smart grid applications.
引用
收藏
页码:60 / 69
页数:10
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