American Journal of Energy Engineering

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Research on Power Generation Energy Sources Structure Adjustment Algorithm Based on HyperGraph

Received: 05 June 2019    Accepted: 29 June 2019    Published: 10 July 2019
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Abstract

Nowadays, the energy structure is gradually changing to clean power generation. Clean energy mainly includes renewable energy and part of non-renewable energy. Non-renewable energy is depleting day by day, showing a shrinking trend. Renewable energy is not affected by energy shortage, and is the focus of future development. How to ensure the sustainable and healthy development of clean energy, it is necessary to adjust the existing power generation energy structure scientifically and rationally. In this paper, the theory of hypergraph is introduced to cluster the optimal combination information of clean energy, and a hypergraph model of power generation energy structure adjustment is established. The problem of replacing fossil energy in power generation energy consumption with clean energy is solved as the original objective. By mapping the generation energy structure adjustment with hypergraph, the problem of generation energy structure adjustment is transformed into the problem of solving hypergraph path. By using the two-point hyperpath algorithm, an optimal path for the development of clean power generation, reducing the proportion of fossil energy power generation, and gradually converting to clean energy is obtained. The application of hypergraph algorithm in the structural adjustment of power generation is of great significance to promote the diversification of power generation energy, especially in the clean development, low-carbon development and green development of the power industry.

DOI 10.11648/j.ajee.20190702.12
Published in American Journal of Energy Engineering (Volume 7, Issue 2, June 2019)
Page(s) 49-54
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Hyper Graph, Power Generation Energy, Restructuring, Algorithm

