A Dynamic Active Distribution Network Equivalent for Enhancing the Generalization Capability of the Exponential Recovery Model in Stability Studies
| Autor: | Hendrik Lens, Georgios Mitrentsis |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
business.industry
Computer science Generalization 020209 energy Energy Engineering and Power Technology 02 engineering and technology Stability (probability) Field (computer science) Power (physics) Exponential function Nonlinear system Control theory Distributed generation 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Scenario testing business |
| Zdroj: | IEEE Transactions on Power Systems. 36:2709-2712 |
| ISSN: | 1558-0679 0885-8950 |
| DOI: | 10.1109/tpwrs.2021.3053137 |
| Popis: | This letter introduces an enhancement of the exponential recovery model (ERM) in order to widen its applicability and generalization capability from purely load-composed distribution networks to active distribution networks (ADNs), while maintaining its nonlinear characteristics. Although recent approaches proposed modifications of the ERM to tackle its limitation to capture bidirectional power flows, these may fail to generalize to new test scenarios with significant distributed generation (DG) due to their direct dependence on the measured power at the point of common coupling. In ADNs, this value does not represent the actual power demand of the loads. To address this issue, a new methodology based on nonlinear functions and the actual change of the signals is presented. The efficacy of the proposed model to capture the general ADN dynamics is validated using field measurements acquired over one year. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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