Modeling and forecasting electricity prices with input/output hidden Markov models

被引：211

作者：

González, AM ^{[1
]}

San Roque, AM ^{[1
]}

García-González, J ^{[1
]}

机构：

[1] Univ Pontificia Comillas Madrid, IIT, Escuela Tecn Superior Ingn, Madrid 28015, Spain

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 2005年 / 20卷 / 01期

关键词：

artificial neural networks; electricity markets; hidden Markov models; modeling competitors' behavior; price forecasting;

D O I：

10.1109/TPWRS.2004.840412

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In competitive electricity markets, in addition to the uncertainty of exogenous variables such as energy demand, water inflows, and availability of generation units and fuel costs, participants are faced with the uncertainty of their competitors' behavior. The analysis of electricity price time series reflects a switching nature, related to discrete changes in competitors' strategies, which can be represented by a set of dynamic models sequenced together by a Marko am. In this paper, an Input-Output Hidden Markov Model (IOHMM) is proposed for analyzing and forecasting electricity spot prices. The model provides both good predictions in terms of accuracy as well as dynamic information about the market. In this way, different market states are identified and characterized by their more relevant explanatory variables. Moreover, a conditional probability transition matrix governs the probabilities of remaining in the same state, or changing to another, whenever a new market session is opened. The model has been successfully applied to real clearing prices in the Spanish electricity market.

引用

页码：13 / 24

页数：12

共 33 条

[21]

LAUZON VP, 1999, MODELES STAT COMME A

[22]

LUCIA JJ, 2001, ELECT PRICES POWER D

[23]

McLachlan G. J., 1997, EM ALGORITHM EXTENSI

[24] Forecasting next-day electricity prices by time series models [J].

Nogales, FJ ;

Contreras, J ;

Conejo, AJ ;

Espínola, R .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2002, 17 (02) :342-348

[25] Modeling and prediction of human behavior [J].

Pentland, A ;

Liu, A .

NEURAL COMPUTATION, 1999, 11 (01) :229-242

[26] A TUTORIAL ON HIDDEN MARKOV-MODELS AND SELECTED APPLICATIONS IN SPEECH RECOGNITION [J].

RABINER, LR .

PROCEEDINGS OF THE IEEE, 1989, 77 (02) :257-286

[27] Short-term variations and long-term dynamics in commodity prices [J].

Schwartz, E ;

Smith, JE .

MANAGEMENT SCIENCE, 2000, 46 (07) :893-911

[28]

SHANMING S, 1998, THESIS U COLORADO BO

[29] Electricity price short-term forecasting using artificial neural networks [J].

Szkuta, BR ;

Sanabria, LA ;

Dillon, TS .

IEEE TRANSACTIONS ON POWER SYSTEMS, 1999, 14 (03) :851-857

[30]

Titterington D.M., 1985, Statistical analysis of finite mixture distributions

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