Exploration of a Scalable Holomorphic Embedding Method Formulation for Power System Analysis Applications

abstract: The holomorphic embedding method (HEM) applied to the power-flow problem (HEPF) has been used in the past to obtain the voltages and flows for power systems. The incentives for using this method over the traditional Newton-Raphson based nu-merical methods lie in the claim that the method i...

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Other Authors: Rao, Shruti Dwarkanath (Author)
Format: Doctoral Thesis
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/2286/R.I.45022
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spelling ndltd-asu.edu-item-450222018-06-22T03:08:40Z Exploration of a Scalable Holomorphic Embedding Method Formulation for Power System Analysis Applications abstract: The holomorphic embedding method (HEM) applied to the power-flow problem (HEPF) has been used in the past to obtain the voltages and flows for power systems. The incentives for using this method over the traditional Newton-Raphson based nu-merical methods lie in the claim that the method is theoretically guaranteed to converge to the operable solution, if one exists. In this report, HEPF will be used for two power system analysis purposes: a. Estimating the saddle-node bifurcation point (SNBP) of a system b. Developing reduced-order network equivalents for distribution systems. Typically, the continuation power flow (CPF) is used to estimate the SNBP of a system, which involves solving multiple power-flow problems. One of the advantages of HEPF is that the solution is obtained as an analytical expression of the embedding parameter, and using this property, three of the proposed HEPF-based methods can es-timate the SNBP of a given power system without solving multiple power-flow prob-lems (if generator VAr limits are ignored). If VAr limits are considered, the mathemat-ical representation of the power-flow problem changes and thus an iterative process would have to be performed in order to estimate the SNBP of the system. This would typically still require fewer power-flow problems to be solved than CPF in order to estimate the SNBP. Another proposed application is to develop reduced order network equivalents for radial distribution networks that retain the nonlinearities of the eliminated portion of the network and hence remain more accurate than traditional Ward-type reductions (which linearize about the given operating point) when the operating condition changes. Different ways of accelerating the convergence of the power series obtained as a part of HEPF, are explored and it is shown that the eta method is the most efficient of all methods tested. The local-measurement-based methods of estimating the SNBP are studied. Non-linear Thévenin-like networks as well as multi-bus networks are built using model data to estimate the SNBP and it is shown that the structure of these networks can be made arbitrary by appropriately modifying the nonlinear current injections, which can sim-plify the process of building such networks from measurements. Dissertation/Thesis Rao, Shruti Dwarkanath (Author) Tylavsky, Daniel J (Advisor) Undrill, John (Committee member) Vittal, Vijay (Committee member) Pal, Anamitra (Committee member) Arizona State University (Publisher) Electrical engineering Analytic continuation Holomorphically embedded power flow Local-measurement based steady-state voltage stability analysis Nonlinear network reduction Saddle-node bifurcation point Steady-state voltage stability eng 277 pages Doctoral Dissertation Electrical Engineering 2017 Doctoral Dissertation http://hdl.handle.net/2286/R.I.45022 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2017
collection NDLTD
language English
format Doctoral Thesis
sources NDLTD
topic Electrical engineering
Analytic continuation
Holomorphically embedded power flow
Local-measurement based steady-state voltage stability analysis
Nonlinear network reduction
Saddle-node bifurcation point
Steady-state voltage stability
spellingShingle Electrical engineering
Analytic continuation
Holomorphically embedded power flow
Local-measurement based steady-state voltage stability analysis
Nonlinear network reduction
Saddle-node bifurcation point
Steady-state voltage stability
Exploration of a Scalable Holomorphic Embedding Method Formulation for Power System Analysis Applications
description abstract: The holomorphic embedding method (HEM) applied to the power-flow problem (HEPF) has been used in the past to obtain the voltages and flows for power systems. The incentives for using this method over the traditional Newton-Raphson based nu-merical methods lie in the claim that the method is theoretically guaranteed to converge to the operable solution, if one exists. In this report, HEPF will be used for two power system analysis purposes: a. Estimating the saddle-node bifurcation point (SNBP) of a system b. Developing reduced-order network equivalents for distribution systems. Typically, the continuation power flow (CPF) is used to estimate the SNBP of a system, which involves solving multiple power-flow problems. One of the advantages of HEPF is that the solution is obtained as an analytical expression of the embedding parameter, and using this property, three of the proposed HEPF-based methods can es-timate the SNBP of a given power system without solving multiple power-flow prob-lems (if generator VAr limits are ignored). If VAr limits are considered, the mathemat-ical representation of the power-flow problem changes and thus an iterative process would have to be performed in order to estimate the SNBP of the system. This would typically still require fewer power-flow problems to be solved than CPF in order to estimate the SNBP. Another proposed application is to develop reduced order network equivalents for radial distribution networks that retain the nonlinearities of the eliminated portion of the network and hence remain more accurate than traditional Ward-type reductions (which linearize about the given operating point) when the operating condition changes. Different ways of accelerating the convergence of the power series obtained as a part of HEPF, are explored and it is shown that the eta method is the most efficient of all methods tested. The local-measurement-based methods of estimating the SNBP are studied. Non-linear Thévenin-like networks as well as multi-bus networks are built using model data to estimate the SNBP and it is shown that the structure of these networks can be made arbitrary by appropriately modifying the nonlinear current injections, which can sim-plify the process of building such networks from measurements. === Dissertation/Thesis === Doctoral Dissertation Electrical Engineering 2017
author2 Rao, Shruti Dwarkanath (Author)
author_facet Rao, Shruti Dwarkanath (Author)
title Exploration of a Scalable Holomorphic Embedding Method Formulation for Power System Analysis Applications
title_short Exploration of a Scalable Holomorphic Embedding Method Formulation for Power System Analysis Applications
title_full Exploration of a Scalable Holomorphic Embedding Method Formulation for Power System Analysis Applications
title_fullStr Exploration of a Scalable Holomorphic Embedding Method Formulation for Power System Analysis Applications
title_full_unstemmed Exploration of a Scalable Holomorphic Embedding Method Formulation for Power System Analysis Applications
title_sort exploration of a scalable holomorphic embedding method formulation for power system analysis applications
publishDate 2017
url http://hdl.handle.net/2286/R.I.45022
_version_ 1718701536736968704