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The Key Research and Application in Grid Planning Using Improved Genetic Algorithm

The Key Research and Application in Grid Planning Using Improved Genetic Algorithm

Fan Yina, Lang Zixi, Ren Yuan, Dong Ruiwen
Copyright: © 2019 |Volume: 10 |Issue: 3 |Pages: 17
ISSN: 1947-9328|EISSN: 1947-9336|EISBN13: 9781522566168|DOI: 10.4018/IJORIS.2019070105
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MLA

Yina, Fan, et al. "The Key Research and Application in Grid Planning Using Improved Genetic Algorithm." IJORIS vol.10, no.3 2019: pp.59-75. http://doi.org/10.4018/IJORIS.2019070105

APA

Yina, F., Zixi, L., Yuan, R., & Ruiwen, D. (2019). The Key Research and Application in Grid Planning Using Improved Genetic Algorithm. International Journal of Operations Research and Information Systems (IJORIS), 10(3), 59-75. http://doi.org/10.4018/IJORIS.2019070105

Chicago

Yina, Fan, et al. "The Key Research and Application in Grid Planning Using Improved Genetic Algorithm," International Journal of Operations Research and Information Systems (IJORIS) 10, no.3: 59-75. http://doi.org/10.4018/IJORIS.2019070105

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Abstract

In order to guarantee the power grid operation under the premise of reliability and stability, acquire relative economic investment and operating cost, and adaptable to all kinds of change flexibly, this article improves the traditional generic algorithm by considering the various objective function and constraint condition. The improved algorithm can search and optimize according to mechanism for the survival of the fittest. It is especially suited for the optimization solution of integer variables. The application of the algorithm proposed to fifteen nodes system of a certain city and comparative experiments show that the algorithm has fast convergence speed and optimizing result. A comparative analysis of the optimizing project using improved generic algorithm and computational result using engineering computational method in practical grid planning yield the same results, this shows that the improved algorithm has better adaptability.