Genetic algorithm evolution of utility bidding strategies for the competitive marketplace

Author

Richter, Charles W., Jr. ; Sheblé, Gerald B.

Author_Institution

Dept. of Electr. Eng. & Comput. Eng., Iowa State Univ., Ames, IA, USA

Volume

13

Issue

1

fYear

1998

fDate

2/1/1998 12:00:00 AM

Firstpage

256

Lastpage

261

Abstract

This paper describes an environment in which distribution companies (discos) and generation companies (gencos), buy and sell power via double auctions implemented in a regional commodity exchange. The electric utilities´ profits depend on the implementation of a successful bidding strategy. In this research, a genetic algorithm evolves bidding strategies as gencos and discos trade power. A framework in which bidding strategies may be tested and modified is presented. This simulated electric commodity exchange can be used offline to predict whether bid strategies will be profitable and successful. It can also be used to experimentally verify how bidding behavior affects the competitive electric marketplace

Keywords

economics; electricity supply industry; genetic algorithms; power systems; competitive marketplace; distribution companies; double auctions; electric utility bidding strategies; generation companies; genetic algorithm; regional commodity exchange; Distributed computing; Economic forecasting; Electricity supply industry deregulation; Genetic algorithms; Power engineering computing; Power generation; Power industry; Power system simulation; Senior members; Student members;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/59.651644

Filename

651644