A robust must‐run capacity identifying approach in power system dispatch considering interdependence with natural gas system
| Title: | A robust must‐run capacity identifying approach in power system dispatch considering interdependence with natural gas system |
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| Authors: | Wenqi Wu, Yunpeng Xiao, Tao Hu, Xiuli Wang |
| Source: | IET Renewable Power Generation, Vol 18, Iss 16, Pp 3936-3943 (2024) |
| Publisher Information: | Wiley, 2024. |
| Publication Year: | 2024 |
| Collection: | LCC:Renewable energy sources |
| Subject Terms: | power generation dispatch, power generation economics, power generation scheduling, power markets, Renewable energy sources, TJ807-830 |
| More Details: | Abstract Identifying the must‐run capacity (MRC) could help to accelerate the unit commitment and assess market power, thus critical for achieving an efficient power system dispatch. However, the existing approaches identify the MRC without considering the ever‐strengthening interdependence between power system and natural gas (NG) system, as well as neglecting either the uncertainties of renewables or the constraints on start‐up/shut‐down states for thermal units. To fill the gaps, this article proposes a novel model and methodology for identifying the MRC in power system considering the interdependence with NG system, with adopting a distributionally robust (DR) approach to consider the uncertainties of renewables. A constraint‐generation based algorithm is devised to solve the model, with a relax‐round‐polish based Alternating Direction Method of Multipliers (ADMM) algorithm to address the interaction between the two energy systems. Comparative studies show the effectiveness in MRC assessment over the existing approaches. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 1752-1424 1752-1416 |
| Relation: | https://doaj.org/toc/1752-1416; https://doaj.org/toc/1752-1424 |
| DOI: | 10.1049/rpg2.13080 |
| Access URL: | https://doaj.org/article/a18e316681cd4369bf30f5c017fbf57f |
| Accession Number: | edsdoj.18e316681cd4369bf30f5c017fbf57f |
| Database: | Directory of Open Access Journals |
| ISSN: | 17521424 17521416 |
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| DOI: | 10.1049/rpg2.13080 |
| Published in: | IET Renewable Power Generation |
| Language: | English |