Distributionally Robust Unit Commitment with Flexible Generation Resources Considering Renewable Energy Uncertainty

Abstract

As the penetration of intermittent renewable energy increases in bulk power systems, flexible generation resources, such as quick-start gas units, become important tools for system operators to address the power imbalance problem. To better capture their flexibility, we proposed a distributionally robust unit commitment framework with both regular and flexible generation resources, in which the unit commitment decisions for flexible generation resources can be adjusted in the second stage to accommodate the renewable energy intermittency. In order to tackle this two-stage distributionally robust mixed-binary model, to which traditional separation algorithms wont apply, we designed an integer L-shaped algorithm with advanced cutting plane techniques. In comparison to the traditional distributionally robust unit commitment, the proposed approach can reduce the system cost through an improved flexible resource quantification in the modeling.

Department(s)

Electrical and Computer Engineering

Publication Status

Early Access

Comments

This work was partially supported by National Science Foundation (NSF) under Grants 2045978 and 2046243.

Keywords and Phrases

Costs; Distributionally Robust Optimization; Flexible Generation Resources; Measurement; Probability Distribution; Random Variables; Renewable Energy Sources; Renewable Energy Uncertainty; System Flexibility; Transmission Line Matrix Methods; Two-Stage Mixed-Binary Linear Program; Uncertainty; Unit Commitment

International Standard Serial Number (ISSN)

1558-0679; 0885-8950

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2022 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jan 2022

Link to Full Text

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