GENERATING.CAPACITY RELIABILITY INDICES
| dc.creator | Jamali, Mohsin Mohammad | |
| dc.date.accessioned | 2017-08-16T21:58:06Z | |
| dc.date.available | 2017-08-16T21:58:06Z | |
| dc.date.issued | 1979-01 | |
| dc.date.submitted | January 1979 | en_US |
| dc.description.abstract | Both probabilistic and non-probabilistic methods are widely used, for generating capacity planning in power systems. In recent years, however, special interest has been devoted to further development of comprehensive probabilistic techniques. The thesis examines several methods of obtaining quantitative reliability indices useful in the area of generating capacity reserve assessment and long range planning. These methods utilize the individual unit Forced Outage Rates (FOR), failure and repair rates and determine the mean values of the indices of loss of load and energy loss. The times to failure and times to repair are also considered as random variables in this thesis in order to determine the mean values and distributions of selected generating capacity reliability indices using a Monte Carlo Simulation time dependent method. All the methods presented are illustrated by applications to a Saskatchewan Power Corporation generation system model. Expansion studies have been conducted and the results are discussed for each probabilistic technique. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10388/8020 | |
| dc.title | GENERATING.CAPACITY RELIABILITY INDICES | en_US |
| dc.type.genre | Thesis | en_US |
| thesis.degree.department | Electrical and Computer Engineering | en_US |
| thesis.degree.discipline | Electrical Engineering | en_US |
| thesis.degree.grantor | University of Saskatchewan | en_US |
| thesis.degree.level | Masters | en_US |
| thesis.degree.name | Master of Science (M.Sc.) | en_US |