IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v367y2024ics0306261924007542.html
   My bibliography  Save this article

A hierarchical demand assessment methodology of peaking resources in multi-areas interconnected systems with a high percentage of renewables

Author

Listed:
  • Junhui, L.I.
  • Pan, Yahui
  • Mu, Gang
  • Chen, Guohang
  • Zhu, Xingxu
  • Yan, Ganggui
  • Li, Cuiping
  • Jia, Chen

Abstract

The uncertainty of wind power poses a serious challenge in peak regulation for multi-area interconnected power system, and this paper proposes a method for quantitatively assessing the peaking resource demand of a multi-area interconnected power system, which takes into account the complementary characteristics of inter-area regulating resources and the wind power forecast error. First, wind power historical data are analysed with a data-driven model-based wind power forecast error, to reduce the impact of renewable energy uncertainty on power system peaking demand. Subsequently, a multi-area peaking demand analysis method considering power flow constraints, which is proposed for the effective utilization of peaking resources in areas with complementary characteristics. The method can adequately quantify the area power margin, adjustable power, and area grid peaking demand. On this basis, a two-layer assessment model of multi-area peaking resource demand is constructed, the areas are divided into different categories of peaking aggregation based on the area peaking characteristics. The upper layer takes the area operating cost as the optimisation objective, to derive the optimal output of each area in the system, and the lower layer ensures the optimal matching of power among clusters, which is solved by using a Nash equilibrium. Finally, the effectiveness and superiority of the method is verified by case analysis, and the numerical results show that compared with the traditional global optimal method, the cost of operation and transmission has been decreased by 21.5% and the security of power flows has been significantly enhanced.

