In recent times, silicone rubber insulating material is used for power transmission line and substation insulation applications. In the present work, tracking and erosion resistance of the micro size filled and nano s...In recent times, silicone rubber insulating material is used for power transmission line and substation insulation applications. In the present work, tracking and erosion resistance of the micro size filled and nano size filled silicone rubber material has been studied under the AC voltage, with ammonium chloride as a contaminant, as per IEC 60587 test procedures. The characteristic changes in the tracking resistance of the micro size and nano size filled specimens are analyzed through leakage current measurement. Comparative Tracking Index （CTI） is also evaluated in order to understand the relative behavior of solid electrical insulating material with regard to their susceptibility to surface tracking. Trend followed by the fundamental, third harmonic and fifth harmonic components of the leakage current during the tracking study are analyzed using moving average current technique. It is observed that the harmonic components of leakage current show good correlation with the tracking and erosion resistance of the material. It is noticed that 5 % wt ofnano size filler gives similar performance to that of 30 % wt of micro size filler in silicone composites.展开更多
In this paper, an interline power flow controller （IPFC） is used for controlling multi transmission lines. However, the optimal placement of IPFC in the transmis-sion line is a major problem. Thus, we use a combinat...In this paper, an interline power flow controller （IPFC） is used for controlling multi transmission lines. However, the optimal placement of IPFC in the transmis-sion line is a major problem. Thus, we use a combination of tabu search （TS） algorithm and artificial neural network （ANN） in the proposed method to find out the best placement locations for IPFC in a given multi transmission line system. TS algorithm is an optimization algorithm and we use it in the proposed method to determine the optimum bus combination using line data. Then, using the optimum bus combination, the neural network is trained to find out the best placement locations for IPFC. Finally, IPFC is connected at the best locations indicated by the neural network. Furthermore, using Newton-Raphson load flow algorithm, the transmission line loss of the IPFC connected bus is analyzed. The proposed methodology is implemen- ted in MATLAB working platform and tested on the IEEE-14 bus system. The output is compared with the genetic algorithm （GA） and general load flow analysis. The results are validated with Levenberg-Marquardt back propagation and gradient descent with momentum network training algorithm.展开更多
文摘In recent times, silicone rubber insulating material is used for power transmission line and substation insulation applications. In the present work, tracking and erosion resistance of the micro size filled and nano size filled silicone rubber material has been studied under the AC voltage, with ammonium chloride as a contaminant, as per IEC 60587 test procedures. The characteristic changes in the tracking resistance of the micro size and nano size filled specimens are analyzed through leakage current measurement. Comparative Tracking Index （CTI） is also evaluated in order to understand the relative behavior of solid electrical insulating material with regard to their susceptibility to surface tracking. Trend followed by the fundamental, third harmonic and fifth harmonic components of the leakage current during the tracking study are analyzed using moving average current technique. It is observed that the harmonic components of leakage current show good correlation with the tracking and erosion resistance of the material. It is noticed that 5 % wt ofnano size filler gives similar performance to that of 30 % wt of micro size filler in silicone composites.
文摘In this paper, an interline power flow controller （IPFC） is used for controlling multi transmission lines. However, the optimal placement of IPFC in the transmis-sion line is a major problem. Thus, we use a combination of tabu search （TS） algorithm and artificial neural network （ANN） in the proposed method to find out the best placement locations for IPFC in a given multi transmission line system. TS algorithm is an optimization algorithm and we use it in the proposed method to determine the optimum bus combination using line data. Then, using the optimum bus combination, the neural network is trained to find out the best placement locations for IPFC. Finally, IPFC is connected at the best locations indicated by the neural network. Furthermore, using Newton-Raphson load flow algorithm, the transmission line loss of the IPFC connected bus is analyzed. The proposed methodology is implemen- ted in MATLAB working platform and tested on the IEEE-14 bus system. The output is compared with the genetic algorithm （GA） and general load flow analysis. The results are validated with Levenberg-Marquardt back propagation and gradient descent with momentum network training algorithm.
