DocumentCode :
1720259
Title :
Price-maker wind power producer participating in a joint day-ahead and real-time market
Author :
Delikaraoglou, Stefanos ; Papakonstantinou, Athanasios ; Ordoudis, Christos ; Pinson, Pierre
Author_Institution :
Dept. of Electr. Eng., Tech. Univ. of Denmark, Lyngby, Denmark
fYear :
2015
Firstpage :
1
Lastpage :
5
Abstract :
The large scale integration of stochastic renewable energy introduces significant challenges for power system operators and disputes the efficiency of the current market design. Recent research embeds the uncertain nature of renewable sources by modelling electricity markets as a two-stage stochastic problem, co-optimizing day-ahead and real-time dispatch. In this framework, we introduce a bilevel model to derive the optimal bid of a strategic wind power producer acting as price-maker both in day-ahead and real-time stages. The proposed model is a Mathematical Program with Equilibrium Constraints (MPEC) that is reformulated as a single-level Mixed-Integer Linear Program (MILP), which can be readily solved. Our analysis shows that adopting strategic behaviour may improve producer´s expected profit as the share of wind power increases. However, this incentive diminishes in power systems where available flexible capacity is high enough to ensure an efficient market operation.
Keywords :
integer programming; linear programming; power generation dispatch; power generation economics; power markets; stochastic programming; wind power; MILP model; MPEC model; day-ahead and real-time dispatch cooptimization; joint day-ahead and real-time electricity market; mathematical program with equilibrium constraint; power system operation; single-level mixed integer linear program; stochastic renewable energy; two-stage stochastic problem; wind power production; Electricity supply industry; Power systems; Production; Real-time systems; Stochastic processes; Uncertainty; Wind power generation; Electricity markets; mathematical program with equilibrium constraints (MPEC); price-maker; stochastic programming; wind power;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
European Energy Market (EEM), 2015 12th International Conference on the
Conference_Location :
Lisbon
Type :
conf
DOI :
10.1109/EEM.2015.7216701
Filename :
7216701
Link To Document :
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