Conditional Maximum Likelihood of Three-Phase Phasor Estimation for ?PMU in Active Distribution Networks

Jiang Li, Wenzhen Wei, Shuo Zhang, Guoqing Li and Chenghong Gu
Additional contact information
Jiang Li: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Wenzhen Wei: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Shuo Zhang: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Guoqing Li: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Chenghong Gu: Department of Electronic & Electrical Engineering, University of Bath, Bath BA2 7AY, UK

Energies, 2018, vol. 11, issue 5, 1-18

Abstract: Micro phasor measurement units (μPMU) installed in active distribution networks are very useful for improving observability by acquiring system real-time data. However, three-phase imbalance and harmonic power flows adversely impact the accuracy of synchronous measurements, which implies the importance of phasor estimation errors. This paper proposes a new phasor estimation algorithm for μPMU in active distribution networks that uses a conditional maximum likelihood (CML) estimation method. Firstly, the signal model of three-phase, three-wire and four-wire imbalance systems is established. Then, the probability distributions of the magnitude and phase angles are derived from the geometric characteristics of the CML method by solving the geometric equation. Simulation results show that the proposed CML based method is effective for estimating phasor and impedance models of active distribution networks by using μPMU measurement data.

Keywords: active distribution networks; PMU; conditional maximum likelihood estimation; three-phase imbalance system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/5/1320/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/5/1320/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:5:p:1320-:d:148382

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().