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http://hdl.handle.net/11531/100633| Title: | Data-driven continuous-time framework for frequency-constrained unit commitment |
| Authors: | Rajabdorri, Mohammad Lobato Miguélez, Enrique Sigrist, Lukas Aghaei, Jamshid |
| Issue Date: | 1-Nov-2024 |
| Abstract: | The conventional approach to solving the unit commitment problem involves discrete intervals at an hourly scale, particularly when integrating frequency dynamics to formulate a frequency-constrained unit commitment. To overcome this limitation, a novel continuous-time frequency-constrained unit commitment framework is proposed in this paper. In this approach, Bernstein polynomials represent continuous variables in the unit commitment problem and enable the calculation of frequency response-related metrics such as the rate of change of frequency, quasi-steady-state frequency, and frequency nadir, and the corresponding continuous-time constraints are introduced. Notably, startup and shut-down trajectories are meticulously considered, transforming the formulation into a fully continuous-time model and simplifying constraints related to variable continuity. To address the complexities associated with integrating the obtained non-linear frequency nadir constraint into a mixed-integer linear problem, an alternative data-driven frequency nadir constraint is proposed, which accurately constrains frequency nadir deviations throughout the time interval. To validate the proposed model, it is applied to the real-life network of the Spanish Island of La Palma. The data-driven method for estimating frequency nadir has demonstrated a minimum accuracy of 99.61 and has consistently maintained the frequency above the defined threshold. |
| Description: | Artículos en revistas |
| URI: | https:doi.org10.1016j.ijepes.2024.110327 http://hdl.handle.net/11531/100633 |
| ISSN: | 0142-0615 |
| Appears in Collections: | Artículos |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| IIT-24-316R | 2,7 MB | Unknown | View/Open | |
| IIT-24-316R_preview | 3,52 kB | Unknown | View/Open |
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