Electrical & Computer Engineering, Department of
First Advisor
Wei Qiao
Second Advisor
Liyan Qu
Date of this Version
5-2024
Document Type
Article
Citation
A thesis presented to the faculty of the Graduate College at the University of Nebraska in partial fulfillment of requirements for the degree of Master of Science
Major: Electrical Engineering
Under the supervision of Professors Wei Qiao and Liyan Qu
Lincoln, Nebraska, May 2024
Abstract
Wind power is one of the world's fastest-growing renewable energy resources and has expanded quickly within the US electric grid. Currently, wind power producers (WPPs) may sell energy products in US markets but are not allowed to sell reserve products, due to the uncertain and intermittent nature of wind power. However, as wind’s share of the power supply grows, it may eventually be necessary for WPPs to contribute to system-wide reserves. This paper proposes a stochastic optimization model to determine the optimal offer strategy for a WPP that participates in the day-ahead and real-time energy and spinning reserve markets. The objective function maximizes the WPP’s total expected profit while minimizing risk by allowing the WPP to split its offers between the energy market and the spinning reserve market, which has lower penalties for failing to deliver the cleared day-ahead offer. Risk is considered through the Conditional Value at Risk metric and several risk aversion levels are studied. Case study results show that the proposed offer strategy increases expected profit and decreases risk compared to the case where the WPP only participates in the energy market.
Advisors: Wei Qiao and Liyan Qu
Included in
Applied Mathematics Commons, Computer Engineering Commons, Corporate Finance Commons, Entrepreneurial and Small Business Operations Commons, Finance and Financial Management Commons, International Business Commons, Oil, Gas, and Energy Commons, Other Economics Commons, Other Electrical and Computer Engineering Commons, Risk Analysis Commons, Sustainability Commons
Comments
Copyright 2024, Anne Stratman. Used by permission