Masters Theses

Keywords and Phrases

Electricity markets; Hedging; Markowitz Optimization; Microgrid; Risk; Uncertainty


"After deregulation of electricity in the United States, the day-ahead and real-time markets allow load serving entities and generation companies to bid and purchase/sell energy under the supervision of the independent system operator (ISO). The electricity market prices are inherently uncertain, and can be highly volatile. The main objective of this thesis is to hedge against the risk from the uncertainty of the market prices when purchasing/selling energy from/to the market. The energy manager can also schedule distributed generators (DGs) and storage of the microgrid to meet the demand, in addition to energy transactions from the market. The risk measure used in this work is the variance of the uncertain market purchase/sale cost/revenue, assuming the price following a Gaussian distribution. Using Markowitz optimization, the risk is minimized to find the optimal mix of purchase from the markets. The problem is formulated as a mixed integer quadratic program. The microgrid at Illinois Institute of Technology (IIT) in Chicago, IL was used as a case study. The result of this work reveals the tradeoff faced by the microgrid energy manager between minimizing the risk and minimizing the mean of the total operating cost (TOC) of the microgrid. With this information, the microgrid energy manager can make decisions in the day-ahead and real-time markets according to their risk aversion preference. The assumption of market prices following Gaussian distribution is also verified to be reasonable for the purpose of hedging against their risks. This is done by comparing the result of the proposed formulation with that obtained from the sample market prices randomly generated using the distribution of actual historic market price data"--Abstract, page iii.


Joo, Jhi-Young

Committee Member(s)

Ferdowsi, Mehdi
Shamsi, Pourya


Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering


Missouri University of Science and Technology

Publication Date

Summer 2016


vii, 30 pages

Note about bibliography

Includes bibliographical references (pages 28-29).


© 2016 Sriram Raghavan, All rights reserved.

Document Type

Thesis - Open Access

File Type




Subject Headings

Hedging (Finance) -- Prices -- Econometric models
Financial risk management
Electric utilities -- Rates

Thesis Number

T 10976

Electronic OCLC #