| Autor: |
Moudud Ahmed, Arash Vahidnia, Manoj Datta, Lasantha Meegahapola |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 8, Pp 69482-69495 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2020.2985978 |
| Popis: |
High penetration of dynamic loads, such as induction motors (IMs) could give rise to sustained voltage/frequency and power oscillations in hybrid AC/DC microgrids during disturbances. Majority of the published literature has investigated these stability issues with aggregated models of IMs in hybrid AC/DC microgrids, which do not properly reflect the actual dynamics of parallel operating IMs; hence, power oscillation damping (POD) controllers must be designed explicitly considering various oscillations induced by parallel operating IMs. This paper proposes an adaptive neuro-fuzzy inference system (ANFIS) based POD controller to damp low-frequency oscillations (LFOs) induced by IMs in hybrid AC/DC microgrids. The proposed supplementary POD controller was embedded to the energy storage system (ESS) controller, which provides additional damping power proportional to the frequency deviation. The following two features namely: 1) ability to adjust the gain based on the frequency deviation, and 2) ability to handle more non-linearity in the system dynamics, make the proposed adaptive ANFIS based POD controller more unique compared to conventional POD controllers. The effectiveness of the proposed ANFIS-POD controller is verified using non-linear dynamic simulations considering a range of disturbances in a hybrid AC/DC microgrid and different combinations of parallel operating IMs. Results indicate improved oscillatory stability performance in the hybrid AC/DC microgrid with the proposed ANFIS-POD controller. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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