Research On Probability Prediction Method Of Overhead Wire Thermal Rating

The thermal rating of overhead wire is a characteristic of its thermal load capacity,and which is closely related to meteorological factors such as wind speed,wind direction,ambient temperature and solar intensity.Therefore,it is highly volatile and difficult to be accurately predicted.In this paper,the research on the probability prediction method of overhead conductor's thermal rating can be used to predict the variation range and distribution law of thermal ratings of spans,and provide reference information for the power system operators to determine the future value of the line's thermal rating.So it is of great significance for improving the utilization rate of overhead lines and improving the safe and economic operation level of power systems.At present,the method for predicting the thermal rating has the following problems:? Due to the meteorological environment,the thermal rating is highly volatile,and the point prediction technology is difficult to give accurate information of the future thermal rating·? The existing probability prediction method is mostly time-by-time.As the correlation characteristics between the thermal rating periods are not fully considered,the distribution of prediction results is large and deviates from the actual variation of thermal ratings.?At present,the research on thermal rating prediction of overhead wire is more dependent on the online monitoring equipment,which may increase the related investment in communication equipment and daily operation.Therefore,the promotion and application of thermal rating prediction technology is limited to some extent.Regarding the issue above,firstly,based on the comprehensive research at home and abroad,the paper introduces the framework and a functional module of the dynamic thermal rating system(DTR system)of the transmission line,as well clarifies the preconditions for the positioning and development of this paper in the DTR system.Secondly,based on the micro-meteorological data measured by DTR system,the paper analyzes the autocorrelation of thermal ratings as well as the correlation between thermal ratings and the micro-meteorological at different backtracking time.According to the analysis results,the thermal rating prediction input and prediction time domain are selected reasonably.Then,the probability prediction of overhead conductor's thermal rating is realized combined with the quantile regression.On this basis,the Copula function is further used to evaluate the correlation characteristics of the probability distributions of multi-period thermal ratings.A dynamic dependence model for joint probability density distribution of multi-period thermal ratings is established to realize the joint probability density prediction for multi-period thermal ratings.Finally,under the conservative assumption of wind conditions,the relevance of ambient temperature or solar intensity between the regional weather forecast and micro weather are analyzed based on the collected historical data.Thus,the method of regional weather forecast data for the conservative prediction of thermal ratings of the regional power grid is proposed.The methods of the paper can help the power system operators to grasp the variation range and distribution law of thermal ratings of the overhead conductor,and which is conducive to improving the efficiency of equipment use and showing greater economic profits as well as social benefits,as it can provide a basis for improving the conservative value of the thermal rating.