DocumentCode :
2676093
Title :
A probability model for the electricity price duration curve under an oligopoly market
Author :
Valenzuela, Jorge ; Maxumdar, M.
Author_Institution :
Auburn Univ., AL
fYear :
0
fDate :
0-0 0
Abstract :
Summary form only given. In this paper, we propose a new formulation for the "price duration curve" (PDC) using probability considerations and provide a procedure for constructing it. This curve is expected to be useful in the long-term prediction of market prices and is similar in spirit to the load duration curve. It shows the proportion of time over a given time horizon during which the real-time market price of electricity is expected to exceed specified dollar amounts. The price over a long term is a stochastic quantity that depends on physical factors such as production cost, load, generation availability, unit commitment, and transmission constraints. It also depends on economic factors such as strategic bidding and load elasticity. We illustrate a procedure for constructing a stochastic system-based model for the PDC, taking into account the randomness associated with load and generator outages. The effects of unit commitment, transmission congestion, and transmission outages are not considered. We use two economic models. One is due to Bertrand and represents perfect competition. The other model is due to Rudkevich who have given a closed-form expression for the market-clearing price in an oligopoly consisting of several identical firms
Keywords :
oligopoly; power markets; power system economics; pricing; probability; stochastic processes; electricity price duration curve; generator outages; load duration curve; load elasticity; load outages; long-term prediction; market prices; market-clearing price; oligopoly market; probability model; stochastic quantity; stochastic system; strategic bidding; transmission congestion; transmission outages; unit commitment; Availability; Closed-form solution; Costs; Economic forecasting; Elasticity; Oligopoly; Power system economics; Production; Stochastic processes; Stochastic systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering Society General Meeting, 2006. IEEE
Conference_Location :
Montreal, Que.
Print_ISBN :
1-4244-0493-2
Type :
conf
DOI :
10.1109/PES.2006.1709124
Filename :
1709124
Link To Document :
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