IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v404y2026ics0306261925017891.html

Maximizing solar share using robust system reserve for optimal operation of energy storage-integrated hybrid power systems

Author

Listed:
  • Saeed, Rana Muhammad Musharraf
  • Khan, Naveed Ahmed
  • Shakir, Mustafa
  • Awan, Ahmed Bilal

Abstract

In hybrid power systems, the effective deployment of energy storage systems is a challenging task due to the unpredictable and intermittent nature of renewable energy sources. This paper proposes an operational model for solar-integrated hybrid power systems to address key issues, including economic operation, reliable solar energy integration, energy deficits, and the allocation of overall system reserves, alongside efficient storage management. A mixed-integer optimization model is formulated to minimize overall system operating costs, maximize solar energy share, and maintain robust reserve limits, subject to practical constraints. To allocate appropriate reserves, a contingency-based system reserve is formulated to ensure reliable operation under simultaneous solar and thermal contingencies. The joint optimization problem is solved by decomposing it into sub problems. The solution employs Lagrange relaxation, binary search lambda iteration, contingency based system reserve analysis, and binary integer programming. Additionally, a Pareto-optimal solution is presented to balance the maximization of solar power plants and the minimization of solar energy costs, ensuring a reliable solar energy share.

Suggested Citation

  • Saeed, Rana Muhammad Musharraf & Khan, Naveed Ahmed & Shakir, Mustafa & Awan, Ahmed Bilal, 2026. "Maximizing solar share using robust system reserve for optimal operation of energy storage-integrated hybrid power systems," Applied Energy, Elsevier, vol. 404(C).
    • Handle: RePEc:eee:appene:v:404:y:2026:i:c:s0306261925017891
    DOI: 10.1016/j.apenergy.2025.127059
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261925017891
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2025.127059?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. Anatolijs Mahnitko & Tatjana Lomane & Inga Zicmane, 2025. "Problematic Aspects of Energy Systems with a High Penetration of Renewable Energy Sources," Energies, MDPI, vol. 18(16), pages 1-14, August.
    2. Rana Muhammad Musharraf Saeed & Naveed Ahmed Khan & Mustafa Shakir & Guftaar Ahmad Sardar Sidhu & Ahmed Bilal Awan & Mohammad Abdul Baseer, 2024. "Maximizing Solar Share in Robust System Spinning Reserve-Constrained Economic Operation of Hybrid Power Systems," Energies, MDPI, vol. 17(11), pages 1-22, June.
    3. Fatemeh Marzbani & Akmal Abdelfatah, 2024. "Economic Dispatch Optimization Strategies and Problem Formulation: A Comprehensive Review," Energies, MDPI, vol. 17(3), pages 1-31, January.
    4. Wei, Xuan & Xu, Yinliang & Sun, Hongbin & Bai, Xiang & Chang, Xinyue & Xue, Yixun, 2024. "Day-ahead optimal dispatch of a virtual power plant in the joint energy-reserve-carbon market," Applied Energy, Elsevier, vol. 356(C).
    5. Wang, Xinyue & Zhong, Haiwang & Zhang, Guanglun & Ruan, Guangchun & He, Yiliu & Yu, Zekuan, 2024. "Adaptive look-ahead economic dispatch based on deep reinforcement learning," Applied Energy, Elsevier, vol. 353(PB).
    6. Nikolaidis, Pavlos & Poullikkas, Andreas, 2021. "A novel cluster-based spinning reserve dynamic model for wind and PV power reinforcement," Energy, Elsevier, vol. 234(C).
    7. Zhou, Bo & Ai, Xiaomeng & Fang, Jiakun & Yao, Wei & Zuo, Wenping & Chen, Zhe & Wen, Jinyu, 2019. "Data-adaptive robust unit commitment in the hybrid AC/DC power system," Applied Energy, Elsevier, vol. 254(C).
    8. Quan, Hao & Srinivasan, Dipti & Khambadkone, Ashwin M. & Khosravi, Abbas, 2015. "A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources," Applied Energy, Elsevier, vol. 152(C), pages 71-82.
    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. Jiang, Sufan & Gao, Shan & Pan, Guangsheng & Zhao, Xin & Liu, Yu & Guo, Yasen & Wang, Sicheng, 2020. "A novel robust security constrained unit commitment model considering HVDC regulation," Applied Energy, Elsevier, vol. 278(C).
    2. Jiang, Sufan & Gao, Shan & Pan, Guangsheng & Liu, Yu & Wu, Chuanshen & Wang, Sicheng, 2021. "Congestion-aware robust security constrained unit commitment model for AC-DC grids," Applied Energy, Elsevier, vol. 304(C).
