State Estimation and Bad Data Detection in Hybrid AC/DC Systems with LCC/MMC
Based on the CIM/XML and CIM/E documents exported from the regional dispatching system, this paper focuses on data generation and starts by converting the exported documents into raw input data for state estimation. Considering the interactions between the AC system and LCC, MMC, and between LCC and...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
State Grid Energy Research Institute
2024-11-01
|
| Series: | Zhongguo dianli |
| Subjects: | |
| Online Access: | https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202307020 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Based on the CIM/XML and CIM/E documents exported from the regional dispatching system, this paper focuses on data generation and starts by converting the exported documents into raw input data for state estimation. Considering the interactions between the AC system and LCC, MMC, and between LCC and MMC, the unified iterative method is used to model the AC/DC state estimation of the 500kV subnetwork. Subsequently, the Gaussian noise is added to the original measurement data, and the maximum residual test method is employed for detecting and identifying bad data. Finally, the effectiveness of the proposed models for AC/DC state estimation and the detection and identification of bad data are validated through simulation data. |
|---|---|
| ISSN: | 1004-9649 |