IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i15p5800-d1210606.html
   My bibliography  Save this article

Assessment of Converter Performance in Hybrid AC-DC Power System under Optimal Power Flow with Minimum Number of DC Link Control Variables

Author

Listed:
  • Chintan Patel

    (National Institute of Technology Silchar, Silchar 788010, India)

  • Tanmoy Malakar

    (National Institute of Technology Silchar, Silchar 788010, India)

  • S. Sreejith

    (National Institute of Technology Silchar, Silchar 788010, India)

Abstract

This paper presents a strategy to evaluate the performances of converter stations under the optimized operating points of hybrid AC-DC power systems with a reduced number of DC link variables. Compared to previous works reported with five DC-side control variables (CVs), the uniqueness of the presented optimal power flow (OPF) formulation lies within the selection of only two DC-side control variables (CVs), such as the inverter voltage and current in the DC link, apart from the conventional AC-side variables. Previous research has mainly been focused on optimizing hybrid power system performance through OPF-based formulations, but has mostly ignored the associated converter performances. Hence, in this study, converter performance, in terms of ripple and harmonics in DC voltage and AC current and the utilization of the converter infrastructure, is evaluated. The minimization of active power loss is taken as an objective function, and the problem is solved for a modified IEEE 30 bus system using a recently developed and very efficient Archimedes optimization algorithm (AOA). Case studies are performed to assess the efficacy of the presented OPF model in power systems, as well as converter performance. Furthermore, the results are extended to assess the applicability of the proposed model to the allocation of photovoltaic (PV)-type distributed generations (DGs) in hybrid AC-DC systems. The average improvement in power loss is found to be around 7.5% compared to the reported results. Furthermore, an approximate 10% improvement in converter power factor and an approximate 50% reduction in ripple factor are achieved.

