NDLI: Important variable assessment and electricity price forecasting based on regression tree models: classification and regression trees, Bagging and Random Forests

Content Provider	IET Digital Library
Author	González, Camino Williams, José Mira Mc Juárez, Isabel
Abstract	Electricity price forecasting has become the focus of considerable interest in a deregulated energy market. In this study, regression tree-based models: classification and regression trees, Bagging and Random Forests have been built and used to identify the variables dominating the marginal price of the commodity as well as for short-term (one hour and day ahead) electricity price forecasting for the Spanish–Iberian market. Different prediction models are proposed including the main features of the market such as load, hydro and thermal generation and from available, wind energy production, of strategic interest in the Spanish market. In addition other explanatory variables are considered as lagged prices, as well as hour, day, month and year indicators. In the study, hourly data from 2000–2011 corresponding to 22 variables have been used. The results show the effectiveness of the proposed ensemble of tree-based models which emerge as an alternative and promising tool, competitive with other existing methods.
Starting Page	1120
Ending Page	1128
Page Count	9
ISSN	17518687
Volume Number	9
e-ISSN	17518695
Issue Number	Issue 11, Aug (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/9/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2014.0655
Journal	IET Generation, Transmission & Distribution
Publisher Date	2015-02-27
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Bagging Combinatorial Mathematics Hydro Generation Marginal Price Mathematics Power Market Power System Economics Power System Managemen Power System Operation Random Forest Regression Analysis Regression Tree Model Short-term Electricity Price Forecasting Spanish-Iberian Market Statistics Thermal Generation Trees Variable Assessment Wind Energy Production
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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