EKF for Power Estimation of Uncertain Time-varying CPLs in DC Shipboard MGs

Navid Vafamand, Shirin Yousefizadeh, Mohammad Hassan Khooban, Jan Dimon Bendtsen, Tomislav Dragicevic

Publikation: Konferencebidrag uden forlag/tidsskriftKonferenceabstrakt til konferenceForskningpeer review

4 Citationer (Scopus)

Abstrakt

The stability of DC microgrids (DC MG) that are connected to constant power loads (CPL) is of prime importance for the operation of shipboard power systems (SPS). To control the DC MG of SPS effectively, the instantaneous power value of the time-varying uncertain CPLs is necessary. Since the integration of current sensors is costly and the resistance of these sensors degrades ripple filtering, instantaneous power estimation of CPLs is proposed. This paper investigates the development of an extended Kalman filter (EKF) to estimate the power of time-varying uncertain CPLs alongside estimation of CPLs’ and sources’ currents in a DC MG. By augmenting the CPLs powers into the DC MG states, a joint estimation problem is presented to effectively estimate the currents of the DC MG as well as the CPLs powers values. The proposed approach is applied to a DC MG that feeds one CPL. Experimental results show the effectiveness of the proposed EKF in the estimation of instantaneous CPLs powers and the currents of the CPLs and the source.
OriginalsprogEngelsk
Publikationsdato2018
Antal sider6
DOI
StatusUdgivet - 2018
BegivenhedProceedings of the 44th Annual Conference of the IEEE Industrial Electronics Society (IECON 2018) -
Varighed: 23 okt. 2018 → …

Konference

KonferenceProceedings of the 44th Annual Conference of the IEEE Industrial Electronics Society (IECON 2018)
Periode23/10/2018 → …

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  • Citationsformater

    Vafamand, N., Yousefizadeh, S., Khooban, M. H., Bendtsen, J. D., & Dragicevic, T. (2018). EKF for Power Estimation of Uncertain Time-varying CPLs in DC Shipboard MGs. 1-6. Abstract fra Proceedings of the 44th Annual Conference of the IEEE Industrial Electronics Society (IECON 2018), . https://doi.org/10.1109/IECON.2018.8591350