Name
Abstract | ||
|---|---|---|
Volt/VAR optimization (VVO) is one important operation in distribution systems to maintain acceptable voltage profiles. However, the high penetration of renewable generation poses severe challenges to VVO, leading to voltage deviation and fluctuation. This is further complicated by the growing coupling between the electricity and natural gas systems. To resolve the unacceptable voltage deviation under energy system interdependency, this article proposes a cooptimization of VVO for an integrated electricity and gas system (IEGS) with uncertain renewable generation. A two-stage data-driven distributionally robust optimization is developed to model the coordinated optimization problem, which determines the two-stage VVO and operation schemes with dispatch and corrective adjustment through active power regulation and reactive power support in both day-ahead and real-time stage. A semidefinite programming is reformulated to ensure the tractability and the proposed problem is solved by a constraint generation framework. Simulation studies are conducted on a 33-bus-6-node IEGS. Case studies demonstrate that the interdependency between electricity and gas systems reduces the significant operation cost and voltage rise. It, thus, can benefit integrated system operators with a powerful operation tool to manage the systems with fewer costs but integrate more renewable energy while maintaining the high supply quality. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/JSYST.2020.2992583 | IEEE SYSTEMS JOURNAL |
Keywords | DocType | Volume |
Optimization, Reactive power, Uncertainty, Voltage control, Indexes, Natural gas, Pipelines, Data-driven optimization, distributionally robust optimization (DRO), integrated electricity and gas system (IEGS), two-stage framework, Volt, VAR optimization | Journal | 15 |
Issue | ISSN | Citations |
2 | 1932-8184 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pengfei Zhao | 1 | 10 | 9.72 |
| Chenghong Gu | 2 | 4 | 7.82 |
| Xiang, Y. | 3 | 8 | 2.25 |
| Xin Zhang | 4 | 591 | 60.75 |
| Yichen Shen | 5 | 1 | 1.37 |
| Shuangqi Li | 6 | 0 | 2.03 |