Title :
Generator bidding in oligopolistic electricity markets using optimal control: Fundamentals and application
Author :
Youfei Liu ; Wu, F.F.
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of Hong Kong, Hong Kong, China
Abstract :
In this paper, optimal control is applied to study generator bidding in an oligopolistic electricity market. The repeated bidding process in (hourly-based) real-time electricity markets is modeled as a dynamic feedback system; an optimal control problem is then formulated to explore individual generator´s long-term/multiperiod optimization behavior. Particularly in our formulation, the periodic property of the system demand is considered. Several lemmas are included for concerning system stability. Based on the necessary conditions for optimality from the Pontryagin maximum principle, a sweeping method is proposed, and an optimal state-feedback control rule is then obtained via backward induction. Numerical results suggest that the generator who unilaterally applies optimal control for generation decisions will obtain more profits. A sensitivity analysis is also performed, identifying these market factors that affect the performance of optimal control.
Keywords :
optimal control; optimisation; power generation control; power generation economics; power markets; sensitivity analysis; state feedback; Pontryagin maximum principle; backward induction; dynamic feedback system; generator bidding process; generator long-term optimization behavior; multiperiod optimization behavior; oligopolistic electricity markets; optimal control problem; optimal state-feedback control rule; power system stability; real-time electricity markets; repeated bidding process; sensitivity analysis; sweeping method; Electricity supply industry; Generators; Optimal control; Optimization; Power system dynamics; Stability analysis; Vectors; Generator bidding; linear periodic system; oligopolistic electricity markets; optimal control; sensitivity analysis;
Conference_Titel :
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-2727-5
Electronic_ISBN :
1944-9925
DOI :
10.1109/PESGM.2012.6344662