Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO

被引：77
|
作者：
Uniejewski, Bartosz [1 ,2 ]
Marcjasz, Grzegorz [1 ,2 ]
Weron, Rafai [1 ]
机构：
[1] Wroclaw Univ Sci & Technol, Fac Comp Sci & Management, Dept Operat Res, Wroclaw, Poland
[2] Wroclaw Univ Sci & Technol, Fac Pure & Appl Math, Wroclaw, Poland
来源：
INTERNATIONAL JOURNAL OF FORECASTING | 2019年 / 35卷 / 04期
关键词：
Intraday electricity market; Variable selection; Price forecasting; LASSO; ARX model; Diebold-Mariano test; Trading strategy; IMPACT; FUNDAMENTALS; MODELS;
D O I：
10.1016/j.ijforecast.2019.02.001
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
We use a unique set of prices from the German EPEX market and take a closer look at the fine structure of intraday markets for electricity, with their continuous trading for individual load periods up to 30 min before delivery. We apply the least absolute shrinkage and selection operator (LASSO) in order to gain statistically sound insights on variable selection and provide recommendations for very short-term electricity price forecasting. (C) 2019 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码：1533 / 1547
页数：15
相关论文
共 50 条
  • [1] Understanding intraday electricity markets: Variable selection and very short-term price forecasting using LASSO (vol 35, pg 1533, 2019)
    Uniejewski, Bartosz
    Marcjasz, Grzegorz
    Weron, Rafal
    INTERNATIONAL JOURNAL OF FORECASTING, 2021, 37 (03) : 1311 - 1311
  • [2] Hybrid Model for Very Short-Term Electricity Price Forecasting
    Hamilton, Geoffrey
    Abeygunawardana, Anula
    Jovanovic, Dejan P.
    Ledwich, Gerard F.
    2018 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM), 2018,
  • [3] A Review of Short-term Electricity Price Forecasting Techniques in Deregulated Electricity Markets
    Hu, Linlin
    Taylor, Gareth
    Wan, Hai-Bin
    Irving, Malcolm
    UPEC: 2009 44TH INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE, 2009, : 145 - 149
  • [4] Short-Term Electricity Price Forecasting
    Arabali, A.
    Chalko, E.
    Etezadi-Amoli, M.
    Fadali, M. S.
    2013 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING (PES), 2013,
  • [5] A Review on Short-Term Electricity Price Forecasting Techniques for Energy Markets
    Jiang, LianLian
    Hu, Guoqiang
    2018 15TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV), 2018, : 937 - 944
  • [6] Analysis of Features Used in Short-Term Electricity Price Forecasting for Deregulated Markets
    Biricik, Goksel
    Bozkurt, O. Ozgur
    Taysi, Z. Cihan
    2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2015, : 600 - 603
  • [7] Short-term electricity price forecasting based on price subsequences
    State Grid Corporation of China, Beijing 100031, China
    不详
    Dianli Xitong Zidonghue, 2007, 3 (4-8):
  • [8] Adaptive short-term electricity price forecasting using artificial neural networks in the restructured power markets
    Yamin, HY
    Shahidehpour, SM
    Li, Z
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2004, 26 (08) : 571 - 581
  • [9] A proposed grey model for short-term electricity price forecasting in competitive power markets
    Lei, Mingli
    Feng, Zuren
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2012, 43 (01) : 531 - 538
  • [10] Very short term irradiance forecasting using the lasso
    Yang, Dazhi
    Ye, Zhen
    Lim, Li Hong Idris
    Dong, Zibo
    SOLAR ENERGY, 2015, 114 : 314 - 326
12345