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Title: | Droop Coefficient Design in Droop Control of Power Converters for Improved Load Sharing: An Artificial Neural Network Approach |
Authors: | Hussaini, Habibu Yang, Tao Gao, Yuan Dragicevic, Tomislav Bozhko, Serhiy |
Keywords: | Artificial neural network Droop coefficient Cable resistance More electric aircraft Data generation Current sharing |
Issue Date: | Jun-2021 |
Publisher: | IEEE |
Citation: | H. Hussaini, T. Yang, Y. Gao, C. Wang, T. Dragicevic and S. Bozhko, "Droop Coefficient Design in Droop Control of Power Converters for Improved Load Sharing: An Artificial Neural Network Approach," 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE), Kyoto, Japan, 2021, pp. 1-6, doi: 10.1109/ISIE45552.2021.9576482. |
Abstract: | In this paper, a new approach for the design of the droop coefficient in the droop control of power converters using the artificial neural network (ANN) is proposed. In the first instance, a detailed more electric aircraft (MEA) electrical power system (EPS) circuit model is simulated in a loop using different combinations of the converters droop coefficients within a design space. The inaccurate output DC currents sharing of the converters due to the influence of the unequal cable resistance are then obtained from each of the simulations. The data generated is then used to train the NN to be a dedicated surrogate model of the detailed MEA EPS simulation. Thus, for any user-defined desired current sharing among the converters that are within the design space, the proposed NN can provide the optimal droop coefficients. This NN approach has been verified through simulations to ensure accurate current sharing between the converters as desired. Hence, can be used in the design of the droop coefficient to enhance the performance of the conventional droop control method. |
URI: | http://repository.futminna.edu.ng:8080/jspui/handle/123456789/17832 |
ISSN: | Electronic ISSN: 2163-5145 Print on Demand(PoD) ISSN: 2163-5137 |
Appears in Collections: | Electrical/Electronic Engineering |
Files in This Item:
File | Description | Size | Format | |
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Submitted Manuscript final.pdf | Droop Coefficient Design in Droop Control of Power Converters for Improved Load Sharing: An Artificial Neural Network Approach | 387.29 kB | Adobe PDF | View/Open |
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