Suggested Citation

  • Chintan Patel & Tanmoy Malakar & S. Sreejith, 2023. "Assessment of Converter Performance in Hybrid AC-DC Power System under Optimal Power Flow with Minimum Number of DC Link Control Variables," Energies, MDPI, vol. 16(15), pages 1-20, August.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:15:p:5800-:d:1210606
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/15/5800/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/15/5800/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Diego Oliveira & Gustavo C. Borges Leal & Danilo Herrera & Eduardo Galván-Díez & Juan M. Carrasco & Mauricio Aredes, 2023. "An Analysis on the VSC-HVDC Contribution for the Static Voltage Stability Margin and Effective Short Circuit Ratio Enhancement in Hybrid Multi-Infeed HVDC Systems," Energies, MDPI, vol. 16(1), pages 1-28, January.
    2. Yanwen Wang & Lingjie Wu & Shaoyang Chen, 2023. "A Simplified Model of the HVDC Transmission System for Sub-Synchronous Oscillations," Sustainability, MDPI, vol. 15(9), pages 1-15, April.
    3. Abha Pragati & Manohar Mishra & Pravat Kumar Rout & Debadatta Amaresh Gadanayak & Shazia Hasan & B. Rajanarayan Prusty, 2023. "A Comprehensive Survey of HVDC Protection System: Fault Analysis, Methodology, Issues, Challenges, and Future Perspective," Energies, MDPI, vol. 16(11), pages 1-39, May.
    4. Mohammad Abdul Baseer & Ibrahim Alsaduni, 2023. "A Novel Renewable Smart Grid Model to Sustain Solar Power Generation," Energies, MDPI, vol. 16(12), pages 1-17, June.
    5. 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).
    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. Sahebkar Farkhani, Jalal & Çelik, Özgür & Ma, Kaiqi & Bak, Claus Leth & Chen, Zhe, 2024. "A comprehensive review of potential protection methods for VSC multi-terminal HVDC systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    3. Dong, Jizhe & Han, Shunjie & Shao, Xiangxin & Tang, Like & Chen, Renhui & Wu, Longfei & Zheng, Cunlong & Li, Zonghao & Li, Haolin, 2021. "Day-ahead wind-thermal unit commitment considering historical virtual wind power data," Energy, Elsevier, vol. 235(C).
    4. Zhu, Yansong & Liu, Jizhen & Hu, Yong & Xie, Yan & Zeng, Deliang & Li, Ruilian, 2024. "Distributionally robust optimization model considering deep peak shaving and uncertainty of renewable energy," Energy, Elsevier, vol. 288(C).
    5. Jiang, Sufan & Wu, Chuanshen & Gao, Shan & Pan, Guangsheng & Liu, Yu & Zhao, Xin & Wang, Sicheng, 2022. "Robust frequency risk-constrained unit commitment model for AC-DC system considering wind uncertainty," Renewable Energy, Elsevier, vol. 195(C), pages 395-406.
    6. Qiu, Haifeng & Sun, Qirun & Lu, Xi & Beng Gooi, Hoay & Zhang, Suhan, 2022. "Optimality-feasibility-aware multistage unit commitment considering nonanticipative realization of uncertainty," Applied Energy, Elsevier, vol. 327(C).
    7. 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).
    8. Biéron, M. & Le Dréau, J. & Haas, B., 2023. "Assessment of the marginal technologies reacting to demand response events: A French case-study," Energy, Elsevier, vol. 275(C).
    9. Shengshi Wang & Lianyong Zuo & Miao Li & Qiao Wang & Xizhen Xue & Qicong Liu & Shuai Jiang & Jian Wang & Xitong Duan, 2021. "The Data-Driven Modeling of Pressure Loss in Multi-Batch Refined Oil Pipelines with Drag Reducer Using Long Short-Term Memory (LSTM) Network," Energies, MDPI, vol. 14(18), pages 1-25, September.
    10. Satyajit Mohanty & Ankit Bhanja & Shivam Prakash Gautam & Dhanamjayulu Chittathuru & Santanu Kumar Dash & Mrutyunjaya Mangaraj & Ravikumar Chinthaginjala & Abdullah M. Alamri, 2023. "Review of a Comprehensive Analysis of Planning, Functionality, Control, and Protection for Direct Current Microgrids," Sustainability, MDPI, vol. 15(21), pages 1-28, October.
    11. Si, Fangyuan & Han, Yinghua & Zhao, Qiang & Wang, Jinkuan, 2020. "Cost-effective operation of the urban energy system with variable supply and demand via coordination of multi-energy flows," Energy, Elsevier, vol. 203(C).
    12. Qiu, Haifeng & You, Fengqi, 2020. "Decentralized-distributed robust electric power scheduling for multi-microgrid systems," Applied Energy, Elsevier, vol. 269(C).
    13. Haiyan Zheng & Liying Huang & Ran Quan, 2023. "Mixed-Integer Conic Formulation of Unit Commitment with Stochastic Wind Power," Mathematics, MDPI, vol. 11(2), pages 1-16, January.
    14. Jiménez, Diego & Angulo, Alejandro & Street, Alexandre & Mancilla-David, Fernando, 2023. "A closed-loop data-driven optimization framework for the unit commitment problem: A Q-learning approach under real-time operation," Applied Energy, Elsevier, vol. 330(PB).
    15. Qing, Ke & Du, Yuefang & Huang, Qi & Duan, Chao & Hu, Weihao, 2024. "Energy scheduling for microgrids with renewable energy sources considering an adjustable convex hull based uncertainty set," Renewable Energy, Elsevier, vol. 220(C).
    16. Yufei Wang & Haiyun Wang & Jiahui Wu, 2023. "Analysis of Asymmetric Fault Commutation Failure in HVDC System Considering Instantaneous Variation of DC Current," Sustainability, MDPI, vol. 15(15), pages 1-18, July.
    17. Wu, Yunyun & Fang, Jiakun & Ai, Xiaomeng & Xue, Xizhen & Cui, Shichang & Chen, Xia & Wen, Jinyu, 2023. "Robust co-planning of AC/DC transmission network and energy storage considering uncertainty of renewable energy," Applied Energy, Elsevier, vol. 339(C).
    18. Nikolaidis, Pavlos & Poullikkas, Andreas, 2021. "A novel cluster-based spinning reserve dynamic model for wind and PV power reinforcement," Energy, Elsevier, vol. 234(C).
    19. Zhang, Menglin & Wu, Qiuwei & Wen, Jinyu & Lin, Zhongwei & Fang, Fang & Chen, Qun, 2021. "Optimal operation of integrated electricity and heat system: A review of modeling and solution methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    20. 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).

    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:15:p:5800-:d:1210606. 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.