• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.161-172
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• 2017

In the paper, a hybrid technique is proposed for detecting the location and capacity of distributed generation (DG) sources like wind and photovoltaic (PV) in power system. The novelty of the proposed method is the combined performance of both the Biography Based Optimization (BBO) and Particle Swarm Optimization (PSO) techniques. The mentioned techniques are the optimization techniques, which are used for optimizing the optimum location and capacity of the DG sources for radial distribution network. Initially, the Artificial Neural Network (ANN) is applied to obtain the available capacity of DG sources like wind and PV for 24 hours. The BBO algorithm requires radial distribution network voltage, real and power loss for determining the optimum location and capacity of the DG. Here, the BBO input parameters are classified into sub parameters and allowed as the PSO algorithm optimization process. The PSO synthesis the problem and develops the sub solution with the help of sub parameters. The BBO migration and mutation process is applied for the sub solution of PSO for identifying the optimum location and capacity of DG. For the analysis of the proposed method, the test case is considered. The IEEE standard bench mark 33 bus system is utilized for analyzing the effectiveness of the proposed method. Then the proposed technique is implemented in the MATLAB/simulink platform and the effectiveness is analyzed by comparing it with the BBO and PSO techniques. The comparison results demonstrate the superiority of the proposed approach and confirm its potential to solve the problem.

• Current Applied Physics
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• v.18 no.12
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• pp.1564-1570
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• 2018

Charge transport dynamics in ZnO based inverted organic solar cell (IOSC) has been characterized with transient photocurrent spectroscopy and localised photocurrent mapping-atomic force microscopy. The value of maximum exciton generation rate was found to vary from $2.6{\times}10^{27}m^{-3}s^{-1}$ ($J_{sat}=79.7A\;m^{-2}$) to $2.9{\times}10^{27}m^{-3}s^{-1}$ ($J_{sat}=90.8A\;m^{-2}$) for devices with power conversion efficiency ranging from 2.03 to 2.51%. These results suggest that nanorods served as an excellent electron transporting layer that provides efficient charge transport and enhances IOSC device performance. The photovoltaic performance of OSCs with various growth times of ZnO nanorods have been analysed for a comparison between AM1.5G spectrum and local solar spectrum. The simulated PCE of all devices operating under local spectrum exhibited extensive improvement with the gain of 13.3-3.7% in which the ZnO nanorods grown at 15 min possess the highest PCE under local solar with the value of 2.82%.