Title :
Stochastic cournot model for wind power trading in electricity markets
Author :
Sharma, Kailash Chand ; Bhakar, Rohit ; Padhy, Narayana Prasad
Author_Institution :
Dept. of Electr. Eng., Malaviya Nat. Inst. of Tech. Jaipur, Jaipur, India
Abstract :
In evolving electricity markets, wind generators would submit bids to the system operator, with an aim to maximize their profits. Generation offered by wind firms is highly random, which may result into heavy imbalance charges. In markets dominated by wind generators, they would optimize their offered bids, considering rival behavior. In oligopolistic electricity markets, this strategic behavior can be represented as a Stochastic Cournot model. Wind uncertainty is represented by scenarios generated using Auto Regressive Moving Average (ARMA) model. With a consideration of wind power uncertainty and imbalance cost, the expected profit of generators is calculated for a practical case study of wind firms located at Massachusetts, USA. Nash equilibrium is obtained using payoff matrix approach. This bidding strategy mechanism offers quantum increase in profit for wind firms, when their behavior is modeled in a game theoretic framework. Flexibility of approach offers opportunities for its extension to associated challenges.
Keywords :
autoregressive moving average processes; power generation economics; power markets; profitability; wind power plants; ARMA model; Massachusetts; Nash equilibrium; USA; autoregressive moving average; bidding strategy mechanism; electricity markets; game theoretic framework; imbalance cost; oligopolistic electricity markets; payoff matrix approach; stochastic Cournot model; system operator; wind firms; wind generators; wind power trading; wind power uncertainty; Electricity supply industry; Generators; Mathematical model; Nash equilibrium; Stochastic processes; Uncertainty; Wind power generation; Electricity Markets; Nash Equilibrium; Stochastic Cournot Model; Wind Power Uncertainty;
Conference_Titel :
PES General Meeting | Conference & Exposition, 2014 IEEE
Conference_Location :
National Harbor, MD
DOI :
10.1109/PESGM.2014.6939299