Partially Affine Policy for Multistage Robust Unit Commitment with Fast-Ramping Units

Zhongjie Guo; Jiayu Bai; Wei Wei; Shengwei Mei; Weihao Hu

doi:10.17775/CSEEJPES.2023.08300

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Partially Affine Policy for Multistage Robust Unit Commitment with Fast-Ramping Units

Regular Papers | 更新时间：2026-10-15

- Partially Affine Policy for Multistage Robust Unit Commitment with Fast-Ramping Units
- CSEE Journal of Power and Energy Systems Vol. 11, Issue 1, Pages: 477-480(2025)
- 作者机构：
  
  1. School of Mechanical, and Electrical Engineering, University of Electronic Science and Technology of China,Chengdu,China
  2. State Grid Sichuan Electric Power Research Institute,Sichuan,China
  3. Department of Electrical Engineering, Tsinghua University,Beijing,China
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2023.08300
  CLC：
- Published：01 January 2025
- 稿件说明：
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Zhongjie Guo, Jiayu Bai, Wei Wei, et al. Partially Affine Policy for Multistage Robust Unit Commitment with Fast-Ramping Units[J]. CSEE Journal of Power and Energy Systems, 2025, 11(1): 477-480.
DOI：

Zhongjie Guo, Jiayu Bai, Wei Wei, et al. Partially Affine Policy for Multistage Robust Unit Commitment with Fast-Ramping Units[J]. CSEE Journal of Power and Energy Systems, 2025, 11(1): 477-480. DOI： 10.17775/CSEEJPES.2023.08300.

摘要

Abstract

Multistage robust unit commitment (MRUC) is an important decision-making problem in power system operations. The affine policy facilitates problem-solving

but it compromises flexibility. This letter proposes a partially affine policy for MRU C problem with fast-ramping units; this policy imposes affine relations to coupling variables only and leaves the remaining variables to be optimized in the real-time dispatch. As a result

the real-time flexibility of fast-ramping units is retained. By adopting this approach

MRU C with a partially affine policy becomes a special two-stage adaptive robust optimization problem. Numerical tests verify that the proposed partially affine policy significantly reduces the conservativeness compared with affine policy

improving the dispatch economy and flexibility.

关键词

Keywords

references

12. Z. J. Guo. ( 2023 ). Online appendix-CCG algorithm for MRUC-PAF. [Online] . Available: https://github.comlZhongjieGuo/Papers.

13. Z. J. Guo. ( 2023 ). PAF-data. [Online] . Available: https://github.comlZhongjieGuo/Papers.

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