Dissertation/Thesis Abstract

Multi-objective optimal phasor measurement units placement in power systems
by Khiabani, Vahidhossein, Ph.D., North Dakota State University, 2014, 126; 3629098
Abstract (Summary)

The extensive development of power networks has increased the requirements for robust, reliable and secure monitoring and control techniques based on the concept of Wide Area Measurement System (WAMS). Phasor Measurement Units (PMUs) are key elements in WAMS based operations of power systems. Most existing algorithms consider the problem of optimal PMU placement where the main objective is to ensure observability. They consider cost and observability of buses ignoring the reliability aspect of both WAMS and PMUs. Given the twin and conflicting objectives of cost and reliability, this dissertation aims to model and solve a multi-objective optimization formulation that maintains full system observability with minimum cost while exceeding a pre-specified level of reliability of observability. No unique solution exists for these conflicting objectives, hence the model finds the best tradeoffs. Given that the reliability-based PMU placement model is Non-deterministic Polynomial time hard (NP-hard), the mathematical model can only address small problems. This research accomplishes the following: (a) modeling and solving the multi-objective PMU placement model for IEEE standard test systems and its observability, and (b) developing heuristic algorithms to increase the scalability of the model and solve large problems. In short, early consideration of the reliability of observability in the PMU placement problem provides a balanced approach which increases the reliability of the power system overall and reduces the cost of reliability. The findings are helpful to show and understand the effectiveness of the proposed models. However the increased cost associated with the increased reliability would be negligible when considering cost of blackouts to commerce, industry, and society as a whole.

Indexing (document details)
Advisor: Farahmand, Kambiz
Commitee: Nygard, Kendall, Shi, Jing, Zhang, Jun
School: North Dakota State University
Department: Industrial and Manufacturing Engineering
School Location: United States -- North Dakota
Source: DAI-B 75/11(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Electrical engineering, Industrial engineering, Operations research
Keywords: Genetic algorithm, Multi-objective optimization, Nonlinear programming, Observability, Phasor measurement units (pmus), Reliability modeling
Publication Number: 3629098
ISBN: 978-1-321-05768-3
Copyright © 2019 ProQuest LLC. All rights reserved. Terms and Conditions Privacy Policy Cookie Policy
ProQuest