Electricity Price Forecasting Considering Residual Demand

被引:0
|
作者
Motamedi, A. [1 ]
Geidel, C. [2 ]
Zareipour, H. [3 ]
Rosehart, W. D. [3 ]
机构
[1] AESO, Grid & Market Operat Dept, Calgary, AB, Canada
[2] Tech Univ Berlin, Dept Elect cal Engn & Comp Sci, Berlin, Germany
[3] Univ Calgary, Dept Elect & Comp Engn\, Calgary, AB, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Price forecasting; residual demand; smart grid; wind power; MARKET; SYSTEMS; IMPACT;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this paper, short-term electricity price forecasting considering residual electricity demand is investigated. Residual, or net, demand is determined by subtracting any unpredictable generation from the system load. Focusing on wind energy as the main hard-to-predict source of electricity, we first examine the dependency of short-term electricity prices and wind power using data association mining algorithms. Second, we investigate the impact of including net demand in short-term electricity price forecasting, and we propose a new electricity price forecasting model. Data from the Alberta and the Nordic electricity markets are used to conduct studies and evaluate the forecasting results.
引用
收藏
页数:8
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