Title :
The best bidding price based on Ant Colony Algorithm in electric power market
Author :
Li, Shan ; Gao, Liang ; Xu, Gang
Author_Institution :
Dept. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing, China
Abstract :
In electric power market, the research of best bidding price is an important study, in which the calculation and description of node price is the key issue. Based on the highly effective ant colony algorithm, this paper proposes a methodology of best bidding for solving the optimal price model of the electric power market. We use the random global search capability of ant colony algorithm to deal with the constraints of power system operation and solve the optimization problem between power producers bidding and consumers demand, to estimate the wholesale or retail price in the electricity market. Finally, we use the IEEE 30 - bus test system as a pilot system to test the proposed methodology, and the test results and analysis show that the computational model has a certain degree of practical significance in our electric power market.
Keywords :
optimisation; power markets; search problems; IEEE 30-bus test system; ant colony algorithm; best bidding price; electric power market; node price; optimal price model; pilot system; power system operation constraint; random global search capability; Ant colony optimization; Constraint optimization; Consumer electronics; Cost function; Electricity supply industry; Guidelines; Power engineering and energy; Power system modeling; Power systems; System testing; Ant Colony Algorithm; Bidding price; Electric power market; Nodal price;
Conference_Titel :
Sustainable Power Generation and Supply, 2009. SUPERGEN '09. International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4934-7
DOI :
10.1109/SUPERGEN.2009.5348327
