DETERMINATION OF TRANSMISSION LINE AMPACITIES BY PROBABILITY AND NUMERICAL METHODS
dc.contributor.advisor | Billinton, R. | |
dc.creator | Koval, Don Orest | |
dc.date.accessioned | 2018-12-20T18:51:07Z | |
dc.date.available | 2018-12-20T18:51:07Z | |
dc.date.issued | 1969-05 | |
dc.date.submitted | May 1969 | en_US |
dc.description.abstract | The transmission line is the primary medium by which electrical power is transmitted and distributed within a power system. The maximum load current that can be carried by the conductor is designated as the conductor ampacity and is normally determined from a single set of weather conditions. In recent years, it has been suggested that traditional ampacities are conservative and that local weather and operating practices should be utilized in evaluating a given conductor ampacity. This thesis presents the numerical and statistical methods for establishing the ampacity of an existing transmission line considering actual hourly weather and load current data collected over a period of one year. These methods are generalized to be applicable to any transmission line located in a given weather environment. .A statistical weather model has been developed utilizing the Pearson Family of Curves, the Method of Least Squares and some elements of correlation theory. Digital computer programs have been developed to study conductor ampacities based on the maximum conductor temperature and the permanent loss of strength in the conductor due to annealing. The actual weather data, the statistical weather model and various load current distributions have been studied to establish the ampacity for an existing transmission line. General conclusions reached concerning ampacities agreed with published data. The statistical weather model approach was found to be accurate, quite flexible and requires less digital computer time than the sequential utilization of actual data. | en_US |
dc.identifier.uri | http://hdl.handle.net/10388/11680 | |
dc.title | DETERMINATION OF TRANSMISSION LINE AMPACITIES BY PROBABILITY AND NUMERICAL METHODS | 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 |