Suggested Citation

  • Junhui, L.I. & Pan, Yahui & Mu, Gang & Chen, Guohang & Zhu, Xingxu & Yan, Ganggui & Li, Cuiping & Jia, Chen, 2024. "A hierarchical demand assessment methodology of peaking resources in multi-areas interconnected systems with a high percentage of renewables," Applied Energy, Elsevier, vol. 367(C).
  • Handle: RePEc:eee:appene:v:367:y:2024:i:c:s0306261924007542
    DOI: 10.1016/j.apenergy.2024.123371
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924007542
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2024.123371?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wu, Xin & Yao, Lijuan & Pi, Tanxin & Liu, Yuhang & Li, Xiang & Gong, Gangjun, 2023. "Virtual-real interaction control of hybrid load system for low-carbon energy services," Applied Energy, Elsevier, vol. 330(PB).
    2. Li, Zheng & Luan, Ranran & Lin, Boqiang, 2022. "The trend and factors affecting renewable energy distribution and disparity across countries," Energy, Elsevier, vol. 254(PB).
    3. Yuan, Meng & Thellufsen, Jakob Zinck & Lund, Henrik & Liang, Yongtu, 2021. "The electrification of transportation in energy transition," Energy, Elsevier, vol. 236(C).
    4. Han, Shuo & He, Mengjiao & Zhao, Ziwen & Chen, Diyi & Xu, Beibei & Jurasz, Jakub & Liu, Fusheng & Zheng, Hongxi, 2023. "Overcoming the uncertainty and volatility of wind power: Day-ahead scheduling of hydro-wind hybrid power generation system by coordinating power regulation and frequency response flexibility," Applied Energy, Elsevier, vol. 333(C).
    5. Pilpola, Sannamari & Lund, Peter D., 2020. "Analyzing the effects of uncertainties on the modelling of low-carbon energy system pathways," Energy, Elsevier, vol. 201(C).
    6. Yang, Hongming & Liang, Rui & Yuan, Yuan & Chen, Bowen & Xiang, Sheng & Liu, Junpeng & Zhao, Huan & Ackom, Emmanuel, 2022. "Distributionally robust optimal dispatch in the power system with high penetration of wind power based on net load fluctuation data," Applied Energy, Elsevier, vol. 313(C).
    7. Ratnam, Kamala Sarojini & Palanisamy, K. & Yang, Guangya, 2020. "Future low-inertia power systems: Requirements, issues, and solutions - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    8. Wang, Jingxing & Chung, Seokhyun & AlShelahi, Abdullah & Kontar, Raed & Byon, Eunshin & Saigal, Romesh, 2021. "Look-ahead decision making for renewable energy: A dynamic “predict and store” approach," Applied Energy, Elsevier, vol. 296(C).
    9. Ahmed, Ijaz & Rehan, Muhammad & Basit, Abdul & Malik, Saddam Hussain & Alvi, Um-E-Habiba & Hong, Keum-Shik, 2022. "Multi-area economic emission dispatch for large-scale multi-fueled power plants contemplating inter-connected grid tie-lines power flow limitations," Energy, Elsevier, vol. 261(PB).
    10. Zhao, Jing & Yang, Zilan & Shi, Linyu & Liu, Dehan & Li, Haonan & Mi, Yumiao & Wang, Hongbin & Feng, Meili & Hutagaol, Timothy Joseph, 2024. "Photovoltaic capacity dynamic tracking model predictive control strategy of air-conditioning systems with consideration of flexible loads," Applied Energy, Elsevier, vol. 356(C).
    11. Keskar, Aditya & Galik, Christopher & Johnson, Jeremiah X., 2023. "Planning for winter peaking power systems in the United States," Energy Policy, Elsevier, vol. 173(C).
    12. Zeng, Huibin & Shao, Bilin & Dai, Hongbin & Tian, Ning & Zhao, Wei, 2023. "Incentive-based demand response strategies for natural gas considering carbon emissions and load volatility," Applied Energy, Elsevier, vol. 348(C).
    13. Shair, Jan & Li, Haozhi & Hu, Jiabing & Xie, Xiaorong, 2021. "Power system stability issues, classifications and research prospects in the context of high-penetration of renewables and power electronics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    14. Ghahramani, Mehrdad & Nazari-Heris, Morteza & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2019. "Energy and reserve management of a smart distribution system by incorporating responsive-loads /battery/wind turbines considering uncertain parameters," Energy, Elsevier, vol. 183(C), pages 205-219.
    15. Titz, Maurizio & Pütz, Sebastian & Witthaut, Dirk, 2024. "Identifying drivers and mitigators for congestion and redispatch in the German electric power system with explainable AI," Applied Energy, Elsevier, vol. 356(C).
    16. Wang, Sen & Li, Fengting & Zhang, Gaohang & Yin, Chunya, 2023. "Analysis of energy storage demand for peak shaving and frequency regulation of power systems with high penetration of renewable energy," Energy, Elsevier, vol. 267(C).
    17. Bogdanov, Dmitrii & Ram, Manish & Aghahosseini, Arman & Gulagi, Ashish & Oyewo, Ayobami Solomon & Child, Michael & Caldera, Upeksha & Sadovskaia, Kristina & Farfan, Javier & De Souza Noel Simas Barbos, 2021. "Low-cost renewable electricity as the key driver of the global energy transition towards sustainability," Energy, Elsevier, vol. 227(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Linbo Fang & Wei Peng & Youliang Li & Zi Yang & Yi Sun & Hang Liu & Lei Xu & Lei Sun & Weikang Fang, 2024. "A Bi-Level Peak Regulation Optimization Model for Power Systems Considering Ramping Capability and Demand Response," Energies, MDPI, vol. 17(19), pages 1-17, September.

