Davide Gotti published this dataset on 2024-05 05 as complementary material for a topology identification method. It includes input measurements, binary classification outputs, D+ elements, and PowerFactory source files for the modified New England and IEEE 118-bus test systems.
Use Cases
- Training and testing machine learning models for topology identification based on the provided input measurements.
- Analyzing the performance of topology processing algorithms using the supplied binary classification outputs.
- Studying the characteristics of the modified New England and IEEE 118-bus test systems via the included PowerFactory source files.
- Investigating the role of D+ elements in power system stability and state estimation.
Strengths
- Includes source files for two established power system test cases: the modified New England and IEEE 118-bus systems.
- Dataset is directly linked to a specific research paper, providing clear context for its intended use.
- Last updated on 2024-05-05, indicating recent maintenance.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment for large-scale model training.
- Description metadata is limited; actual data quality requires manual inspection after download.
Provenance
- Source
- e-cienciaDatos Harvested Dataverse
- Collection Method
- Likely generated as part of the research for the paper "A Fast Data-Driven Topology Identification Method for Dynamic State Estimation Applications".
- Time Range
- null
- Freshness
- Last updated 2024-05-05 07:43:25
- Geography
- null