Sensitivity analysis in structured optimization problems methods and applications to power systems models
Abstract/Contents
- Abstract
- This work presents developments in differentiable optimization, with applications to the computation of marginal emissions in power system models. First, we discuss how recent results in differentiable optimization can be used readily to compute any emissions sensitivity metric (including marginal emissions) in optimization-based models. Second, we develop a general decentralized scheme for differentiation of graph-structured optimization problems. The methodology is efficient and can be made fully distributed, with convergence guarantees. Finally, we come full circle and illustrate the benefits of the decentralized framework in the computation of marginal emission factors. Using historical data, we demonstrate how the proposed approach allows for efficient computation of marginal emissions in large network models.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2024; ©2024 |
| Publication date | 2024; 2024 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Fuentes Valenzuela, Lucas Jose M |
|---|---|
| Degree supervisor | Pavone, Marco |
| Thesis advisor | Pavone, Marco |
| Thesis advisor | El Gamal, Abbas |
| Thesis advisor | Pilanci, Mert |
| Degree committee member | El Gamal, Abbas |
| Degree committee member | Pilanci, Mert |
| Associated with | Stanford University, School of Engineering |
| Associated with | Stanford University, Department of Electrical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Lucas Fuentes Valenzuela. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2024. |
| Location | https://purl.stanford.edu/dq253dd4135 |
Access conditions
- Copyright
- © 2024 by Lucas Jose M Fuentes Valenzuela
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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