    3. Abdin, Adam F. & Caunhye, Aakil & Zio, Enrico & Cardin, Michel-Alexandre, 2022. "Optimizing generation expansion planning with operational uncertainty: A multistage adaptive robust approach," Applied Energy, Elsevier, vol. 306(PA).
    4. Zhihan Shi & Weisong Han & Guangming Zhang & Zhiqing Bai & Mingxiang Zhu & Xiaodong Lv, 2022. "Research on Low-Carbon Energy Sharing through the Alliance of Integrated Energy Systems with Multiple Uncertainties," Energies, MDPI, vol. 15(24), pages 1-20, December.
    5. Ma, Yixiang & Yu, Lean & Zhang, Guoxing & Lu, Zhiming & Wu, Jiaqian, 2023. "Source-load uncertainty-based multi-objective multi-energy complementary optimal scheduling," Renewable Energy, Elsevier, vol. 219(P1).
    6. Tascikaraoglu, Akin & Sanandaji, Borhan M. & Poolla, Kameshwar & Varaiya, Pravin, 2016. "Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform," Applied Energy, Elsevier, vol. 165(C), pages 735-747.
    7. Juangsa, Firman Bagja & Prananto, Lukman Adi & Mufrodi, Zahrul & Budiman, Arief & Oda, Takuya & Aziz, Muhammad, 2018. "Highly energy-efficient combination of dehydrogenation of methylcyclohexane and hydrogen-based power generation," Applied Energy, Elsevier, vol. 226(C), pages 31-38.
    8. Wang, Zhiwen & Shen, Chen & Liu, Feng, 2018. "A conditional model of wind power forecast errors and its application in scenario generation," Applied Energy, Elsevier, vol. 212(C), pages 771-785.
    9. Tian, Zhirui & Liu, Weican & Zhang, Jiahao & Sun, Wenpu & Wu, Chenye, 2025. "EDformer family: End-to-end multi-task load forecasting frameworks for day-ahead economic dispatch," Applied Energy, Elsevier, vol. 383(C).
    10. Chen, Ting & Vandendriessche, Frederik, 2023. "Enabling independent flexibility service providers to participate in electricity markets: A legal analysis of the Belgium case," Utilities Policy, Elsevier, vol. 81(C).
    11. Hao, Junhong & Feng, Xiaolong & Chen, Xiangru & Jin, Xilin & Wang, Xingce & Hao, Tong & Hong, Feng & Du, Xiaoze, 2024. "Optimal scheduling of active distribution network considering symmetric heat and power source-load spatial-temporal characteristics," Applied Energy, Elsevier, vol. 373(C).
    12. Xie, Kaigui & Dong, Jizhe & Singh, Chanan & Hu, Bo, 2016. "Optimal capacity and type planning of generating units in a bundled wind–thermal generation system," Applied Energy, Elsevier, vol. 164(C), pages 200-210.
    13. Mohammad Masih Sediqi & Mohammed Elsayed Lotfy & Abdul Matin Ibrahimi & Tomonobu Senjyu & Narayanan. K, 2019. "Stochastic Unit Commitment and Optimal Power Trading Incorporating PV Uncertainty," Sustainability, MDPI, vol. 11(16), pages 1-16, August.
    14. Díaz, Guzmán & Coto, José & Gómez-Aleixandre, Javier, 2019. "Prediction and explanation of the formation of the Spanish day-ahead electricity price through machine learning regression," Applied Energy, Elsevier, vol. 239(C), pages 610-625.
    15. Wang, Wenxiao & Li, Chaoshun & Liao, Xiang & Qin, Hui, 2017. "Study on unit commitment problem considering pumped storage and renewable energy via a novel binary artificial sheep algorithm," Applied Energy, Elsevier, vol. 187(C), pages 612-626.
    16. Hao, Yinping & He, Qing & Du, Dongmei, 2020. "A trans-critical carbon dioxide energy storage system with heat pump to recover stored heat of compression," Renewable Energy, Elsevier, vol. 152(C), pages 1099-1108.
    17. Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.
    18. Yang, Ting & Zhao, Yingjie & Pen, Haibo & Wang, Zhaoxia, 2018. "Data center holistic demand response algorithm to smooth microgrid tie-line power fluctuation," Applied Energy, Elsevier, vol. 231(C), pages 277-287.
    19. Shi, Shouyuan & Yu, Tao & Lan, Chaofan & Pan, Zhenning, 2024. "Estimating the actual emission cost in an annual compliance cycle: Synergistic generation and carbon trading optimization for price-taking generation companies," Applied Energy, Elsevier, vol. 376(PA).
    20. Muhammad Asghar Majeed & Furqan Asghar & Muhammad Imtiaz Hussain & Waseem Amjad & Anjum Munir & Hammad Armghan & Jun-Tae Kim, 2022. "Adaptive Dynamic Control Based Optimization of Renewable Energy Resources for Grid-Tied Microgrids," Sustainability, MDPI, vol. 14(3), pages 1-14, February.

    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:appene:v:404:y:2026:i:c:s0306261925017891. 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.