In this dissertation our objective is to characterize and measure the impact of various sources of uncertainty in the electricity market from the end-user perspective and develop optimization methodologies to mitigate the final impact.
In Chapter 2, we study interruptible load contracts from the perspective of a participating manufacturing company. We develop a production planning frame- work that mitigates the uncertainty created by the contractual clauses. We present a mathematical modeling approach and computational results.
In Chapter 3, we conduct an experiment using real time electricity prices from the two regional U.S. markets to test the for inherent patterns in real-time locational marginal prices (LMPs) that could be used for constructing the uncertainty sets for the optimization problems. We present the statistical results and findings to characterize these patterns. Next, another experiment is conducted to compare the information content of various data selection rules and the accuracy of various forecasting techniques.
In Chapter 4, we conduct an experiment to quantify the value of information using two problem classes: the production planning problem and the job shop scheduling problem. We present various mathematical models to represent a limited set of protoypical optimization problems for each problem class, a comparison of various methods that can be used to construct these optimization problems, simulations of these models with real prices, and finally a numerical analysis of the impact of price uncertainty on optimal solutions. In this chapter, the value of information is quantified as the reflection of the price uncertainty on the optimal objective function value's deviation from a solution obtained by solving an optimization problem with imperfect information.
Our findings indicate that depending on the production and the manufacturing environment, the impact of the price uncertainty on the optimal solutions varies significantly. Without conducting a similar analysis to ours, negotiating terms and prices purely based on price uncertainty may be speculative, illusory and misleading for the contract taking parties.
|Advisor:||Snyder, Lawrence V., Belotti, Pietro|
|Commitee:||Kishore, Shalinee, Ralphs, Theodore K.|
|School Location:||United States -- Pennsylvania|
|Source:||DAI-B 74/03(E), Dissertation Abstracts International|
|Keywords:||Empirical study, Isone, Job shop scheduling, Pjm, Power procurement portfolios, Production planning|
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