Cramer, E;
Paeleke, L;
Mitsos, A;
Dahmen, M;
(2022)
Normalizing flow-based day-ahead wind power scenario generation for profitable and reliable delivery commitments by wind farm operators.
Computers & Chemical Engineering
, 166
, Article 107923. 10.1016/j.compchemeng.2022.107923.
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Abstract
We present a specialized scenario generation method that utilizes forecast information to generate scenarios for day-ahead scheduling problems. In particular, we use normalizing flows to generate wind power scenarios by sampling from a conditional distribution that uses wind speed forecasts to tailor the scenarios to a specific day. We apply the generated scenarios in a stochastic day-ahead bidding problem of a wind electricity producer and analyze whether the scenarios yield profitable decisions. Compared to Gaussian copulas and Wasserstein-generative adversarial networks, the normalizing flow successfully narrows the range of scenarios around the daily trends while maintaining a diverse variety of possible realizations. In the stochastic day-ahead bidding problem, the conditional scenarios from all methods lead to significantly more stable profitable results compared to an unconditional selection of historical scenarios. The normalizing flow consistently obtains the highest profits, even for small sets scenarios.
| Type: | Article |
|---|---|
| Title: | Normalizing flow-based day-ahead wind power scenario generation for profitable and reliable delivery commitments by wind farm operators |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.compchemeng.2022.107923 |
| Publisher version: | https://doi.org/10.1016/j.compchemeng.2022.107923 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Wind power, Scenario generation, Stochastic programming, Stability |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10212577 |
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