![Sample our Economics, Finance,Business & Industry journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5931/TOC-Subject-Sample-2021-Economics-Finance-Business-Industry.jpg"})
Abstract
In the power system, Ultra-High-Voltage (UHV) transmission is an effective means to improve and solve the imbalance between power supply and demand. However, with the continuous improvement of the voltage level, the adverse effects caused by the electromagnetic environment of the transmission lines are also growing. Audible noise produced by corona discharge of transmission lines has seriously interfered with the daily life of residents near the transmission lines, which can not meet the requirements of protecting residents and environmental friendliness. In this article, the background noise in the time-domain waveform of corona current is removed by wavelet analysis. The time domain waveform of corona current is transformed into the frequency domain by a fast Fourier transform. Through the analysis of the spectrum of corona current, it is found that the corona current attenuates with the increase of frequency, and most of the energy is concentrated in the first 1.5 MHz frequency band. The relationship between each frequency band of corona current and audible noise is obtained by the multiple linear regression, and the regression model is proved to be well fitted by testing. The experimental analysis shows that the algorithm in this article is 8% better than the traditional finite element method, and is closest to the actual measurement value, which proves that the actual effect of the research contained in this article is more effective. These achievements are helpful for the further study of the electromagnetic environment of UHV transmission lines, which is conducive to promoting the vigorous development of the UHV DC transmission technology in China, allocating resources more reasonably and reducing environmental pollution, and meeting the strategic requirements of energy and environment in China.
Additional information
Funding
Notes on contributors
Xiaoguang Li
Xiaoguang Li (1983.09), master degree. Now he works as a senior engineer in State Grid Xinjiang Electric Power Co., Ltd. Electric Power Research Institute, Institute of Intelligent Measurement. His main research directions include smart sensors, high voltage and insulation technology.
Longxiang Yuan
Longxiang Yuan (1985.02), master degree. Now he works as an intermediate engineer in State Grid Xinjiang Electric Power Co., Ltd. Electric Power Research Institute, Institute of Intelligent Measurement. His main research directions include high voltage equipment test and fault diagnosis and analysis.
Hui Song
Hui Song (1990.08), master degree. Now he works as an intermediate engineer in State Grid Xinjiang Electric Power Co., Ltd. Electric Power Research Institute, Institute of Intelligent Measurement. His main research direction is transformer high voltage test technology.