Next Day Price Forecasting in Deregulated Market by Combination of Artificial Neural Network and ARIMA Time Series Models

被引：0

作者：

Areekul, Phatchakorn ^{[1
]}

Senjyu, Tomonobu ^{[1
]}

Urasaki, Naomitsu ^{[1
]}

Yona, Atsushi ^{[1
]}

机构：

[1] Univ Ryukyus, Fac Engn, Dept Elect & Elect Engn, Okinawa 9030213, Japan

来源：

ICIEA 2010: PROCEEDINGS OF THE 5TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOL 3 | 2010年

关键词：

Electricity price forecasting; neural network; ARIMA; combination methodology; back-propagation;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Electricity price forecasting is becoming increasingly relevant to power producers and consumers in the new competitive electric power markets, when planning bidding strategies in order to maximize their benefits and utilities, respectively. This paper proposed a method to predict hourly electricity prices for next-day electricity markets by combination methodology of ARIMA and ANN models. The proposed method is examined on the Australian National Electricity Market (NEM), New South Wales regional in year 2006. Comparison of forecasting performance with the proposed ARIMA, ANN and combination (ARIMA-ANN) models are presented. Empirical results indicate that an ARIMA-ANN model can improve the price forecasting accuracy.

引用

页码：299 / 304

页数：6

共 50 条

[21] Forecasting Malaysian Foreign Exchange Rate Using Artificial Neural Network and ARIMA Time Series
Ismail, Munira
Jubley, Nurul Zafirah
Ali, Zalina Mohd.
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MATHEMATICS, ENGINEERING AND INDUSTRIAL APPLICATIONS 2018 (ICOMEIA 2018), 2018, 2013
[22] A Spiking Neural Network Based on Temporal Encoding for Electricity Price Time Series Forecasting in Deregulated Markets
Sharma, V.
Srinivasan, D.
2010 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS IJCNN 2010, 2010,
[23] Building neural network forecasting models from time series ARIMA models: A procedure and a comparative analysis
Cubiles-De-La-Vega, María-Dolores
Pino-Mejías, Rafael
Pascual-Acosta, Antonio
Muñoz-García, Joaquín
Intelligent Data Analysis, 2002, 6 (01) : 53 - 65
[24] Forecasting stock price using integrated artificial neural network and metaheuristic algorithms compared to time series models
Shahvaroughi Farahani, Milad
Razavi Hajiagha, Seyed Hossein
SOFT COMPUTING, 2021, 25 (13) : 8483 - 8513
[25] Forecasting stock price using integrated artificial neural network and metaheuristic algorithms compared to time series models
Milad Shahvaroughi Farahani
Seyed Hossein Razavi Hajiagha
Soft Computing, 2021, 25 : 8483 - 8513
[26] Hybridization of ARIMA with Learning Models for Forecasting of Stock Market Time Series
Frédy Pokou
Jules Sadefo Kamdem
François Benhmad
Computational Economics, 2024, 63 : 1349 - 1399
[27] A Hybrid Forecasting Structure Based on Arima and Artificial Neural Network Models
Atesongun, Adil
Gulsen, Mehmet
APPLIED SCIENCES-BASEL, 2024, 14 (16):
[28] Hybridization of ARIMA with Learning Models for Forecasting of Stock Market Time Series
Pokou, Fredy
Kamdem, Jules Sadefo
Benhmad, Francois
COMPUTATIONAL ECONOMICS, 2024, 63 (04) : 1349 - 1399
[29] Forecast of Next Day Clearing Price in Deregulated Electricity Market
Zhou, Hui
Wu, Xinhua
Wang, Wei
Chen, Liping
2009 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2009), VOLS 1-9, 2009, : 4397 - +
[30] A comparison of artificial neural network and time series models for forecasting commodity prices
Kohzadi, N
Boyd, MS
Kermanshahi, B
Kaastra, I
NEUROCOMPUTING, 1996, 10 (02) : 169 - 181

← 1 2 3 4 5 →