Risk-sensitive optimization for power systems

Madavan, Avinash N.

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https://hdl.handle.net/2142/117802 Copy

Description

Title

Risk-sensitive optimization for power systems

Author(s)

Madavan, Avinash N.

Issue Date

2022-11-30

Director of Research (if dissertation) or Advisor (if thesis)

Bose, Subhonmesh

Doctoral Committee Chair(s)

Bose, Subhonmesh

Committee Member(s)

• Basar, Tamer
• Srikant, Rayadurgam
• Dominguez-Garcia, Alejandro D
• Tong, Lang

Department of Study

Electrical & Computer Eng

Discipline

Electrical & Computer Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• risk-sensitive optimization
• conditional value at risk
• power systems
• electricity markets

Abstract

In this thesis, we study methods of incorporating uncertainty, whether it be discrete component failures or continuous variability in renewable energy, explicitly in decision-making for power systems operations and planning. We model this uncertainty in a risk-sensitive fashion using the conditional value at risk measure, presenting formulations to capture these uncertainties, as well as market design around them. We then study algorithms to solve such problems, in a more general form, exploring decomposition-based approaches such as critical region exploration and Benders' decomposition to handle discrete uncertainty, and a stochastic approximation approach to handle continuous uncertainty.

Graduation Semester

2022-12

Type of Resource

Thesis

Copyright and License Information

Copyright 2022 Avinash Madavan

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