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Model Segmentation and Simplification for Electric Power Distribution Systems

Reiman, Andrew P. (2017) Model Segmentation and Simplification for Electric Power Distribution Systems. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Quasi-static time-series (QSTS) simulation is used to simulate the behavior of electric power distribution systems over long periods of time (typically hours to years). The technique involves repeatedly solving the load-flow problem for a distribution system model. This is useful in accounting for solar power variations in distributed energy resource (DER) planning. When a QSTS simulation has a small enough time step and a long enough duration, the computational burden of the simulation can be prohibitive. One way to relieve the computational burden is to simplify the model of the distribution system.

This dissertation includes an overview of existing methods of distribution system simplification and also introduces a new method, segment substitution, which addresses many of the limitations of the existing methods. The segment substitution method offers dramatic (i.e. more than 98%) model order reduction with a simplification error that is expected to be acceptable for many applications. In contrast to existing methods of distribution system model simplification, which rely on topological inspection and linearization, the segment substitution method can be used to produce a simplified model using black-box segment data and an assumed simplified topology. It also produces a more realistic simplified approximation of constant-power load models than existing methods.

Simplification using segment substitution is demonstrated using two full-scale distribution system models to achieve simulation performance gains of over 90% while introducing a state error less than 0.2%.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Reiman, Andrew P.apr28@pitt.eduAPR28
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee CoChairMcDermott, Thomastem42@pitt.eduTEM42
Committee CoChairReed, Gregorygfr3@pitt.eduGFR3
Committee MemberAkcakaya, Muratakcakaya@pitt.eduakcakaya
Committee MemberKwasinski, Alexisakwasins@pitt.eduakwasins
Committee MemberStanchina, Williamwes25@pitt.eduWES25
Committee MemberZeng, Bobzeng@pitt.edubzeng
Date: 14 June 2017
Date Type: Publication
Defense Date: 15 March 2017
Approval Date: 14 June 2017
Submission Date: 16 March 2017
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 156
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Electrical and Computer Engineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Power System Modeling; Model Reduction
Date Deposited: 14 Jun 2017 18:24
Last Modified: 14 Jun 2017 18:24


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