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Phasor Estimation for Grid Power Monitoring: Least Square vs. Linear Kalman Filter
| Content Provider | MDPI |
|---|---|
| Author | Amirat, Yassine Oubrahim, Zakarya Ahmed, Hafiz Benbouzid, Mohamed Wang, Tianzhen |
| Copyright Year | 2020 |
| Description | This paper deals with a comparative study of two phasor estimators based on the least square (LS) and the linear Kalman filter (KF) methods, while assuming that the fundamental frequency is unknown. To solve this issue, the maximum likelihood technique is used with an iterative Newton–Raphson-based algorithm that allows minimizing the likelihood function. Both least square (LSE) and Kalman filter estimators (KFE) are evaluated using simulated and real power system events data. The obtained results clearly show that the LS-based technique yields the highest statistical performance and has a lower computation complexity. |
| Starting Page | 2456 |
| e-ISSN | 19961073 |
| DOI | 10.3390/en13102456 |
| Journal | Energies |
| Issue Number | 10 |
| Volume Number | 13 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2020-05-13 |
| Access Restriction | Open |
| Subject Keyword | Energies Industrial Engineering Phasor and Frequency Estimation Kalman Filter Estimation (kfe) Least Square Estimation (lse) Phasor Measurement Units Ieee Standard C37.118 Power Quality Monitoring |
| Content Type | Text |
| Resource Type | Article |
