DocumentCode
2133937
Title
Bidding wind power in short-term electricity market based on multiple-objective fuzzy optimization
Author
Xue, Yaosuo ; Venkatesh, Bala ; Chang, Liuchen
Author_Institution
Dept. of Electr. & Comput. Eng., New Brunswick Univ., Fredericton, NB
fYear
2008
fDate
4-7 May 2008
Abstract
Wind energy is promising with no fuel cost and zero greenhouse gas emissions; however, its intermittent and volatile nature has added much to operation burdens and thus a low penetration level in short-term or spot market. On the one hand, the power system operator is facing increased spinning reserve and generation uncertainty; on the other hand, the wind independent power producer (IPP) is subject to imbalance penalties in the balancing market. Previous literatures solely focused on maximizing the profit for a wind IPP formulating optimal bidding strategies without the consideration of operator side. This paper proposes a multiple-objective optimal bidding strategy to achieve both wind IPPpsilas maximum profit and less challenge for the operator. The strategy is formulated as a mixed-integer linear programming (MILP) problem with fuzzy optimization techniques. Analytic and numerical solutions will be given with discussion on risk control.
Keywords
fuzzy set theory; linear programming; power generation economics; power markets; wind power plants; IPP; MILP; bidding wind power; mixed-integer linear programming; multiple-objective fuzzy optimization; numerical solutions; power system operator; risk control; short-term electricity market; spinning reserve; wind independent power producer; Costs; Electricity supply industry; Fuels; Global warming; Power generation; Power systems; Spinning; Uncertainty; Wind energy; Wind energy generation; Optimal bidding strategy; fuzzy optimization; mixed-integer linear programming; wind power;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on
Conference_Location
Niagara Falls, ON
ISSN
0840-7789
Print_ISBN
978-1-4244-1642-4
Electronic_ISBN
0840-7789
Type
conf
DOI
10.1109/CCECE.2008.4564715
Filename
4564715
Link To Document