IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i7p1793-d1626962.html
   My bibliography  Save this article

Convex Optimization and PV Inverter Control Strategy-Based Research on Active Distribution Networks

Author

Listed:
  • Jiachuan Shi

    (Shandong Key Laboratory of Smart Buildings and Energy Efficiency, School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, China)

  • Sining Hu

    (School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, China)

  • Rao Fu

    (School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, China)

  • Quan Zhang

    (School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, China)

Abstract

Optimizing the operation of active distribution networks (ADNs) has become more challenging because of the uncertainty created by the high penetration level of distributed photovoltaic (PV). From the convex optimization perspective, this paper proposes a two-layer optimization model to simplify the solution of the ADN optimal operation problem. Firstly, to pick out the ADN “key” nodes, a “key” nodes selection approach that used improved K-means clustering algorithm and two indexes (integrated voltage sensitivity and reactive power-balance degree) is introduced. Then, a two-layer ADN optimization model is built using various time scales. The upper layer is a long-time-scale model with on-load tap-changer transformer (OLTC) and capacitor bank (CB), and the lower layer is a short-time-scale optimization model with PV inverters and distributed energy storages (ESs). To take into account the PV users’ interests, maximizing PV active power output is added to the objective. Afterwards, under the application of the second-order cone programming (SOCP) power-flow model, a linearization method of OLTC model and its tap change frequency constraints are proposed. The linear OLTC model, together with the linear models of the other equipment, constructs a mixed-integer second-order cone convex optimization (MISOCP) model. Finally, the effectiveness of the proposed method is verified by solving the IEEE33 node system using the CPLEX solver.

