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‘In Silico’ Testing of a Decentralized PMUData-Based Power Systems Mode Estimator
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. (SmarTS Lab)
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. (SmarTS Lab)ORCID iD: 0000-0003-2353-1683
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. (SmarTS Lab)ORCID iD: 0000-0002-6090-1674
KTH, School of Electrical Engineering (EES), Electric Power and Energy Systems. Statnett. (SmarTS Lab)ORCID iD: 0000-0002-4125-1055
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2016 (English)In: Power and Energy Society General Meeting (PESGM), 2016, IEEE conference proceedings, 2016Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents the software implementation ofa Phasor Measurement Unit (PMU) data-based mode estimationapplication in a decentralized mode estimation architecture. Thiswork builds from previous efforts in the development of a modeestimator implemented using a centralized architecture, meaninga set of modes were estimated for the whole system in a singleprocessing location. One drawback of mode estimators that usecentralized mode architecture is that the observability and thereforeestimation of important low-damped local electromechanicalmodes can be affected by the higher observability of otherdominant modes of the systems (e.g inter-area modes). This workproposes, implements and tests a decentralized architecture inorder to increase the observation capability to provide betterestimates of local low damped oscillations. In this architecture,the data from a single PMU or a group of local PMUs couldbe processed by a processor to estimate the modal parametersobserved at a specific part of the grid or observed by specificgroup of PMUs. The decentralized architecture and results oftests are presented in this paper together with comparison witha centralized architecture.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2016.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-185010DOI: 10.1109/PESGM.2016.7741392ISI: 000399937901040Scopus ID: 2-s2.0-85002279692OAI: oai:DiVA.org:kth-185010DiVA: diva2:917903
Conference
IEEE PES General Meeting 2016, Boston, MA, US, July 17-21, 2016
Note

QC 20160415

Available from: 2016-04-08 Created: 2016-04-08 Last updated: 2017-06-15Bibliographically approved

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Mode Estimator(961 kB)88 downloads
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Baudette, MaximeHooshyar, HosseinVanfretti, Luigi

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Singh, Ravi ShankarBaudette, MaximeHooshyar, HosseinVanfretti, LuigiAlmas, Muhammad Shoaib
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