No abstract

Particle charging is an essential process for electrostatic precipitators (ESPs) in removing particles. A particle charge measurement system, which can adjust the flue gas temperature, was designed to study the effects of the flue gas parameters (viz., temperature and humidity), particle composition, and discharge electrodes on particle charging. The particle charge increased with the temperature when the applied electric field strength was constant. For particles with a diameter of 0.73 µm, the average charge increased by 30% (from 140 e to 183 e) when the temperature increased from 300 K to 363 K. Furthermore, with a constant electric field strength of -4.2 kV cm -1 , the average charge increased by 98% when the relative dielectric constant increased from 4.5 to 11.8. Increased relative humidity significantly accelerated particle charging. For particles > 0.1 µm, the average charge increased by more than 50% when the relative humidity increased from 30% to 80%. Optimizing the discharge electrode also enhanced charging. After the wire electrode (d = 1 mm) was replaced by a ribbon electrode, particle charging increased by more than 75% for 0.7 µm particles at -4.2 kV cm -1 .

Large-scale doubly fed induction generator (DFIG) wind farms are integrated into power grid through transmission line. Traditional pilot protection as the main protection is widely used in transmission line. However, when traditional pilot protection is applied to transmission line with DFIG, it may appear undesired tripping. Therefore, this work presents a novel pilot protection based on time-domain waveform identification for transmission line with DFIG. The waveform features of the fault currents provided by DFIG and synchronous generator are analyzed. According to the waveform similarity between prefault and postfault currents, calculated separately at DFIG wind farm side and power grid side, the protection principle is established: when internal faults occur, the waveform similarity calculated at DFIG wind farm side is much lower than that calculated at power grid side; when external faults occur, the waveform similarity calculated at both sides are almost the same. A complete protection flow based on proposed principle is designed. Furthermore, a false data detection method is raised for resisting the influence of noise on the performance of proposed protection. Extensive digital simulations are conducted to verify the principle. The test results indicate that the proposed protection can reliably identify the internal faults and external faults, and also has strong ability to withstand the effects of fault resistance, noise, and communication delay. K E Y W O R D S DFIG, Hausdorff distance algorithm, pilot protection, time-domain waveform identification, transmission line List of Symbols and Abbreviations: Z eq , equivalent impedance of upstream network; I, current sampling sequence; I * , normalized I; max{I}, maximum value in I; min{I}, minimum value in I; k, sampling point label of I; X, waveform set X = {x 1 , x 2 , .…x m }; Y, waveform set Y = {y 1 , y 2 , .…y n };

A diagnosis scheme using the Hurst exponent for metal particle faults in GIL/GIS is proposed to improve the accuracy of classification and identification. First, the diagnosis source signal is the vibration signal generated by the collision of metal particles in the electric field. Then, the signal is processed via variational mode decomposition (VMD) based on particle swarm optimization with adaptive parameter adjustment (APA-PSO). In the end, fault types are classified and identified by an SVM model, whose feature vector is composed of the Hurst exponents of each intrinsic mode function (IMF-H). Extensive experimental data verify the effect of this new scheme. The results exhibit that the classification performance of SVM is significantly improved by the new feature vector. Furthermore, the VMD based on APA-PSO with adaptive parameter adjustment can effectively enhance the decomposition quality.