References
[1] James McCalley, Jay Caspary, Christopher Clack, Wayne Galli, Melinda Marquis, Dale Osborn, Antje Orths, Justin Sharp, Vera Silva, and Peter Zeng, “Wide-Area Planning of Electric Infrastructure,” IEEE power & energy magazine, Vol. 15, No. 6, pp. 83-93, November/December 2017.
[2] A. MacDonald, C. Clack, A. Alexander, A. Dunbar, J. Wilczak, and Y. Xie, “Future cost-competitive electricity systems and their impact on US CO2 emissions,” Nat. Climate Change, vol. 6, pp. 526–531, Jan. 2016.
[3] ENTSO-E. (2016). Ten year network development plan 2016 executive report, European Network of Transmission System perators for Electricity. [Online]. Available: http://tyndp.entsoe.eu/projects/2016-12-20-1600-exec-report.pdf.
[4] Yuzhou Zhang, “Strategic Research and Development Strategy of Clean Energy in China,” Bulletin of Chinese Academy of Sciences, Vol. 29, No. 4, pp. 429-436, 2014.
[5] Chenhui Tang, Fan Zhang, Ning Zhang, Haoyuan Qu, Li Ma, “Day-ahead Economic Dipatch of Power System Considering Renewable Power Uncertainty and Demand Response, ” Automation of Electric Power Systems, vol. 43, No. 6, pp. 1–9, May. 2019.
[6] Energy Research Institute of National Development and Reform Commission of the PRC. (2018). China 2050 high renewable energy penetrantion scenario and roadmap study. [Online]. Available: http://news.bjx.com.cn/html/20160608/740762.shtml.
[7] Xiaoman Xu, Yugeng Sun, Shan Yang, Ruji Huang, “Hypergraph theory and its application,” Acta Electronica Sinica, Vol. 22, No. 8, pp. 22-71, 1994.
[8] Ke Zhang, Haixing Zhao, Zhonglin Ye, Yu Zhu, “Analysis for all-terminal reliability of hypernetworks,” Application Research of Computers, Vol. 37, No. 2, pp. 2-7, 2018.
[9] Miaolin Ye, Spectral Method in Graph and Hypergraph Theory, Anhui University, Hefei, China, p. 36, 2010.
[10] Jianfeng Pei, The super edge-connectivity and restricted edge-connectivity of hypergraphs, Shanxi University, Taiyuan, China, p. 1, 2018.
[11] Quansheng Cheng, Hypergraph Path Solving Algorithms and Their Applications, Huazhong University of Science and Technology, Wuhan, China, pp. 10-29, 2008.
[12] Jing Yang, Zhang-Bing Zhou, Zhi-Yong Liu, “Sub-hypergraph matching based on adjacency tensor,” Computer Vision and Image Understanding, vol. 183, pp. 1–10, June 2019.
[13] Bo Yang, Research on Matrix Algorithm of Simple Graph Problem, Huazhong University of Science and Technology, Wuhan City, China, pp. 2-6, 2017.
[14] Weiji Zhao, Zhanyu Gong, Wen Wang, Shoufang Fan, “Comparison and Analysis of Several Classical Shortest Path Algorithms,” Journal of Chifeng (Natural Science Edition), Vol. 34, No. 12, pp. 47-49, 2018.
[15] Ying Ma, Zhilong Chen, He Liu, Tongxing Zhao, “Study on the shortest path selection based on Floyd improved acceleration algorithm,” Information Technology and Network Security, Vol. 37, No. 6, pp. 72-75+107, 2018.
[16] Wei-Wei Yuan, “An Algorithm based on Feasiable Path the shortest Path,”Journal of Mudanjiang Normal University, No. 2, pp. 36-37, 2017.
[17] Jiahuan Guan, Problems and Countermeasures in Clean Energy Construction: A Case Study of China General Nuclear Power Corporation (CGN), Liaoning Normal University, Dalian, China, p. 9, 2018.
[18] Wen Dai, An Empirical Study on the Relationship between Clean Energy and Economic Growth: A Case Study of Guangdong Province, Guangzhou University, Guangzhou, China, p. 8-15, 2018.
[19] Jinxin, Luo, “Duality of Clean Energy Power Generation Technology,” Style of Science and Technology, No. 13, p. 179, 2018.
[20] Caineng Zou, Songqi Pan, Liushuan Dang, “On Energy Revolution and Science and Technology Revolution,” Style of Journal of Southwest Petroleum University (Science & Technology Edition), Vol. 41, No. 3, pp. 1-12, 2019.
[21] Erdong Zhao, Research on Low Carbonization Development of China's Electric Power Industry, Wuhan University, Wuhan, China, p. 127, 2012.
[22] Fuwei Guo “Development and Problems of New Energy,” Shandong Industrial Technology, No. 19, pp. 230-231, 2019.
[23] Weiwei Feng, Songqi Pan, Liushuan Dang “Creating a Green Future Together to Provide New Ideas for Energy Conservation and Low Carbon Development,” Energy Conservation & Environmental Protection, No. 2, pp. 16-17, 2019.
Author Information
  • Department of Electrical Engineering, Tianjin University, Tianjin, China

  • Department of Electrical Engineering, Tianjin University, Tianjin, China

  • Department of Electrical Engineering, Tianjin University, Tianjin, China

  • Mining Department, Guizhou University, Guiyang, China

  • Department of Hydropower Engineering, Wuhan University, Wuhan, China

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  • APA Style

    Chunhua Qiu, Shaoyun Ge, Ting Yang, Jun Wei, Guoxing Xiang. (2019). Research on Power Generation Energy Sources Structure Adjustment Algorithm Based on HyperGraph. American Journal of Energy Engineering, 7(2), 49-54. https://doi.org/10.11648/j.ajee.20190702.12

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    ACS Style

    Chunhua Qiu; Shaoyun Ge; Ting Yang; Jun Wei; Guoxing Xiang. Research on Power Generation Energy Sources Structure Adjustment Algorithm Based on HyperGraph. Am. J. Energy Eng. 2019, 7(2), 49-54. doi: 10.11648/j.ajee.20190702.12

