Comprehensive Review on Electricity Market Price and Load Forecasting Based on Wind Energy

被引:31
作者
Acaroglu, Hakan [1 ]
Garcia Marquez, Fausto Pedro [2 ]
机构
[1] Eskisehir Osmangazi Univ, Fac Econ & Adm Sci, Dept Econ, TR-26480 Eskisehir, Turkey
[2] Univ Castilla La Mancha, Ingenium Res Grp, Ciudad Real 13004, Spain
关键词
electricity price; electricity load; electricity price forecasting; wind energy; day-ahead market; intra-day market; balancing power market; NEURAL-NETWORK; RENEWABLE ENERGY; WAVELET TRANSFORM; POWER-GENERATION; SEARCH ALGORITHM; DEMAND RESPONSE; OPTIMAL-DESIGN; HYBRID MODELS; SPOT PRICES; IMPACT;
D O I
10.3390/en14227473
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Forecasting the electricity price and load has been a critical area of concern for researchers over the last two decades. There has been a significant economic impact on producers and consumers. Various techniques and methods of forecasting have been developed. The motivation of this paper is to present a comprehensive review on electricity market price and load forecasting, while observing the scientific approaches and techniques based on wind energy. As a methodology, this review follows the historical and structural development of electricity markets, price, and load forecasting methods, and recent trends in wind energy generation, transmission, and consumption. As wind power prediction depends on wind speed, precipitation, temperature, etc., this may have some inauspicious effects on the market operations. The improvements of the forecasting methods in this market are necessary and attract market participants as well as decision makers. To this end, this research shows the main variables of developing electricity markets through wind energy. Findings are discussed and compared with each other via quantitative and qualitative analysis. The results reveal that the complexity of forecasting electricity markets' price and load depends on the increasing number of employed variables as input for better accuracy, and the trend in methodologies varies between the economic and engineering approach. Findings are specifically gathered and summarized based on researches in the conclusions.
引用
收藏
页数:23
相关论文
共 163 条
[1]   Electricity price forecast using Combinatorial Neural Network trained by a new stochastic search method [J].
Abedinia, O. ;
Amjady, N. ;
Shafie-Khah, M. ;
Catalao, J. P. S. .
ENERGY CONVERSION AND MANAGEMENT, 2015, 105 :642-654
[2]   SHORT-TERM LOAD DEMAND MODELING AND FORECASTING - A REVIEW [J].
ABUELMAGD, MA ;
SINHA, NK .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1982, 12 (03) :370-382
[3]   Use of two-component Weibull mixtures in the analysis of wind speed in the Eastern Mediterranean [J].
Akdag, S. A. ;
Bagiorgas, H. S. ;
Mihalakakou, G. .
APPLIED ENERGY, 2010, 87 (08) :2566-2573
[4]   Review of the use of Numerical Weather Prediction (NWP) Models for wind energy assessment [J].
Al-Yahyai, Sultan ;
Charabi, Yassine ;
Gastli, Adel .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2010, 14 (09) :3192-3198
[5]   A summary of demand response in electricity markets [J].
Albadi, M. H. ;
El-Saadany, E. F. .
ELECTRIC POWER SYSTEMS RESEARCH, 2008, 78 (11) :1989-1996
[6]   Energy price forecasting: Problems and proposals for such predictions [J].
Electrical Engineering Department, Semnan University, Semnan, Iran ;
不详 .
IEEE Power Energ. Mag., 2006, 2 (20-29) :20-29
[7]   Day-ahead price forecasting of electricity markets by a new fuzzy neural network [J].
Amjady, N .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2006, 21 (02) :887-896
[8]   Short-term bus load forecasting of power systems by a new hybrid method [J].
Amjady, Nima .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2007, 22 (01) :333-341
[9]   Day-Ahead Deregulated Electricity Market Price Forecasting Using Recurrent Neural Network [J].
Anbazhagan, S. ;
Kumarappan, N. .
IEEE SYSTEMS JOURNAL, 2013, 7 (04) :866-872
[10]  
[Anonymous], 2018, RENEWABLE ENERGIES B