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Research on The Influence of Different Portfolio Types of Investments Considering New Energy Access on Transmission and Distribution Price

Published:26 March 2024Publication History

ABSTRACT

To effectively navigate the evolving dynamics of reform, it becomes imperative to delve into the symbiotic relationship between transmission and distribution tariffs and the incorporation of new energy generation into the grid. This exploration stands as a cornerstone for advancing the depth of power market reforms. Initially, our study dissects the intricate ties binding investment to transmission and distribution pricing. Herein, we underscore the quintessential triad of safety, environmental considerations, and economic viability essential for forging a resilient and sustainable power ecosystem. Subsequently, we architect a cohesive linkage model that delineates the interplay between grid investment and transmission and distribution pricing. This segues into a comprehensive scrutiny of the componential blueprint of transmission and distribution tariffs. Furthermore, we define the objective function, emphasizing the investment returns benchmark while earmarking certain constraints, notably those pertaining to transmission and distribution pricing, along with fresh load limitations. In culmination, we substantiate our findings by juxtaposing varying grid investment strategies against their respective impacts on transmission and distribution tariffs and resultant investment returns, as illuminated by real-world case studies.

References

  1. Central Committee of the Communist Party of China, State Council. Several Opinions on Further Deepening the Reform of Electric Power System [EB/OL]. (2015-03-15) tgs.ndrc.gov.cn/zywj/ 20160129_773852.htmlSam Anzaroot and Andrew McCallum. 2013. UMass Citation Field Extraction Dataset. Retrieved May 27, 2019 from http://www.iesl.cs.umass.edu/data/data-umasscitationfield.Google ScholarGoogle Scholar
  2. Chen Kai, Li Xiaozhen, Huang Kangren. Electricity Transmission and Distribution Price reform: A study on the relationship between Electricity Price, electricity and investment [J]. Price Theory and Practice,2017(4).Google ScholarGoogle Scholar
  3. Zhang Yuhong, ZHOU Ying, WANG Qian, Hu Lin, ZHANG Jiyuan, YU Xiaobao. Research on the linkage model of differentiated power grid investment and transmission and distribution price under the dual carbon goal [J/OL]. Electrical Measurement & Instrumentation, 2023(03).Google ScholarGoogle Scholar
  4. Zhu Liuzhu, Jin Wen, Ye Bin, Xie Wei, Pan Wenming, Du Haihong, You Weiyang. Research on Scenario simulation and optimization of power grid investment strategy under the background of transmission and distribution Price Reform [J]. Price Theory and Practice,2021(05):101-105.Google ScholarGoogle Scholar
  5. Jiang J X, Yuan Y. Research on portfolio optimization of power grid projects considering environmental benefits [J]. Industrial Technical Economics,2018,37(09):53-58.Google ScholarGoogle Scholar
  6. Wang Wei. Dynamic Simulation and Portfolio Optimization of Power Grid Investment under Transmission and Distribution Price Reform [D]. North China Electric Power University (Beijing), 2022.Google ScholarGoogle Scholar
  7. Bhattacharya A, Kojima S.Power sector investment risk and renewable energy: AJapanese case study using portfolio risk optimization method[J]. Energy Policy,2021,40: 69-80.Google ScholarGoogle Scholar
  8. Zhai Changyu, Li Dezhen, Liu Bo. Application of Parallel Simulated Annealing Algorithm in Intelligent Scheduling [J]. Intelligent Manufacturing,2023(01):63-66.Google ScholarGoogle Scholar
  9. Feng Yuewen, Hu Dongyang.Research on Optimal Scheduling of grid-connected Microgrid based on Simulated Annealing Genetic Algorithm [J]. Electrical Engineering Materials,2022(06):75-80.DOI:10.16786/j.cnki.1671-8887.eem.2022.06.019.Google ScholarGoogle ScholarCross RefCross Ref
  10. Gao Jia, Ren Yaming.Solution of Combinatorial Optimization Problem Based on Simulated Annealing Algorithm [J]. Sci-Tech & Development of Enterprise,2021(05):66-68.Google ScholarGoogle Scholar
  11. HAN Lushuang. Multiphase sequence search based on simulated annealing algorithm [J]. Yangtze River Information and Communication,2021,34(02):52-55.Google ScholarGoogle Scholar
  12. Yang Zhenzhen, Fang Xionan. Simulated annealing algorithm and its application [J]. China Science and Technology Information,2021(15):65-66.Google ScholarGoogle Scholar
  13. Chen D H. Simulated annealing algorithm [J]. China Information Technology Education,2021(03):19-23.Google ScholarGoogle Scholar
  14. GAO Xue-Yao, Tan Tao, ZHANG Chun-xiang. Model retrieval based on simulated annealing algorithm [J]. Journal of Harbin university of science and technology, 2020, 25 (3): 151-156. The DOI: 10.15938 / j.j hust. 2020.03.023.Google ScholarGoogle Scholar
  15. Xiong Sencai, Zhu Xuejun, Liu Lihui Based on simulated annealing algorithm for adaptive optimization of fuze-warhead coordination design [J]. Journal of tactical missile technology, 2020 (03): 98-104. The DOI: 10.16358 / j.i SSN. 1009-1300.2020.8.197.Google ScholarGoogle Scholar
  16. Qu Chengjun, Ji Changming, Zhang Yanke Research on Improved Distribution estimation Algorithm based on Simulated annealing [J]. Application Research of Computers,20,37(S1):138-139+142.Google ScholarGoogle Scholar
  17. Yang Yue. Research on load topology of wind farm absorption line based on Simulated annealing algorithm [J]. Communications Technology,2020,53(03):684-688.Google ScholarGoogle Scholar

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  • Published in

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    ICITEE '23: Proceedings of the 6th International Conference on Information Technologies and Electrical Engineering
    November 2023
    764 pages
    ISBN:9798400708299
    DOI:10.1145/3640115

    Copyright © 2023 ACM

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    Publication History

    • Published: 26 March 2024

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