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Equivalent Circuit Formulation Based Framework for Probabilistic Power System Analysis
Equivalent Circuit Formulation Based Framework for Probabilistic Power System Analysis
상세정보
- 자료유형
- 학위논문
- Control Number
- 0015494398
- International Standard Book Number
- 9781687992703
- Dewey Decimal Classification Number
- 621.3
- Main Entry-Personal Name
- Wagner, Martin Rupert.
- Publication, Distribution, etc. (Imprint
- [Sl] : Carnegie Mellon University, 2019
- Publication, Distribution, etc. (Imprint
- Ann Arbor : ProQuest Dissertations & Theses, 2019
- Physical Description
- 153 p
- General Note
- Source: Dissertations Abstracts International, Volume: 81-06, Section: B.
- General Note
- Advisor: Pileggi, Larry.
- Dissertation Note
- Thesis (Ph.D.)--Carnegie Mellon University, 2019.
- Restrictions on Access Note
- This item must not be sold to any third party vendors.
- Summary, Etc.
- 요약The Equivalent Circuit Formulation (ECF) was found to enable robust Power System analysis by formulating Power System problems in terms of their true state variables and further applying circuit simulation methods for their robust solution. This thesis describes the theoretical background to formulate equivalent circuit problems for three different Power System analyses: AC Power Flow analysis, an optimization algorithm to identify Power Flow feasibility, and an optimization-based linear State Estimation (SE) algorithm.We further discuss the design and implementation of a prototype ECF based Power System simulator SUGAR (Simulation with Unified Grid Analyses and Renewables) in C++ that is able to solve the aforementioned analyses effectively. Furthermore, we utilize this implementation to build a framework for probabilistic Power System analyses using a Monte Carlo-based algorithm. We propose a continuation method that effectively and robustly solves Monte Carlo samples given a reference solution, which enables probabilistic Power Flow analysis on models up to continental interconnection-sized systems. In addition, we implement variable correlations within and between models, and propose a probabilistic generation control algorithm.After comparing our linear State Estimation algorithm that incorporates linear models for PMU and RTU measurements to a traditional WLS estimator, we propose a probabilistic approach to State Estimation utilizing this algorithm. We further demonstrate the feasibility of such an approach and present probabilistic SE studies including network uncertainties. Finally, we propose an approach to identify "true"-grid states by a Monte Carlo-based stochastic optimization.
- Subject Added Entry-Topical Term
- Electrical engineering
- Added Entry-Corporate Name
- Carnegie Mellon University Electrical and Computer Engineering
- Host Item Entry
- Dissertations Abstracts International. 81-06B.
- Host Item Entry
- Dissertation Abstract International
- Electronic Location and Access
- 로그인을 한후 보실 수 있는 자료입니다.
- Control Number
- joongbu:568291
MARC
008200131s2019 c eng d■001000015494398
■00520200217182520
■020 ▼a9781687992703
■035 ▼a(MiAaPQ)AAI27540311
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a621.3
■1001 ▼aWagner, Martin Rupert.
■24510▼aEquivalent Circuit Formulation Based Framework for Probabilistic Power System Analysis
■260 ▼a[Sl]▼bCarnegie Mellon University▼c2019
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2019
■300 ▼a153 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 81-06, Section: B.
■500 ▼aAdvisor: Pileggi, Larry.
■5021 ▼aThesis (Ph.D.)--Carnegie Mellon University, 2019.
■506 ▼aThis item must not be sold to any third party vendors.
■520 ▼aThe Equivalent Circuit Formulation (ECF) was found to enable robust Power System analysis by formulating Power System problems in terms of their true state variables and further applying circuit simulation methods for their robust solution. This thesis describes the theoretical background to formulate equivalent circuit problems for three different Power System analyses: AC Power Flow analysis, an optimization algorithm to identify Power Flow feasibility, and an optimization-based linear State Estimation (SE) algorithm.We further discuss the design and implementation of a prototype ECF based Power System simulator SUGAR (Simulation with Unified Grid Analyses and Renewables) in C++ that is able to solve the aforementioned analyses effectively. Furthermore, we utilize this implementation to build a framework for probabilistic Power System analyses using a Monte Carlo-based algorithm. We propose a continuation method that effectively and robustly solves Monte Carlo samples given a reference solution, which enables probabilistic Power Flow analysis on models up to continental interconnection-sized systems. In addition, we implement variable correlations within and between models, and propose a probabilistic generation control algorithm.After comparing our linear State Estimation algorithm that incorporates linear models for PMU and RTU measurements to a traditional WLS estimator, we propose a probabilistic approach to State Estimation utilizing this algorithm. We further demonstrate the feasibility of such an approach and present probabilistic SE studies including network uncertainties. Finally, we propose an approach to identify "true"-grid states by a Monte Carlo-based stochastic optimization.
■590 ▼aSchool code: 0041.
■650 4▼aElectrical engineering
■690 ▼a0544
■71020▼aCarnegie Mellon University▼bElectrical and Computer Engineering.
■7730 ▼tDissertations Abstracts International▼g81-06B.
■773 ▼tDissertation Abstract International
■790 ▼a0041
■791 ▼aPh.D.
■792 ▼a2019
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T15494398▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202002▼f2020
