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Data Mining Based Integrated Electric-Gas Energy System Multi-Objective Optimization

Zhukui Tan1,*, Yongjie Ren1, Hua Li1, Weili Ren2, Xichao Zhou2, Ming Zeng1

1 North China Electric Power University, Beijing, 102206, China
2 State Grid Integrated Energy Service Group, Beijing, 100052, China

* Corresponding Author: Zhukui Tan. Email: email

Energy Engineering 2022, 119(6), 2607-2619. https://doi.org/10.32604/ee.2022.019550

Abstract

With the proposal of carbon neutrality, how to improve the proportion of clean energy in energy consumption and reduce carbon dioxide emissions has become the important challenge for the traditional energy industry. Based on the idea of multi-energy complementarity, a typical integrated energy system consisting of electric system and gas system is constructed based on the application of power to gas (P2G) technology and gas turbine in this paper. Furthermore, a multi-objective optimization model with economic improvement, carbon emission reduction and peak-load shifting as objectives is proposed, and solved by BSO algorithm. Finally, a typical power-gas coupling system is selected as an example to verify the effectiveness of the model. The results showed that the proposed multi-objective optimization model based on BSO algorithm can better play the complementary characteristics of the electric and gas system, and significantly improve the comprehensive benefits of system operation.

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Cite This Article

Tan, Z., Ren, Y., Li, H., Ren, W., Zhou, X. et al. (2022). Data Mining Based Integrated Electric-Gas Energy System Multi-Objective Optimization. Energy Engineering, 119(6), 2607–2619.



cc 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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