Topology oriented security and vulnerability analysis in power systems

Pao Yue-kong Library Electronic Theses Database

Topology oriented security and vulnerability analysis in power systems


Author: Jia, Youwei
Title: Topology oriented security and vulnerability analysis in power systems
Degree: Ph.D.
Year: 2015
Subject: Electric power systems -- Security measures.
Electric power transmission.
Hong Kong Polytechnic University -- Dissertations
Department: Dept. of Electrical Engineering
Pages: xx, 154, 25 pages : color illustrations
Language: English
InnoPac Record:
Abstract: Successful development of smart grid demands strengthened system security and reliability, which requires effective security analysis in conducting system operation and expansion planning. Classical N-1 criterion has been widely used in the past to examine every creditable contingency through detailed computations. However, the adequacy of such approach becomes doubtful in facing with many recent blackouts where cascading outages are usually involved. This may be attributed to the increased complexities and nonlinearities involved in operating conditions and topological structures in the context of smart grid development. Thus far, existing literatures on multiple contingency (N-k) analysis show a lack of comprehensiveness to address topological changes of transmission networks in different contingency scenarios, and post-contingency risk (e.g. risk of potential cascading failures), etc. Most existing methods are less effective to accommodate more stringent security standards, which suffer from heavy computational burden, inaccuracy of N-k contingency screening, or both of them. Further, in large-scale electric power networks, such security analysis can be even more intractable due to massive data involved and the combinatorial explosion problem. In this thesis, a comprehensive study is conducted to deal with the security threats particularly from N-k contingency induced topological changes in transmission network and cascading risk in the post-contingency phase. The need of effective and efficient analytical approaches is highlighted in Chapter 1, where research background and incentive of this study are introduced in details. Chapter 2 presents an overview of existing research works concerning security issues of modern electric power network in a static sense, where tricky challenges and open problems are also identified. Motivated by previous works, a topology oriented security study is presented in Chapters 3 and 4, which cover two partsunderlying network robustness and resilience analysis, and N-k induced cascading contingency screening. Chapter 3 focuses on structural issues including topological vulnerability analysis, identification of network separations, network partitions in the smart grid environment, and percolation phenomena as critical phase transitions in power transmission network. Other than event based analysis, Chapter 3 provides high level statistical solutions based on complex network theory. In Chapter 4, a new and efficient N-k contingency screening framework is proposed, which comprises cascading failure simulation module (CFSM) for post-contingency analysis, risk evaluation module (REM) based on data mining techniques, and contingency screening module (CSM) for listing out different Pareto optimal fronts containing high-risk multiple contingencies. This framework comprehensively combines topological aspects and detailed steady-state cascading simulations. The effectiveness of this framework is demonstrated through two case studies on New England 39-bus system and IEEE 118-bus system. It is concluded in Chapter 5 that incorporating topological analysis of underlying networks into steady-state power system security evaluation is an effective and promising way of N-k induced cascading contingency screening. Experimental results demonstrate a high potential of this framework for practical application on system planning. Meanwhile, Chapter 5 also indicates the future works to further extend this framework to fulfill emerging requirements in future smart grids.

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