    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. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    2. Róbert Csalódi & Tímea Czvetkó & Viktor Sebestyén & János Abonyi, 2022. "Sectoral Analysis of Energy Transition Paths and Greenhouse Gas Emissions," Energies, MDPI, vol. 15(21), pages 1-26, October.
    3. Wang, Sen & Li, Fengting & Zhang, Gaohang & Yin, Chunya, 2023. "Analysis of energy storage demand for peak shaving and frequency regulation of power systems with high penetration of renewable energy," Energy, Elsevier, vol. 267(C).
    4. Pastore, Lorenzo Mario & Lo Basso, Gianluigi & Ricciardi, Guido & de Santoli, Livio, 2023. "Smart energy systems for renewable energy communities: A comparative analysis of power-to-X strategies for improving energy self-consumption," Energy, Elsevier, vol. 280(C).
    5. Oyewo, Ayobami Solomon & Solomon, A.A. & Bogdanov, Dmitrii & Aghahosseini, Arman & Mensah, Theophilus Nii Odai & Ram, Manish & Breyer, Christian, 2021. "Just transition towards defossilised energy systems for developing economies: A case study of Ethiopia," Renewable Energy, Elsevier, vol. 176(C), pages 346-365.
    6. Wu, Junqi & Niu, Zhibin & Li, Xiang & Huang, Lizhen & Nielsen, Per Sieverts & Liu, Xiufeng, 2023. "Understanding multi-scale spatiotemporal energy consumption data: A visual analysis approach," Energy, Elsevier, vol. 263(PD).
    7. Bogdanov, Dmitrii & Breyer, Christian, 2024. "Role of smart charging of electric vehicles and vehicle-to-grid in integrated renewables-based energy systems on country level," Energy, Elsevier, vol. 301(C).
    8. Zhang, Huaiyuan & Liao, Kai & Yang, Jianwei & Zheng, Shunwei & He, Zhengyou, 2024. "Frequency-constrained expansion planning for wind and photovoltaic power in wind-photovoltaic-hydro-thermal multi-power system," Applied Energy, Elsevier, vol. 356(C).
    9. Oluwafemi Emmanuel Oni & Omowunmi Mary Longe, 2023. "Analysis of Secondary Controller on MTDC Link with Solar PV Integration for Inter-Area Power Oscillation Damping," Energies, MDPI, vol. 16(17), pages 1-18, August.
    10. Hasret Sahin & A. A. Solomon & Arman Aghahosseini & Christian Breyer, 2024. "Systemwide energy return on investment in a sustainable transition towards net zero power systems," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    11. Taghizadeh-Hesary, Farhad & Rasoulinezhad, Ehsan & Shahbaz, Muhammad & Vinh Vo, Xuan, 2021. "How energy transition and power consumption are related in Asian economies with different income levels?," Energy, Elsevier, vol. 237(C).
    12. Zhao, Jing & Yang, Zilan & Shi, Linyu & Liu, Dehan & Li, Haonan & Mi, Yumiao & Wang, Hongbin & Feng, Meili & Hutagaol, Timothy Joseph, 2024. "Photovoltaic capacity dynamic tracking model predictive control strategy of air-conditioning systems with consideration of flexible loads," Applied Energy, Elsevier, vol. 356(C).
    13. Goutte, Stéphane & Mhadhbi, Mayssa, 2024. "Analyzing Crisis Dynamics: How metal-energy Markets influence green electricity investments," Energy Economics, Elsevier, vol. 134(C).
    14. Tomasz Rokicki & Radosław Jadczak & Adam Kucharski & Piotr Bórawski & Aneta Bełdycka-Bórawska & András Szeberényi & Aleksandra Perkowska, 2022. "Changes in Energy Consumption and Energy Intensity in EU Countries as a Result of the COVID-19 Pandemic by Sector and Area Economy," Energies, MDPI, vol. 15(17), pages 1-26, August.
    15. Huo, Zhihong & Xu, Chang, 2022. "Distributed cooperative automatic generation control and multi-event triggered mechanisms co-design for networked wind-integrated power systems," Renewable Energy, Elsevier, vol. 193(C), pages 41-56.
    16. Liu, Xinyu & Yang, Jianping & Yang, Chunhe & Zhang, Zheyuan & Chen, Weizhong, 2023. "Numerical simulation on cavern support of compressed air energy storage(CAES)considering thermo-mechanical coupling effect," Energy, Elsevier, vol. 282(C).
    17. Shen, Boyang & Chen, Yu & Li, Chuanyue & Wang, Sheng & Chen, Xiaoyuan, 2021. "Superconducting fault current limiter (SFCL): Experiment and the simulation from finite-element method (FEM) to power/energy system software," Energy, Elsevier, vol. 234(C).
    18. Yin, Linfei & He, Xiaoyu, 2023. "Artificial emotional deep Q learning for real-time smart voltage control of cyber-physical social power systems," Energy, Elsevier, vol. 273(C).
    19. Chung-Hao Chang & Shih-Fang Lo, 2022. "Impact Analysis of a National and Corporate Carbon Emission Reduction Target on Renewable Electricity Use: A Review," Energies, MDPI, vol. 15(5), pages 1-18, February.
    20. Lopez, Gabriel & Galimova, Tansu & Fasihi, Mahdi & Bogdanov, Dmitrii & Breyer, Christian, 2023. "Towards defossilised steel: Supply chain options for a green European steel industry," Energy, Elsevier, vol. 273(C).

    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:eee:appene:v:367:y:2024:i:c:s0306261924007542. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.