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Properties and structural analyses of USA’s regional electricity market: A visibility graph network approach

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  • Hu, Jun
  • Xia, Chengyi
  • Li, Huijia
  • Zhu, Peican
  • Xiong, Wenjun

Abstract

Through the market-oriented reform and operation in the recent 30 years, the organizational structure of power systems in the U.S. has formed a relatively stable situation, where various levels of power companies can supervise and restrict each other to create a set of perfect management, plan and approval mechanisms. In this paper, by use of the time series data of electricity price, renewable energy proportion and CO2 emission at each state from 1990 to 2014, we analyze these data from 50 states based on the approach of network science. Firstly, we perform the time series visualization according to the vision graph method. Subsequently, the correlation among these 50 states is calculated regarding the related indicators, and henceforth the relationship network between them is constructed. Finally, the community detection is used to cluster the specific policies carried out at various states. After the detailed analyses, it is indicated that all these 50 states can be divided into four categories as far as the policy of electric reform and power market is concerned. The current results provide some clues to deeply understand the electricity marketing reform in the U.S., and also offer some valuable hints for other countries to optimize the operation or reform of power systems.

Suggested Citation

  • Hu, Jun & Xia, Chengyi & Li, Huijia & Zhu, Peican & Xiong, Wenjun, 2020. "Properties and structural analyses of USA’s regional electricity market: A visibility graph network approach," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    • Handle: RePEc:eee:apmaco:v:385:y:2020:i:c:s0096300320303957
    DOI: 10.1016/j.amc.2020.125434
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    References listed on IDEAS

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    1. Fan, Xinghua & Li, Xuxia & Yin, Jiuli & Tian, Lixin & Liang, Jiaochen, 2019. "Similarity and heterogeneity of price dynamics across China’s regional carbon markets: A visibility graph network approach," Applied Energy, Elsevier, vol. 235(C), pages 739-746.
    2. Wang, Zhishuang & Guo, Quantong & Sun, Shiwen & Xia, Chengyi, 2019. "The impact of awareness diffusion on SIR-like epidemics in multiplex networks," Applied Mathematics and Computation, Elsevier, vol. 349(C), pages 134-147.
    3. Erick Lachapelle & Christopher P. Borick & Barry Rabe, 2012. "Public Attitudes toward Climate Science and Climate Policy in Federal Systems: Canada and the United States Compared," Review of Policy Research, Policy Studies Organization, vol. 29(3), pages 334-357, May.
    4. Jin-Peng Liu & Qian-Ru Yang & Lin He, 2017. "Total-Factor Energy Efficiency (TFEE) Evaluation on Thermal Power Industry with DEA, Malmquist and Multiple Regression Techniques," Energies, MDPI, vol. 10(7), pages 1-14, July.
    5. Li, Jie & Wang, Juan & Sun, Shiwen & Xia, Chengyi, 2018. "Cascading crashes induced by the individual heterogeneity in complex networks," Applied Mathematics and Computation, Elsevier, vol. 323(C), pages 182-192.
    6. Zhu, Peican & Wang, Xinyu & Li, Shudong & Guo, Yangming & Wang, Zhen, 2019. "Investigation of epidemic spreading process on multiplex networks by incorporating fatal properties," Applied Mathematics and Computation, Elsevier, vol. 359(C), pages 512-524.
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    Cited by:

    1. Wu, Xuehui & Wu, Zhong & Hu, Jun, 2022. "Global competitiveness analysis of industrial robot technology innovations market layout using visibility graph," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    2. Wang, Yuyao & Bu, Zhan & Yang, Huan & Li, Hui-Jia & Cao, Jie, 2021. "An effective and scalable overlapping community detection approach: Integrating social identity model and game theory," Applied Mathematics and Computation, Elsevier, vol. 390(C).

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