Suggested Citation

  • Jiachuan Shi & Sining Hu & Rao Fu & Quan Zhang, 2025. "Convex Optimization and PV Inverter Control Strategy-Based Research on Active Distribution Networks," Energies, MDPI, vol. 18(7), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:7:p:1793-:d:1626962
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/7/1793/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/7/1793/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Jingjing & Yao, Liangzhong & Liang, Jun & Wang, Jun & Cheng, Fan, 2025. "Distributed optimization strategy for networked microgrids based on network partitioning," Applied Energy, Elsevier, vol. 378(PB).
    2. Meng, Lingzhuochao & Yang, Xiyun & Zhu, Jiang & Wang, Xinzhe & Meng, Xin, 2024. "Network partition and distributed voltage coordination control strategy of active distribution network system considering photovoltaic uncertainty," Applied Energy, Elsevier, vol. 362(C).
    3. Luo, Lizi & Gu, Wei & Zhang, Xiao-Ping & Cao, Ge & Wang, Weijun & Zhu, Gang & You, Dingjun & Wu, Zhi, 2018. "Optimal siting and sizing of distributed generation in distribution systems with PV solar farm utilized as STATCOM (PV-STATCOM)," Applied Energy, Elsevier, vol. 210(C), pages 1092-1100.
    4. Xiang, Yue & Lu, Yu & Liu, Junyong, 2023. "Deep reinforcement learning based topology-aware voltage regulation of distribution networks with distributed energy storage," Applied Energy, Elsevier, vol. 332(C).
    5. Li, Yiming & Liu, Che & Zhang, Lizhi & Sun, Bo, 2021. "A partition optimization design method for a regional integrated energy system based on a clustering algorithm," Energy, Elsevier, vol. 219(C).
    6. Wang, Yi & Ma, Jiahao & Gao, Ning & Wen, Qingsong & Sun, Liang & Guo, Hongye, 2023. "Federated fuzzy k-means for privacy-preserving behavior analysis in smart grids," Applied Energy, Elsevier, vol. 331(C).
    7. Mostafa Elshahed & Mohamed A. Tolba & Ali M. El-Rifaie & Ahmed Ginidi & Abdullah Shaheen & Shazly A. Mohamed, 2023. "An Artificial Rabbits’ Optimization to Allocate PVSTATCOM for Ancillary Service Provision in Distribution Systems," Mathematics, MDPI, vol. 11(2), pages 1-19, January.
    8. Suryakiran, B.V. & Nizami, Sohrab & Verma, Ashu & Saha, Tapan Kumar & Mishra, Sukumar, 2023. "A DSO-based day-ahead market mechanism for optimal operational planning of active distribution network," Energy, Elsevier, vol. 282(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. Víctor M. Garrido-Arévalo & Walter Gil-González & Oscar Danilo Montoya & Harold R. Chamorro & Jorge Mírez, 2023. "Efficient Allocation and Sizing the PV-STATCOMs in Electrical Distribution Grids Using Mixed-Integer Convex Approximation," Energies, MDPI, vol. 16(20), pages 1-19, October.
    2. Guido C. Guerrero-Liquet & Santiago Oviedo-Casado & J. M. Sánchez-Lozano & M. Socorro García-Cascales & Javier Prior & Antonio Urbina, 2018. "Determination of the Optimal Size of Photovoltaic Systems by Using Multi-Criteria Decision-Making Methods," Sustainability, MDPI, vol. 10(12), pages 1-18, December.
    3. Peng, Weike & Gao, Jiaxin & Chen, Yuntian & Wang, Shengwei, 2024. "Bridging data barriers among participants: Assessing the potential of geoenergy through federated learning," Applied Energy, Elsevier, vol. 367(C).
    4. Xinghua Wang & Fucheng Zhong & Yilin Xu & Xixian Liu & Zezhong Li & Jianan Liu & Zhuoli Zhao, 2023. "Extraction and Joint Method of PV–Load Typical Scenes Considering Temporal and Spatial Distribution Characteristics," Energies, MDPI, vol. 16(18), pages 1-19, September.
    5. Zhu, Xingxu & Hou, Xiangchen & Li, Junhui & Yan, Gangui & Li, Cuiping & Wang, Dongbo, 2023. "Distributed online prediction optimization algorithm for distributed energy resources considering the multi-periods optimal operation," Applied Energy, Elsevier, vol. 348(C).
    6. Ding, Yanyan & Jian, Sisi, 2024. "Strategic investment in charging infrastructure: Sharing costs or taking over?," Applied Energy, Elsevier, vol. 376(PA).
    7. Li, Yinxiao & Wang, Yi & Chen, Qixin, 2020. "Study on the impacts of meteorological factors on distributed photovoltaic accommodation considering dynamic line parameters," Applied Energy, Elsevier, vol. 259(C).
    8. Luo, Lizi & Wu, Zhi & Gu, Wei & Huang, He & Gao, Song & Han, Jun, 2020. "Coordinated allocation of distributed generation resources and electric vehicle charging stations in distribution systems with vehicle-to-grid interaction," Energy, Elsevier, vol. 192(C).
    9. Zhao, Yincheng & Zhang, Guozhou & Hu, Weihao & Huang, Qi & Chen, Zhe & Blaabjerg, Frede, 2023. "Meta-learning based voltage control strategy for emergency faults of active distribution networks," Applied Energy, Elsevier, vol. 349(C).
    10. 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).
    11. Chen, Bingyang & Zeng, Xingjie & Zhang, Weishan & Fan, Lulu & Cao, Shaohua & Zhou, Jiehan, 2023. "Knowledge sharing-based multi-block federated learning for few-shot oil layer identification," Energy, Elsevier, vol. 283(C).
    12. Gheouany, Saad & Ouadi, Hamid & El Bakali, Saida, 2024. "Optimal active and reactive energy management for a smart microgrid system under the Moroccan grid pricing code," Energy, Elsevier, vol. 306(C).
    13. Singh, Pushpendra & Meena, Nand K. & Yang, Jin & Vega-Fuentes, Eduardo & Bishnoi, Shree Krishna, 2020. "Multi-criteria decision making monarch butterfly optimization for optimal distributed energy resources mix in distribution networks," Applied Energy, Elsevier, vol. 278(C).
    14. Temitayo O. Olowu & Aditya Sundararajan & Masood Moghaddami & Arif I. Sarwat, 2018. "Future Challenges and Mitigation Methods for High Photovoltaic Penetration: A Survey," Energies, MDPI, vol. 11(7), pages 1-32, July.
    15. Oscar Danilo Montoya & Walter Gil-González & Jesus C. Hernández, 2023. "Efficient Integration of Fixed-Step Capacitor Banks and D-STATCOMs in Radial and Meshed Distribution Networks Considering Daily Operation Curves," Energies, MDPI, vol. 16(8), pages 1-23, April.
    16. Shang, Yitong & Li, Sen, 2024. "FedPT-V2G: Security enhanced federated transformer learning for real-time V2G dispatch with non-IID data," Applied Energy, Elsevier, vol. 358(C).
    17. Vavilapalli, Sridhar & Umashankar, S. & Sanjeevikumar, P. & Ramachandaramurthy, Vigna K. & Mihet-Popa, Lucian & Fedák, Viliam, 2018. "Three-stage control architecture for cascaded H-Bridge inverters in large-scale PV systems – Real time simulation validation," Applied Energy, Elsevier, vol. 229(C), pages 1111-1127.
    18. Reza Sirjani, 2018. "Optimal Placement and Sizing of PV-STATCOM in Power Systems Using Empirical Data and Adaptive Particle Swarm Optimization," Sustainability, MDPI, vol. 10(3), pages 1-15, March.
    19. Mostafa Elshahed & Mohamed A. Tolba & Ali M. El-Rifaie & Ahmed Ginidi & Abdullah Shaheen & Shazly A. Mohamed, 2023. "An Artificial Rabbits’ Optimization to Allocate PVSTATCOM for Ancillary Service Provision in Distribution Systems," Mathematics, MDPI, vol. 11(2), pages 1-19, January.
    20. Ghareeb Moustafa & Mostafa Elshahed & Ahmed R. Ginidi & Abdullah M. Shaheen & Hany S. E. Mansour, 2023. "A Gradient-Based Optimizer with a Crossover Operator for Distribution Static VAR Compensator (D-SVC) Sizing and Placement in Electrical Systems," Mathematics, MDPI, vol. 11(5), pages 1-30, February.

    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:18:y:2025:i:7:p:1793-:d:1626962. 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.