IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v251y2025ics0960148125009784.html

Research on source-load uncertainty optimal scheduling based on a hybrid robust multi-interval optimization method

Author

Listed:
  • Zhao, Zhuang
  • Wu, Jiahui
  • Wang, Bo
  • Wang, Rui

Abstract

The new power systems(NPS) play an important role in enabling the efficient use of clean energy. In order to improve the operation economy, reliability and efficient consumption of renewable energy of NPS, a hybrid multi-interval robust optimization model was proposed. First, the model takes into account the improved thermal power flexible conversion energy cost model, and designs the output efficiency interval model of wind farm and photovoltaic power station considering the impact of equipment maintenance and failure. Compared with traditional models, these models can more accurately reflect the energy consumption cost and actual output of power supply equipment. Secondly, a hybrid multi-interval robust optimization model is proposed to improve the conservatism of traditional interval optimization methods. In addition, in order to improve the solving efficiency, this paper introduces the adaptive compression particle swarm optimization algorithm to overcome the problem that the traditional optimization algorithm is easy to fall into the local optimal solution. Finally, the IEEE30-node system is taken as an example for simulation verification. The results show that the proposed method can effectively reduce the adverse effects caused by the uncertainty of source and load, and improve the absorption rate of wind power and photovoltaic.

Suggested Citation

  • Zhao, Zhuang & Wu, Jiahui & Wang, Bo & Wang, Rui, 2025. "Research on source-load uncertainty optimal scheduling based on a hybrid robust multi-interval optimization method," Renewable Energy, Elsevier, vol. 251(C).
    • Handle: RePEc:eee:renene:v:251:y:2025:i:c:s0960148125009784
    DOI: 10.1016/j.renene.2025.123316
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148125009784
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2025.123316?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Jiang, C. & Han, X. & Liu, G.R. & Liu, G.P., 2008. "A nonlinear interval number programming method for uncertain optimization problems," European Journal of Operational Research, Elsevier, vol. 188(1), pages 1-13, July.
    2. Liu, Xun & Wang, Jie-Sheng & Zhang, Song-Bo & Guan, Xin-Yi & Gao, Yuan-Zheng, 2024. "Optimization scheduling of off-grid hybrid renewable energy systems based on dung beetle optimizer with convergence factor and mathematical spiral," Renewable Energy, Elsevier, vol. 237(PD).
    3. Yue, Xiaoyu & Liao, Siyang & Xu, Jian & Ke, Deping & Wang, Huiji & Yang, Jiaquan & He, Xuehao, 2024. "Collaborative optimization of renewable energy power systems integrating electrolytic aluminum load regulation and thermal power deep peak shaving," Applied Energy, Elsevier, vol. 373(C).
    4. Mei, Fei & Zhang, Jiatang & Lu, Jixiang & Lu, Jinjun & Jiang, Yuhan & Gu, Jiaqi & Yu, Kun & Gan, Lei, 2021. "Stochastic optimal operation model for a distributed integrated energy system based on multiple-scenario simulations," Energy, Elsevier, vol. 219(C).
    5. Hani Albalawi & Abdul Wadood & Herie Park, 2024. "Economic Load Dispatch Problem Analysis Based on Modified Moth Flame Optimizer (MMFO) Considering Emission and Wind Power," Mathematics, MDPI, vol. 12(21), pages 1-24, October.
    6. Yang, Mao & Wang, Jinxin & Chen, Yiming & Zeng, Yuxuan & Su, Xin, 2024. "Data-driven robust optimization scheduling for microgrid day-ahead to intra-day operations based on renewable energy interval prediction," Energy, Elsevier, vol. 313(C).
    7. Lai, Wenhao & Song, Qi & Zheng, Xiaoliang & Chen, Hualiang, 2025. "The study of optimal reactive power dispatch in power systems based on further improved membrane search algorithm," Applied Energy, Elsevier, vol. 377(PA).
    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. Zhang, Xuehan & Pan, Zhenning & Choi, Sungyun, 2026. "Interval analysis based coordinated dispatch of battery energy storage systems and flexible loads for distribution systems considering extreme operating scenarios," Renewable Energy, Elsevier, vol. 258(C).

