TRANSMISSION LINE RELIABILITY MODELING INCORPORATING EXTREME ADVERSE WEATHER CONSIDERATIONS

This thesis illustrates the development of a reliability model for two redundant transmission lines, which incorporates normal and bad weather conditions. The two indices of system average failure rate and system average outage duration are evaluated for this model using a Markov approach, an approximate equations method and Monte Carlo simulation. The results show that a very optimistic evaluation can be obtained if the effects of bad weather are ignored. The results obtained using the approximate method and the Monte Carlo simulation technique are compared with those obtained using the theoretically exact Markov approach. The comparison indicates that the approximate method provides, under certain conditions, a practical approach for general transmission and distribution system analysis as it can be applied directly in minimal cut applications. The conventional two weather state model is extended in this thesis to a reliability model which incorporates normal, adverse and major adverse weather conditions. Similar analyses were conducted for the conventional two state model, and the developed three state model. The effects due to a portion of the bad weather occurring in major adverse weather were evaluated. The results indicate that the two weather state model does not reflect the increasing importance of major averse weather and can underestimate the potential error. A comparison of the results obtained using the three methods of analysis places some limits on the use of the approximate equations. A series of sensitivity studies were conducted to examine the response of the two weather state models to a specific set of weather parameter changes. In these analyses the average durations of normal and adverse weather relative to the base case, the percentage of line failures occurring in bad weather and the percentage of bad weather failures occurring in major adverse weather were varied. Model acceptability analysis was conducted by comparing the error factors obtained, using the two weather models under different combinations of weather conditions. Application zones for both weather models are illustrated in the thesis for the conditions considered