GA based optimized LS-SVM forecasting of short term electricity price in competitive power markets

被引：13
|
作者：
Mahjoob, M. J. [1 ]
Abdollahzade, M. [1 ]
Zarringhalam, R. [2 ]
机构：
[1] Univ Tehran, Sch Mech Eng, Tehran, Iran
[2] KN Toosi Univ Technol, Sch Mech Eng, Tehran, Iran
来源：
ICIEA 2008: 3RD IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, PROCEEDINGS, VOLS 1-3 | 2008年
关键词：
D O I：
10.1109/ICIEA.2008.4582483
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Development of competitive power markets has emerged an increasing tendency to forecast the future prices among both the producers and the consumers with the major aim of profit maximization. A Least-Square Support Vector Machines approach, in combination with a hybrid Genetic Algorithm based optimization is proposed in this paper to forecast Market Clearing Prices in two different power markets. The forecasting results are compared to a select variety of previously proposed methods such as MLP, ARIMA, WAVELET- ARIMA, Neuro-Fuzzy and Time Series based models. The performed comprehensive comparison demonstrates the remarkable accuracy and effectiveness of the proposed method.
引用
收藏
页码：73 / +
页数：2
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