Electricity Spot Price Forecast by Modelling Supply and Demand Curve

被引:13
作者
Pinhao, Miguel [1 ,2 ]
Fonseca, Miguel [1 ]
Covas, Ricardo [2 ]
机构
[1] NOVA Math, NOVA Sch Sci & Technol, Dept Math, P-2829516 Caparica, Portugal
[2] EDP Energias Portugal, P-1249300 Lisbon, Portugal
关键词
electricity price forecast; electricity; market curves; electricity price; vector auto regression; time-series; WAVELET TRANSFORM; NEURAL-NETWORKS; SEARCH ALGORITHM; HYBRID MODEL; MARKETS; SYSTEM; GENERATION; PREDICTION; MACHINE; LOADS;
D O I
10.3390/math10122012
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Electricity price forecasting has been a booming field over the years, with many methods and techniques being applied with different degrees of success. It is of great interest to the industry sector, becoming a must-have tool for risk management. Most methods forecast the electricity price itself; this paper gives a new perspective to the field by trying to forecast the dynamics behind the electricity price: the supply and demand curves originating from the auction. Given the complexity of the data involved which include many block bids/offers per hour, we propose a technique for market curve modeling and forecasting that incorporates multiple seasonal effects and known market variables, such as wind generation or load. It is shown that this model outperforms the benchmarked ones and increases the performance of ensemble models, highlighting the importance of the use of market bids in electricity price forecasting.
引用
收藏
页数:20
相关论文
共 50 条
  • [21] Do futures prices help forecast the spot price?
    Jin, Xin
    JOURNAL OF FUTURES MARKETS, 2017, 37 (12) : 1205 - 1225
  • [22] An empirical comparison of alternative schemes for combining electricity spot price forecasts
    Nowotarski, Jakub
    Raviv, Eran
    Trueck, Stefan
    Weron, Rafal
    ENERGY ECONOMICS, 2014, 46 : 395 - 412
  • [23] Data-Driven Electricity Price Risk Assessment for Spot Market
    Lu, En
    Wang, Ning
    Zheng, Wei
    Wang, Xuanding
    Lei, Xingyu
    Zhu, Zhengchun
    Gong, Zhaoyu
    INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS, 2022, 2022
  • [24] Short-term electricity price forecast based on the improved hybrid model
    Dong, Yao
    Wang, Jianzhou
    Jiang, He
    Wu, Jie
    ENERGY CONVERSION AND MANAGEMENT, 2011, 52 (8-9) : 2987 - 2995
  • [25] Autonomous Hybrid Forecast Framework to Predict Electricity Demand
    Gehbauer, Christoph
    Oliveira, Paulo
    Tragner, Manfred
    Black, Douglas R.
    Baptista, Jose
    2024 IEEE 22ND MEDITERRANEAN ELECTROTECHNICAL CONFERENCE, MELECON 2024, 2024, : 242 - 247
  • [26] Using the LSTM Network to Forecast the Demand for Electricity in Poland
    Manowska, Anna
    APPLIED SCIENCES-BASEL, 2020, 10 (23): : 1 - 16
  • [27] Electricity Price and Demand Forecasting in Smart Grids
    Motamedi, Amir
    Zareipour, Hamidreza
    Rosehart, William D.
    IEEE TRANSACTIONS ON SMART GRID, 2012, 3 (02) : 664 - 674
  • [28] The price elasticity of electricity demand in South Australia
    Fan, Shu
    Hyndman, Rob J.
    ENERGY POLICY, 2011, 39 (06) : 3709 - 3719
  • [29] Electricity Spot Price Modeling and Forecasting in European Markets
    Tehrani, Shadi
    Juan, Jesus
    Caro, Eduardo
    ENERGIES, 2022, 15 (16)
  • [30] Price dynamics among US electricity spot markets
    Park, H
    Mjelde, JW
    Bessler, DA
    ENERGY ECONOMICS, 2006, 28 (01) : 81 - 101