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    AMA Style

    Chunhua Qiu, Shaoyun Ge, Ting Yang, Jun Wei, Guoxing Xiang. Research on Power Generation Energy Sources Structure Adjustment Algorithm Based on HyperGraph. Am J Energy Eng. 2019;7(2):49-54. doi: 10.11648/j.ajee.20190702.12

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  • @article{10.11648/j.ajee.20190702.12,
      author = {Chunhua Qiu and Shaoyun Ge and Ting Yang and Jun Wei and Guoxing Xiang},
      title = {Research on Power Generation Energy Sources Structure Adjustment Algorithm Based on HyperGraph},
      journal = {American Journal of Energy Engineering},
      volume = {7},
      number = {2},
      pages = {49-54},
      doi = {10.11648/j.ajee.20190702.12},
      url = {https://doi.org/10.11648/j.ajee.20190702.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajee.20190702.12},
      abstract = {Nowadays, the energy structure is gradually changing to clean power generation. Clean energy mainly includes renewable energy and part of non-renewable energy. Non-renewable energy is depleting day by day, showing a shrinking trend. Renewable energy is not affected by energy shortage, and is the focus of future development. How to ensure the sustainable and healthy development of clean energy, it is necessary to adjust the existing power generation energy structure scientifically and rationally. In this paper, the theory of hypergraph is introduced to cluster the optimal combination information of clean energy, and a hypergraph model of power generation energy structure adjustment is established. The problem of replacing fossil energy in power generation energy consumption with clean energy is solved as the original objective. By mapping the generation energy structure adjustment with hypergraph, the problem of generation energy structure adjustment is transformed into the problem of solving hypergraph path. By using the two-point hyperpath algorithm, an optimal path for the development of clean power generation, reducing the proportion of fossil energy power generation, and gradually converting to clean energy is obtained. The application of hypergraph algorithm in the structural adjustment of power generation is of great significance to promote the diversification of power generation energy, especially in the clean development, low-carbon development and green development of the power industry.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Research on Power Generation Energy Sources Structure Adjustment Algorithm Based on HyperGraph
    AU  - Chunhua Qiu
    AU  - Shaoyun Ge
    AU  - Ting Yang
    AU  - Jun Wei
    AU  - Guoxing Xiang
    Y1  - 2019/07/10
    PY  - 2019
    N1  - https://doi.org/10.11648/j.ajee.20190702.12
    DO  - 10.11648/j.ajee.20190702.12
    T2  - American Journal of Energy Engineering
    JF  - American Journal of Energy Engineering
    JO  - American Journal of Energy Engineering
    SP  - 49
    EP  - 54
    PB  - Science Publishing Group
    SN  - 2329-163X
    UR  - https://doi.org/10.11648/j.ajee.20190702.12
    AB  - Nowadays, the energy structure is gradually changing to clean power generation. Clean energy mainly includes renewable energy and part of non-renewable energy. Non-renewable energy is depleting day by day, showing a shrinking trend. Renewable energy is not affected by energy shortage, and is the focus of future development. How to ensure the sustainable and healthy development of clean energy, it is necessary to adjust the existing power generation energy structure scientifically and rationally. In this paper, the theory of hypergraph is introduced to cluster the optimal combination information of clean energy, and a hypergraph model of power generation energy structure adjustment is established. The problem of replacing fossil energy in power generation energy consumption with clean energy is solved as the original objective. By mapping the generation energy structure adjustment with hypergraph, the problem of generation energy structure adjustment is transformed into the problem of solving hypergraph path. By using the two-point hyperpath algorithm, an optimal path for the development of clean power generation, reducing the proportion of fossil energy power generation, and gradually converting to clean energy is obtained. The application of hypergraph algorithm in the structural adjustment of power generation is of great significance to promote the diversification of power generation energy, especially in the clean development, low-carbon development and green development of the power industry.
    VL  - 7
    IS  - 2
    ER  - 

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