Degree Type


Date of Award


Degree Name

Doctor of Philosophy


Electrical and Computer Engineering

First Advisor

Gerald B. Sheble


Under the framework developed in [Sheble, 1999a], this work simulates electric market dynamic using systems theory, decision analysis and decision theory. Activities of Generation Companies (GENCOs), the most active players in electric markets, and their impact on market performances are also examined. Decision-making of GENCOs and interactions between them are studied using decision analysis and decision theory.;The first part of this study studies electric market dynamics: dynamics of electricity price, generation output, and other variables. The problem is examined from the viewpoint of an Independent Contract Administrator (ICA) to simulate market performance and GENCOs' activities in different situations. These situations include various interactions among GENCOs (different expectations for competitors adopted by GENCOs), competition types (quantity competition, price competition, both price and quantity competition), market risk levels (decisions under certainty and uncertainty), and different market organizations (with and without certain market information feedback) in the electric market. Decision-making of GENCOs and interactions between them are modeled as control processes and electric markets are modeled as control systems. The corresponding market dynamics is simulated and market dynamic properties are obtained. Simulation results show that interactions between market participants, as well as market risk levels, competition types, and market organizations, are important to market participant's activities and have significant impact on market performances and properties.;The second part of this study is from GENCOs' viewpoint to develop optimal decision-making strategies and models in short term. First of all, GENCOs decision problem in short term in new deregulated environment is identified as a three-dimension problem: how to make optimal decisions for different time in different geographical markets in different service markets to maximize total gain. Then, a new market-based generation scheduling scheme is proposed to solve this problem. Market rules, competitor's activities, uncertainty in the market, bidding strategies, and short-term generation technical constraints are included in the scheme and analyzed using decision analysis and decision theory. Next, Dynamic Programming (DP) and Stochastic Dynamic Programming (SDP) are adopted to solve the new scheduling problems. Results show that in new environment, GENCOs' optimal generation schedules may be very different from schedules proposed in previous work. (Abstract shortened by UMI.)



Digital Repository @ Iowa State University,

Copyright Owner

Weiguo Yang



Proquest ID


File Format


File Size

116 pages