Degree Type

Thesis

Date of Award

2007

Degree Name

Master of Science

Department

Electrical and Computer Engineering

First Advisor

Chen-Ching Liu

Abstract

The Day-Ahead electricity market is modeled as a multi-agent system with interacting agents including supplier agents, Load Serving Entities, and a Market Operator. Simulation of the market clearing results under the scenario in which agents have learning capabilities is compared with the scenario where agents report true marginal costs. It is shown that, with Q-Learning, electricity suppliers are making more profits compared to the scenario without learning due to strategic gaming. As a result, the LMP at each bus is substantially higher.

DOI

https://doi.org/10.31274/rtd-180813-15826

Publisher

Digital Repository @ Iowa State University, http://lib.dr.iastate.edu/

Copyright Owner

Nanpeng Yu

Language

en

Proquest ID

AAI1447491

OCLC Number

224515936

ISBN

9780549334200

File Format

application/pdf

File Size

40 pages

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