IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i16p6062-d1220364.html
   My bibliography  Save this article

Evaluation Method of the Incremental Power Supply Capability Brought by Distributed Generation

Author

Listed:
  • Yi Hao

    (State Grid Tianjin Electric Power Company, Tianjin 300010, China)

  • Zhigang Huang

    (State Grid Tianjin Electric Power Company, Tianjin 300010, China)

  • Shiqian Ma

    (State Grid Tianjin Electric Power Research Institute, Tianjin 300010, China)

  • Jiakai Huang

    (State Grid Tianjin Electric Power Research Institute, Tianjin 300010, China)

  • Jiahao Chen

    (School of Electrical Automation and Information Engineering, Tianjin University, Tianjin 300072, China)

  • Bing Sun

    (School of Electrical Automation and Information Engineering, Tianjin University, Tianjin 300072, China)

Abstract

More and more distributed generation (DG) and energy storage (ES) devices are being connected to the distribution network (DN). They have the potential of maintaining a stable supply load during failure periods when using islanding operations. Therefore, DG and ES have capacity value, i.e., improving the power supply capability of the system. However, there are strong fluctuations in DG outputs, and the operations of ES devices have sequential characteristics. The same capacity of DG has different load-bearing capabilities compared to conventional thermal or hydroelectric units. This paper proposes a method for evaluation of power supply capability improvement in DNs. First, the temporal fluctuation in both power source and load demand during fault periods is considered. A DN island partition model considering the secondary power outage constraint is established. Then, a modified genetic algorithm is designed. The complex island partition model is solved to achieve accurate power supply reliability evaluation. And the incremental power supply capability associated to DG and ES devices is calculated. Finally, a case study is conducted on the PG&E 69-bus system to verify the effectiveness of the proposed method. It is found that with a 20% configuration ratio of ES devices, the power supply capability improvement brought about by 6 MW DG can reach about 773 kW.

