On the Assessment of Slow Voltage Variations in Electric Distribution Networks using K-Means Clustering Algorithm |
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| Gheorghe Grigoras, Bogdan-Constantin Neagu, Alexandra Adăscăliței |
- Abstract:
- The paper presents a clustering based analysis for the assessment of slow voltage variations from the electric distribution networks. The analysis uses the K-means clustering algorithm for classifying the electric substations (Medium Voltage/Low Voltage – MV/LV) in patterns characterized by linguistic terms from the point of view of slow voltage variations. The patterns were obtained using as input data in the clustering process the voltage quality indices (average deviation, average square deviation, and voltage irregularity degree). The analysis was made on a large supply zone with 722 electric distribution substations divided in three areas (remote, close, and suburb). The results confirmed the robustness and efficiency of proposed approach in the analysis of databases with a high amount of information insured by measurement devices.
- Keywords:
- voltage quality,slow voltage variation, electric distribution networks, K-means clustering
- Download:
- IMEKO-TC4-2017-026.pdf
- DOI:
- -
- Event details
- IMEKO TC:
- TC4
- Event name:
- TC4 Symposium 2017
- Title:
22nd IMEKO TC4 Symposium and 20th International Workshop on ADC Modelling and Testing
"Supporting world development through electric&electronic measurements"- Place:
- Iasi, ROMANIA
- Time:
- 14 September 2017 - 15 September 2017