Parameter optimization of reactive power device planning in hybrid AC/DC networks based on objective‐oriented scenario selection method
| Title: | Parameter optimization of reactive power device planning in hybrid AC/DC networks based on objective‐oriented scenario selection method |
|---|---|
| Authors: | Tao Niu, Wenguo Wu, Sidun Fang, Fan Li, Guanhong Chen |
| Source: | IET Renewable Power Generation, Vol 17, Iss 14, Pp 3457-3470 (2023) |
| Publisher Information: | Wiley, 2023. |
| Publication Year: | 2023 |
| Collection: | LCC:Renewable energy sources |
| Subject Terms: | HVDC power transmission, power system planning, Renewable energy sources, TJ807-830 |
| More Details: | Abstract As one of the most common voltage/var‐related contingencies, commutation failures in hybrid AC/DC networks deteriorate the voltage profiles. Thus, systems may suffer from large‐scale cascading risks induced by the lack of dynamic reactive power support. Conventional power system planning usually aims to optimize the device capacity and location, ignoring the influences of intrinsic device parameters on high‐voltage direct current (HVDC) dynamics during commutation failures. If the intrinsic device parameters are also taken into account in the planning problem, it would allow for faster dynamic voltage/var support during system faults or disturbances to recover from voltage drops. However, considering the intrinsic parameters, allocations and capacities of a device, the optimal planning problem brings several challenges, such as scenario selections and computational burdens. To overcome these issues, an objective‐oriented scenario selection based power system planning approach is proposed in this paper. First, the detailed operations of converter stations are formulated both considering the steady state and system dynamics. Next, the quantitative relation between the power losses and deviation in system conditions is then derived to approximately describe the operational characteristics. Then, an objective‐oriented representative scenario selection method is introduced, aiming to reduce the number of selected scenarios, guaranteeing both computational accuracy and efficiency. Finally, a modified IEEE‐118 system is used to test the proposed algorithm, and the superiority and computational efficiency are observed by the simulation results. |
| 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/rpg2.12810 |
| Access URL: | https://doaj.org/article/0333b391aed94d6b85eae32ec2a5749b |
| Accession Number: | edsdoj.0333b391aed94d6b85eae32ec2a5749b |
| Database: | Directory of Open Access Journals |
| ISSN: | 17521424 17521416 |
|---|---|
| DOI: | 10.1049/rpg2.12810 |
| Published in: | IET Renewable Power Generation |
| Language: | English |