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Research on Distribution Network Full Cost-Benefit Optimization Considering Different Renewable Energy Penetration

Tanzhong Fu1,2,3, Yu Xue1,*, Tancai Xia1, Wang Jing1, De Gejirifu1

1 North China Electric Power University, Beijing, 102206, China
2 Yan’an University, Yan’an, 716000, China
3 Beijing Energy Development Research Center, Beijing, 102206, China

* Corresponding Author: Yu Xue. Email: email

Energy Engineering 2020, 117(6), 397-411. https://doi.org/10.32604/EE.2020.011633

Abstract

To further study the impact of renewable energy penetration on the technical transformation of distribution networks. Based on the output power characteristics of wind power and photovoltaics, a renewable energy grid-connected capacity model and a distribution network full cost-benefit model were constructed. Based on this, to maximize the comprehensive income of the distribution network and the renewable energy penetration rate, to establish the technical reform optimization model and search for the optimal solution through the improved NSGA-II algorithm. Finally, the effectiveness of the proposed model was verified by setting up three scenarios of simultaneous wind power, grid-connected wind power, grid-connected wind power, and grid-connected photovoltaic power.

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APA Style
Fu, T., Xue, Y., Xia, T., Jing, W., Gejirifu, D. (2020). Research on distribution network full cost-benefit optimization considering different renewable energy penetration. Energy Engineering, 117(6), 397-411. https://doi.org/10.32604/EE.2020.011633
Vancouver Style
Fu T, Xue Y, Xia T, Jing W, Gejirifu D. Research on distribution network full cost-benefit optimization considering different renewable energy penetration. Energ Eng. 2020;117(6):397-411 https://doi.org/10.32604/EE.2020.011633
IEEE Style
T. Fu, Y. Xue, T. Xia, W. Jing, and D. Gejirifu, “Research on Distribution Network Full Cost-Benefit Optimization Considering Different Renewable Energy Penetration,” Energ. Eng., vol. 117, no. 6, pp. 397-411, 2020. https://doi.org/10.32604/EE.2020.011633



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This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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