Bulk electric system reliability simulation and application
| dc.contributor.advisor | Billinton, Roy | en_US |
| dc.contributor.committeeMember | Xu, Wilsun | en_US |
| dc.contributor.committeeMember | Wacker, Gary | en_US |
| dc.contributor.committeeMember | Oguocha, Ikechukwuka N. | en_US |
| dc.contributor.committeeMember | Klymyshyn, David M. | en_US |
| dc.contributor.committeeMember | Karki, Rajesh | en_US |
| dc.creator | Wangdee, Wijarn | en_US |
| dc.date.accessioned | 2005-12-15T13:35:51Z | en_US |
| dc.date.accessioned | 2013-01-04T05:10:36Z | |
| dc.date.available | 2005-12-19T08:00:00Z | en_US |
| dc.date.available | 2013-01-04T05:10:36Z | |
| dc.date.created | 2005-12 | en_US |
| dc.date.issued | 2005-12-09 | en_US |
| dc.date.submitted | December 2005 | en_US |
| dc.description.abstract | Bulk electric system reliability analysis is an important activity in both vertically integrated and unbundled electric power utilities. Competition and uncertainty in the new deregulated electric utility industry are serious concerns. New planning criteria with broader engineering consideration of transmission access and consistent risk assessment must be explicitly addressed. Modern developments in high speed computation facilities now permit the realistic utilization of sequential Monte Carlo simulation technique in practical bulk electric system reliability assessment resulting in a more complete understanding of bulk electric system risks and associated uncertainties. Two significant advantages when utilizing sequential simulation are the ability to obtain accurate frequency and duration indices, and the opportunity to synthesize reliability index probability distributions which describe the annual index variability. This research work introduces the concept of applying reliability index probability distributions to assess bulk electric system risk. Bulk electric system reliability performance index probability distributions are used as integral elements in a performance based regulation (PBR) mechanism. An appreciation of the annual variability of the reliability performance indices can assist power engineers and risk managers to manage and control future potential risks under a PBR reward/penalty structure. There is growing interest in combining deterministic considerations with probabilistic assessment in order to evaluate the “system well-being” of bulk electric systems and to evaluate the likelihood, not only of entering a complete failure state, but also the likelihood of being very close to trouble. The system well-being concept presented in this thesis is a probabilistic framework that incorporates the accepted deterministic N-1 security criterion, and provides valuable information on what the degree of the system vulnerability might be under a particular system condition using a quantitative interpretation of the degree of system security and insecurity. An overall reliability analysis framework considering both adequacy and security perspectives is proposed using system well-being analysis and traditional adequacy assessment. The system planning process using combined adequacy and security considerations offers an additional reliability-based dimension. Sequential Monte Carlo simulation is also ideally suited to the analysis of intermittent generating resources such as wind energy conversion systems (WECS) as its framework can incorporate the chronological characteristics of wind. The reliability impacts of wind power in a bulk electric system are examined in this thesis. Transmission reinforcement planning associated with large-scale WECS and the utilization of reliability cost/worth analysis in the examination of reinforcement alternatives are also illustrated. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10388/etd-12152005-133551 | en_US |
| dc.language.iso | en_US | en_US |
| dc.subject | Wind Power | en_US |
| dc.subject | Reliability Evaluation | en_US |
| dc.subject | Combined Adequacy and Security Framework | en_US |
| dc.subject | Sequential Monte Carlo Simulation | en_US |
| dc.subject | Power Systems | en_US |
| dc.title | Bulk electric system reliability simulation and application | en_US |
| dc.type.genre | Thesis | en_US |
| dc.type.material | text | en_US |
| thesis.degree.department | Electrical Engineering | en_US |
| thesis.degree.discipline | Electrical Engineering | en_US |
| thesis.degree.grantor | University of Saskatchewan | en_US |
| thesis.degree.level | Doctoral | en_US |
| thesis.degree.name | Doctor of Philosophy (Ph.D.) | en_US |