Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies
Abstract Electric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their rel...
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| Format: | Article |
| Language: | English |
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Wiley
2024-10-01
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| Series: | IET Renewable Power Generation |
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| Online Access: | https://doi.org/10.1049/rpg2.13063 |
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| author | Sunil Subedi Jesus D. Vasquez‐Plaza Fabio Andrade Hossein Moradi Rekabdarkolaee Robert Fourney Reinaldo Tonkoski Timothy M. Hansen |
| author_facet | Sunil Subedi Jesus D. Vasquez‐Plaza Fabio Andrade Hossein Moradi Rekabdarkolaee Robert Fourney Reinaldo Tonkoski Timothy M. Hansen |
| author_sort | Sunil Subedi |
| collection | DOAJ |
| description | Abstract Electric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their reliance on exact data about the distribution system and each of its components. Similarly, the use of the DER_A model, which is intended to examine the combined dynamic behavior of many DERs, is limited by the difficulty in parameterization. There is a need for improved dynamic models of DERs for use in large power system simulations for stability analysis. This paper proposes an aggregate model‐free, data‐driven approach for deriving a dynamic partitioned model (DPM) of ADNs. Detailed residential distribution feeders were first developed, including PEC‐based DERs and composite load models (CMLDs), from which the aggregated DPM was derived. The performance was evaluated through various case studies and validated against the detailed ADN model and state‐of‐the‐art DER_A model with CMLD. The data‐driven DPM achieved a fitpercent of over 90%, accurately representing the aggregated dynamic behavior of ADNs. Furthermore, the DPM significantly accelerated the simulation process with a computational speedup of 68 times compared to the detailed ADN and a 3.5 times speedup compared to the DER_A CMLD model. |
| format | Article |
| id | doaj-art-58873fe7e21f47e6b9e2b58e99888996 |
| institution | Kabale University |
| issn | 1752-1416 1752-1424 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Renewable Power Generation |
| spelling | doaj-art-58873fe7e21f47e6b9e2b58e998889962025-01-10T17:41:03ZengWileyIET Renewable Power Generation1752-14161752-14242024-10-0118142261227610.1049/rpg2.13063Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studiesSunil Subedi0Jesus D. Vasquez‐Plaza1Fabio Andrade2Hossein Moradi Rekabdarkolaee3Robert Fourney4Reinaldo Tonkoski5Timothy M. Hansen6Department of Electrical Engineering and Computer Science South Dakota State University Brookings South Dakota USAElectrical & Computer Engineering Department University of Puerto Rico Mayagüez Puerto Rico USAElectrical & Computer Engineering Department University of Puerto Rico Mayagüez Puerto Rico USAMathematics and Statistics Department South Dakota State University Brookings South Dakota USADepartment of Electrical Engineering and Computer Science South Dakota State University Brookings South Dakota USAElectric Power Transmission & Distribution Technical University of Munich Munich GermanyDepartment of Electrical Engineering and Computer Science South Dakota State University Brookings South Dakota USAAbstract Electric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their reliance on exact data about the distribution system and each of its components. Similarly, the use of the DER_A model, which is intended to examine the combined dynamic behavior of many DERs, is limited by the difficulty in parameterization. There is a need for improved dynamic models of DERs for use in large power system simulations for stability analysis. This paper proposes an aggregate model‐free, data‐driven approach for deriving a dynamic partitioned model (DPM) of ADNs. Detailed residential distribution feeders were first developed, including PEC‐based DERs and composite load models (CMLDs), from which the aggregated DPM was derived. The performance was evaluated through various case studies and validated against the detailed ADN model and state‐of‐the‐art DER_A model with CMLD. The data‐driven DPM achieved a fitpercent of over 90%, accurately representing the aggregated dynamic behavior of ADNs. Furthermore, the DPM significantly accelerated the simulation process with a computational speedup of 68 times compared to the detailed ADN and a 3.5 times speedup compared to the DER_A CMLD model.https://doi.org/10.1049/rpg2.13063DC‐AC power convertorsdistribution networkspower electronicspower system dynamic stability |
| spellingShingle | Sunil Subedi Jesus D. Vasquez‐Plaza Fabio Andrade Hossein Moradi Rekabdarkolaee Robert Fourney Reinaldo Tonkoski Timothy M. Hansen Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies IET Renewable Power Generation DC‐AC power convertors distribution networks power electronics power system dynamic stability |
| title | Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies |
| title_full | Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies |
| title_fullStr | Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies |
| title_full_unstemmed | Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies |
| title_short | Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies |
| title_sort | aggregate data driven dynamic modeling of active distribution networks with ders for voltage stability studies |
| topic | DC‐AC power convertors distribution networks power electronics power system dynamic stability |
| url | https://doi.org/10.1049/rpg2.13063 |
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