Dynamic Line Rating Technology And Software Of Its Monitoring Platform

Power supply situation at home is strict nowadays. In the unbalance between supply and demand, dynamic line rating technology is profitable and promising in power supply market. This technology measure tension of bare conductor or weather conditions around transmission lien, estimate average conductor temperature, calculate line thermal capacity instantly and decide current of transmission based on power network stability. It can also realize prediction of line thermal capacity.Theory part of this thesis first introduces methods to calculate line thermal capacity, including weather model (WM) and conductor temperature model (CTM). After an analysis of their errors, we point out the applicable range of both models. Then, based on weather indices of weather model, the thesis pay special attention to adopt Bayesian statistical inference methods to give prediction of probability distribution in the future according to short-term weather indices measurement. As a conclusion, this model can be used to realize a risk-assessment-based DLR system.Practical part of this thesis first presents the composition of the DLR system. As its components, designs of data acquisition terminal and monitor management platform are mentioned briefly. Afterwards, keys of developing communication server system and database system are also given.Emphasis of the practical part is building the monitor management and data analysis system. In the building process, we first used user-case based techniques to analyze demands and capture concerns. Then add-in framework of SharpDevelop is transplanted, based on which the module division is finally decided. Realizing of the modules while keeping them separate is difficult. We accomplish that via a newly developed .NET based aspect orient programming. Applying these techniques, the software is highly modulized and decouplized, which is very beneficial to redeveloping and transplantation.