Suggested Citation

  • Yi Hao & Zhigang Huang & Shiqian Ma & Jiakai Huang & Jiahao Chen & Bing Sun, 2023. "Evaluation Method of the Incremental Power Supply Capability Brought by Distributed Generation," Energies, MDPI, vol. 16(16), pages 1-17, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:16:p:6062-:d:1220364
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/16/6062/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/16/6062/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sun, Bing & Yu, Yixin & Qin, Chao, 2017. "Should China focus on the distributed development of wind and solar photovoltaic power generation? A comparative study," Applied Energy, Elsevier, vol. 185(P1), pages 421-439.
    2. Xu, Keyi & Yan, Jie & Zhang, Hao & Zhang, Haoran & Han, Shuang & Liu, Yongqian, 2021. "Quantile based probabilistic wind turbine power curve model," Applied Energy, Elsevier, vol. 296(C).
    3. Chen, Jiahao & Sun, Bing & Li, Yunfei & Jing, Ruipeng & Zeng, Yuan & Li, Minghao, 2022. "Credible capacity calculation method of distributed generation based on equal power supply reliability criterion," Renewable Energy, Elsevier, vol. 201(P1), pages 534-547.
    4. Zhao, Jinli & Zhang, Mengzhen & Yu, Hao & Ji, Haoran & Song, Guanyu & Li, Peng & Wang, Chengshan & Wu, Jianzhong, 2019. "An islanding partition method of active distribution networks based on chance-constrained programming," Applied Energy, Elsevier, vol. 242(C), pages 78-91.
    5. Zheng, Boshen & Wei, Wei & Chen, Yue & Wu, Qiuwei & Mei, Shengwei, 2022. "A peer-to-peer energy trading market embedded with residential shared energy storage units," Applied Energy, Elsevier, vol. 308(C).
    6. Paik, Chunhyun & Chung, Yongjoo & Kim, Young Jin, 2021. "ELCC-based capacity credit estimation accounting for uncertainties in capacity factors and its application to solar power in Korea," Renewable Energy, Elsevier, vol. 164(C), pages 833-841.
    7. Hou, Qingchun & Zhang, Ning & Du, Ershun & Miao, Miao & Peng, Fei & Kang, Chongqing, 2019. "Probabilistic duck curve in high PV penetration power system: Concept, modeling, and empirical analysis in China," Applied Energy, Elsevier, vol. 242(C), pages 205-215.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jiahao Chen & Bing Sun & Yuan Zeng & Ruipeng Jing & Shimeng Dong & Jingran Wang, 2023. "An Optimal Scheduling Method of Shared Energy Storage System Considering Distribution Network Operation Risk," Energies, MDPI, vol. 16(5), pages 1-24, March.
    2. Chen, Jiahao & Sun, Bing & Li, Yunfei & Jing, Ruipeng & Zeng, Yuan & Li, Minghao, 2022. "Credible capacity calculation method of distributed generation based on equal power supply reliability criterion," Renewable Energy, Elsevier, vol. 201(P1), pages 534-547.
    3. Hao Cai & Ling Liang & Jing Tang & Qianxian Wang & Lihong Wei & Jiaping Xie, 2019. "An Empirical Study on the Efficiency and Influencing Factors of the Photovoltaic Industry in China and an Analysis of Its Influencing Factors," Sustainability, MDPI, vol. 11(23), pages 1-22, November.
    4. Hou, Hui & Xu, Tao & Wu, Xixiu & Wang, Huan & Tang, Aihong & Chen, Yangyang, 2020. "Optimal capacity configuration of the wind-photovoltaic-storage hybrid power system based on gravity energy storage system," Applied Energy, Elsevier, vol. 271(C).
    5. Maarten Evens & Patricia Ercoli & Alessia Arteconi, 2023. "Blockchain-Enabled Microgrids: Toward Peer-to-Peer Energy Trading and Flexible Demand Management," Energies, MDPI, vol. 16(18), pages 1-24, September.
    6. Shen, Feifei & Zhao, Liang & Du, Wenli & Zhong, Weimin & Qian, Feng, 2020. "Large-scale industrial energy systems optimization under uncertainty: A data-driven robust optimization approach," Applied Energy, Elsevier, vol. 259(C).
    7. Muaddi, Saad & Singh, Chanan, 2022. "Investigating capacity credit sensitivity to reliability metrics and computational methodologies," Applied Energy, Elsevier, vol. 325(C).
    8. Wu, Long & Yin, Xunyuan & Pan, Lei & Liu, Jinfeng, 2023. "Distributed economic predictive control of integrated energy systems for enhanced synergy and grid response: A decomposition and cooperation strategy," Applied Energy, Elsevier, vol. 349(C).
    9. Wang, Xuewei & Wang, Jing & Wang, Lin & Yuan, Ruiming, 2019. "Non-overlapping moving compressive measurement algorithm for electrical energy estimation of distorted m-sequence dynamic test signal," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    10. Chen, Hao & Chen, Jiachuan & Han, Guoyi & Cui, Qi, 2022. "Winding down the wind power curtailment in China: What made the difference?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    11. Lin, Boqiang & Ma, Ruiyang, 2022. "Green technology innovations, urban innovation environment and CO2 emission reduction in China: Fresh evidence from a partially linear functional-coefficient panel model," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    12. Homeyra Akter & Harun Or Rashid Howlader & Ahmed Y. Saber & Paras Mandal & Hiroshi Takahashi & Tomonobu Senjyu, 2021. "Optimal Sizing of Hybrid Microgrid in a Remote Island Considering Advanced Direct Load Control for Demand Response and Low Carbon Emission," Energies, MDPI, vol. 14(22), pages 1-19, November.
    13. Xin Yan & Qian Zhang, 2023. "Research on Combination of Distributed Generation Placement and Dynamic Distribution Network Reconfiguration Based on MIBWOA," Sustainability, MDPI, vol. 15(12), pages 1-34, June.
    14. Zhang, Yusheng & Ma, Chao & Yang, Yang & Pang, Xiulan & Liu, Lu & Lian, Jijian, 2021. "Study on short-term optimal operation of cascade hydro-photovoltaic hybrid systems," Applied Energy, Elsevier, vol. 291(C).
    15. Pierre Cayet & Arash Farnoosh, 2022. "A robust structural electric system model with significant share of intermittent renewables under auto-correlated residual demand," EconomiX Working Papers 2022-6, University of Paris Nanterre, EconomiX.
    16. Adisorn Leelasantitham & Thammavich Wongsamerchue & Yod Sukamongkol, 2024. "Economic Pricing in Peer-to-Peer Electrical Trading for a Sustainable Electricity Supply Chain Industry in Thailand," Energies, MDPI, vol. 17(5), pages 1-19, March.
    17. Sepúlveda-Mora, Sergio B. & Hegedus, Steven, 2021. "Making the case for time-of-use electric rates to boost the value of battery storage in commercial buildings with grid connected PV systems," Energy, Elsevier, vol. 218(C).
    18. Gholami, M. & Sanjari, M.J., 2021. "Multiobjective energy management in battery-integrated home energy systems," Renewable Energy, Elsevier, vol. 177(C), pages 967-975.
    19. Xu, Jiuping & Zhao, Chuandang & Wang, Fengjuan & Yang, Guocan, 2022. "Industrial decarbonisation oriented distributed renewable generation towards wastewater treatment sector: Case from the Yangtze River Delta region in China," Energy, Elsevier, vol. 256(C).
    20. Tan, Qinliang & Ding, Yihong & Ye, Qi & Mei, Shufan & Zhang, Yimei & Wei, Yongmei, 2019. "Optimization and evaluation of a dispatch model for an integrated wind-photovoltaic-thermal power system based on dynamic carbon emissions trading," Applied Energy, Elsevier, vol. 253(C), pages 1-1.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:16:p:6062-:d:1220364. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.