Estimation Of Transmission Line Utilization Rate Based On Probabilistic Load Flow And Its Application

Utilization rate of various devices is an important concern of power systemplanning. With the continuous development of transmission grid, increasing growth ofload and more and more attention of utilization level of devices, how to scientificallydetermine the utilization rate of transmission line has a great significance nowadays.In this thesis, modeling and determining method to the utilization rate of transmissionline was deeply studied. Work of this thesis is as following:1) Based on the previous studies, a transmission line utilization rate index wasfirst presented. An approach by using probabilistic power flow algorithm based onMonte Carlo simulation was also given to calculate the index. Some probabilisticfactors in power system operation were considered in the calculation so as it morepracticable, such as load fluctuations, outages of generator and transmissionequipment and economic dispatch of generation units.2) IEEE RTS and New England, two systems were employed to validate thegiven model and approach. The method was then used to analyze reliability oftransmission grid, to identify weak parts and irrationality of the transmission network,and to make the economic evaluation of transmission system expansion planning withconsideration of some embedded uncertainty factors. The utilization rate index helpssystem planners estimate the income produced by the transmission lines and calculatea set of economy assessment indices, which can be a useful guidance for transmissionnetwork expansion plan.3) Finally, a real power system in China was selected to make the applicationstudy. The given method was used by the system planners to identify the possibleoverloaded transmission lines and the unreasonable network structure. It was foundthat the analysis results were correct and very helpful to the reliability analysis,economy assessment, weakness identification, and upgraded scheme optimal, et al.According to the limited time, some topics were just starting and not deeplystudied, which would be further discussed in the future.