    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. Zhao, Heng & Fu, Chao & Zhang, Yaqiong & Wan, Zhiqiang & Lu, Kuan, 2025. "A non-probabilistic reliability-based design optimization method via dimensional decomposition-aided Chebyshev metamodel," Reliability Engineering and System Safety, Elsevier, vol. 262(C).
    2. Da Li & Shijie Zhang & Yunhan Xiao, 2020. "Interval Optimization-Based Optimal Design of Distributed Energy Resource Systems under Uncertainties," Energies, MDPI, vol. 13(13), pages 1-18, July.
    3. Mingshan Mo & Xinrui Xiong & Yunlong Wu & Zuyao Yu, 2023. "Deep-Reinforcement-Learning-Based Low-Carbon Economic Dispatch for Community-Integrated Energy System under Multiple Uncertainties," Energies, MDPI, vol. 16(22), pages 1-18, November.
    4. Zhongzheng Li & Gaohang Zhang & Mengke Liao & Erbiao Zhou, 2025. "Coordinative Scheduling Method for Source–Load–Storage Integrated Systems Considering the Utilization of Energy-Intensive Industry Loads for Regulation," Sustainability, MDPI, vol. 17(16), pages 1-21, August.
    5. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Zhao, Yunlong & Gao, Chong, 2023. "A stochastic hierarchical optimization and revenue allocation approach for multi-regional integrated energy systems based on cooperative games," Applied Energy, Elsevier, vol. 350(C).
    6. Yibo Jiang & Zhe Wang & Shiqi Bian & Siyang Liao & Huibin Lu, 2024. "Source-Load Collaborative Optimization Method Considering Core Production Constraints of Electrolytic Aluminum Load," Energies, MDPI, vol. 17(24), pages 1-17, December.
    7. Cao, Wenqiang & Yu, Junqi & Ru, Chengyi & Wang, Meng & Wang, Ke, 2025. "A two-stage distributionally robust optimization operation scheduling model for solar PT-PV systems based on integrated load consumption prediction," Energy, Elsevier, vol. 332(C).
    8. Wu, Tianyu & Han, Fengwu & Zhao, Yunlong & Yu, Zishuo, 2025. "A decarbonization-oriented and uncertainty-aware energy management strategy for multi-district integrated energy systems with fair peer-to-peer trading," Energy, Elsevier, vol. 323(C).
    9. Mahdi Zarghami & Nasim Safari & Ferenc Szidarovszky & Shafiqul Islam, 2015. "Nonlinear Interval Parameter Programming Combined with Cooperative Games: a Tool for Addressing Uncertainty in Water Allocation Using Water Diplomacy Framework," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(12), pages 4285-4303, September.
    10. Li-Peng Shao & Jia-Jia Chen & Lu-Wen Pan & Zi-Juan Yang, 2022. "A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple Transactions," Mathematics, MDPI, vol. 10(23), pages 1-20, November.
    11. Samir A. Abass, 2012. "0-1 integer interval number programming approach for the multilevel generalized assignment problem," E3 Journal of Business Management and Economics., E3 Journals, vol. 3(9), pages 326-329.
    12. Tong Xin & Guolai Yang & Fengjie Xu & Quanzhao Sun & Alexandi Minak, 2021. "Modeling, Simulation and Uncertain Optimization of the Gun Engraving System," Mathematics, MDPI, vol. 9(4), pages 1-25, February.
    13. Rahaman, Mostafijur & Mondal, Sankar Prasad & Alam, Shariful & Metwally, Ahmed Sayed M. & Salahshour, Soheil & Salimi, Mehdi & Ahmadian, Ali, 2022. "Manifestation of interval uncertainties for fractional differential equations under conformable derivative," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    14. Xiaobin Yang & Haitao Lin & Gang Xiao & Huanbin Xue & Xiaopeng Yang, 2019. "Resolution of Max-Product Fuzzy Relation Equation with Interval-Valued Parameter," Complexity, Hindawi, vol. 2019, pages 1-16, February.
    15. Yang, Xiaohui & Wang, Xiaopeng & Deng, Yeheng & Mei, Linghao & Deng, Fuwei & Zhang, Zhonglian, 2023. "Integrated energy system scheduling model based on non-complete interval multi-objective fuzzy optimization," Renewable Energy, Elsevier, vol. 218(C).
    16. Pan, Yushu & Guo, Xinyu & Yang, Shenbo & Tan, Qingbo & Pan, Leiyi & Ju, Liwei & Tan, Zhongfu, 2025. "A two-stage optimal dispatch model for wind-storage-carbon capture power plants considering carbon emission and green certificate trading," Energy, Elsevier, vol. 332(C).
    17. He, Li & Huang, Guo H. & Lu, Hongwei, 2011. "Bivariate interval semi-infinite programming with an application to environmental decision-making analysis," European Journal of Operational Research, Elsevier, vol. 211(3), pages 452-465, June.
    18. Wang, Jiangjiang & Huo, Shuojie & Yan, Rujing & Cui, Zhiheng, 2022. "Leveraging heat accumulation of district heating network to improve performances of integrated energy system under source-load uncertainties," Energy, Elsevier, vol. 252(C).
    19. Mrinal Jana & Geetanjali Panda, 2018. "$$\chi$$ χ -Optimal solution of single objective nonlinear optimization problem with uncertain parameters," OPSEARCH, Springer;Operational Research Society of India, vol. 55(1), pages 165-186, March.
    20. Cai, Pengcheng & Mi, Yang & Ma, Siyuan & Li, Hongzhong & Li, Dongdong & Wang, Peng, 2023. "Hierarchical game for integrated energy system and electricity-hydrogen hybrid charging station under distributionally robust optimization," Energy, Elsevier, vol. 283(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:renene:v:251:y:2025:i:c:s0960148125009784. 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.journals.elsevier.com/renewable-energy .

    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.