Title :
Optimal bidding strategies for generation companies in electricity markets with transmission capacity constraints taken into account
Author :
Ma, Li ; Wen, Fushuan ; Ni, Yixin ; Wu, F.F.
Author_Institution :
Zhejiang Univ., Hangzhou, China
Abstract :
In the electricity market environment, how to build optimal bidding strategies has become a major concern for generation companies. The deficiency of transmission capacity could lead to congestion, and as a result, the whole electricity market can then be actually divided into two or more submarkets. A direct consequence of transmission congestion is the change of competitive positions of generation companies concerned in the electricity market, and the optimal bidding strategies of them should accordingly be changed. In this paper, the problem of developing optimal bidding strategies for generation companies is systematically investigated with transmission capacity constraints taken into account. A stochastic optimization model is first formulated under the presumption that the bidding behaviors of rival generation companies could be modeled as normal probability distributions. An approach is next presented for solving the optimization problem using the well-known Monte Carlo simulation method and the genetic algorithm. Finally, a simple sample example and the modified IEEE 14-bus system are employed to illustrate the essential features of the proposed model and method.
Keywords :
Monte Carlo methods; electricity supply industry; genetic algorithms; normal distribution; power markets; stochastic programming; Monte Carlo simulation method; electricity market environment; generation company; genetic algorithm; normal probability distribution; optimal bidding strategy; stochastic optimization model; transmission capacity deficiency; transmission congestion management; Dispatching; Electricity supply industry; Energy management; Genetic algorithms; Iron; Power generation; Power markets; Power system management; Power system planning; Power system security;
Conference_Titel :
Power Engineering Society General Meeting, 2003, IEEE
Print_ISBN :
0-7803-7989-6
DOI :
10.1109/PES.2003.1271056