Title :
Electricity market price dynamics: Markov process analysis
Author :
Guti?©rrez-Alcaraz, G. ; Shebl?©, G.B.
Author_Institution :
Dept. of Electr. Eng. & Comput. Eng., Iowa State Univ., Ames, IA
Abstract :
Market dynamics have been studied with emphasis on price stability. Dynamic market pricing in a purely competitive environment for a given trading period is determined by the interaction of the supplier and buyer with information available to each. The scheduling of generation is determined according to a generation company´s (GENCOs) perception of the expected future conditions. Future conditions include equipment availability and competitor play. These decisions, which attempt to maximize profits, and the resulting interactions represents a major source of electric market dynamics. Profits in any period depend on level of efficiency as well as on the levels of efficiency of other competing GENCOs. Incorrect, untimely, and improperly analyzed information often lead to suboptimal solutions for the profit maximizing player, This paper analyzes market price dynamics by using Markov process (MP) modeling. An example application is presented as would be conducted by information seeking players to maximize profit. Key issues with applying Markov chains to different market conditions are identified. The key economic pricing signals, representing different forces, are examined as a basis of influencing these key decisions by each player
Keywords :
Markov processes; power generation economics; power generation scheduling; power markets; pricing; GENCO; Markov chain; Markov process modeling; competitor play; dynamic market pricing; economic pricing signal; equipment availability; generation company; generation scheduling; market dynamics; price stability; profit maximization; suboptimal solution; Aggregates; Contracts; Electricity supply industry; Environmental economics; Information analysis; Markov processes; Power generation economics; Power system modeling; Pricing; Stability analysis;
Conference_Titel :
Probabilistic Methods Applied to Power Systems, 2004 International Conference on
Print_ISBN :
0-9761319-1-9