IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i15p5592-d877938.html
   My bibliography  Save this article

A Substation-Based Optimal Photovoltaic Generation System Placement Considering Multiple Evaluation Indices

Author

Listed:
  • Rong-Ceng Leou

    (Department of Electrical Engineering, Cheng Shiu University, Kaohsiung 833301, Taiwan)

Abstract

The placement of the photovoltaic generation system (PVGS) and operation of the on-load tap changer (OLTC) should have great impacts on the system loss and voltage quality, which are the main concerns of the distribution operator. Considering these multiple evaluation indices and other constraints, this paper proposed a substation-based optimal PVGS placement and OLTC operation model. The objective function that was used to evaluate the optimal PVGS placement and OLTC operation consists of a minimization of system loss and voltage quality. The model’s constraints contain the voltage and line flow limits, voltage deviations, voltage unbalance, etc. Uncertainties of the load and irradiance are also included in the model. A nondominated sorting genetic algorithm II (NSGA II) is used to solve this multi-objective optimization problem. Comparisons of the substation-based and feeder-based planning are also studied in this paper. The test results demonstrate the substation-based planning could obtain a better solution.

Suggested Citation

  • Rong-Ceng Leou, 2022. "A Substation-Based Optimal Photovoltaic Generation System Placement Considering Multiple Evaluation Indices," Energies, MDPI, vol. 15(15), pages 1-18, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5592-:d:877938
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/15/5592/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/15/5592/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kucuksari, Sadik & Khaleghi, Amirreza M. & Hamidi, Maryam & Zhang, Ye & Szidarovszky, Ferenc & Bayraksan, Guzin & Son, Young-Jun, 2014. "An Integrated GIS, optimization and simulation framework for optimal PV size and location in campus area environments," Applied Energy, Elsevier, vol. 113(C), pages 1601-1613.
    2. Oludamilare Bode Adewuyi & Ayooluwa Peter Adeagbo & Isaiah Gbadegesin Adebayo & Harun Or Rashid Howlader & Yanxia Sun, 2021. "Modified Analytical Approach for PV-DGs Integration into a Radial Distribution Network Considering Loss Sensitivity and Voltage Stability," Energies, MDPI, vol. 14(22), pages 1-20, November.
    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. Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2014. "An optimal investment planning framework for multiple distributed generation units in industrial distribution systems," Applied Energy, Elsevier, vol. 124(C), pages 62-72.
    2. Zhong, Qing & Tong, Daoqin, 2020. "Spatial layout optimization for solar photovoltaic (PV) panel installation," Renewable Energy, Elsevier, vol. 150(C), pages 1-11.
    3. Ren, Haoshan & Ma, Zhenjun & Chan, Antoni B. & Sun, Yongjun, 2023. "Optimal planning of municipal-scale distributed rooftop photovoltaic systems with maximized solar energy generation under constraints in high-density cities," Energy, Elsevier, vol. 263(PA).
    4. Gubbala Venkata Naga Lakshmi & Askani Jaya Laxmi & Venkataramana Veeramsetty & Surender Reddy Salkuti, 2022. "Optimal Placement of Distributed Generation Based on Power Quality Improvement Using Self-Adaptive Lévy Flight Jaya Algorithm," Clean Technol., MDPI, vol. 4(4), pages 1-13, November.
    5. Jung, Seunghoon & Jeoung, Jaewon & Kang, Hyuna & Hong, Taehoon, 2021. "Optimal planning of a rooftop PV system using GIS-based reinforcement learning," Applied Energy, Elsevier, vol. 298(C).
    6. Amro M Elshurafa & Abdel Rahman Muhsen, 2019. "The Upper Limit of Distributed Solar PV Capacity in Riyadh: A GIS-Assisted Study," Sustainability, MDPI, vol. 11(16), pages 1-20, August.
    7. Mohamed Els. S. Abdelwareth & Dedet Candra Riawan & Chow Chompoo-inwai, 2023. "Optimum Generated Power for a Hybrid DG/PV/Battery Radial Network Using Meta-Heuristic Algorithms Based DG Allocation," Sustainability, MDPI, vol. 15(13), pages 1-25, July.
    8. Shafiullah, Md & Rahman, Syed Masiur & Mortoja, Md. Golam & Al-Ramadan, Baqer, 2016. "Role of spatial analysis technology in power system industry: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 584-595.
    9. Costa, Fabrício Rodrigues & Ribeiro, Carlos Antonio Alvares Soares & Marcatti, Gustavo Eduardo & Lorenzon, Alexandre Simões & Teixeira, Thaisa Ribeiro & Domingues, Getulio Fonseca & Castro, Nero Lemos, 2020. "GIS applied to location of bioenergy plants in tropical agricultural areas," Renewable Energy, Elsevier, vol. 153(C), pages 911-918.
    10. Contreras, Javier & Rodríguez, Yeny E., 2014. "GARCH-based put option valuation to maximize benefit of wind investors," Applied Energy, Elsevier, vol. 136(C), pages 259-268.
    11. Thai, Clinton & Brouwer, Jack, 2021. "Challenges estimating distributed solar potential with utilization factors: California universities case study," Applied Energy, Elsevier, vol. 282(PB).
    12. Ehsan Noorollahi & Dawud Fadai & Mohsen Akbarpour Shirazi & Seyed Hassan Ghodsipour, 2016. "Land Suitability Analysis for Solar Farms Exploitation Using GIS and Fuzzy Analytic Hierarchy Process (FAHP)—A Case Study of Iran," Energies, MDPI, vol. 9(8), pages 1-24, August.
    13. Muttaqi, K.M. & Le, An D.T. & Aghaei, J. & Mahboubi-Moghaddam, E. & Negnevitsky, M. & Ledwich, G., 2016. "Optimizing distributed generation parameters through economic feasibility assessment," Applied Energy, Elsevier, vol. 165(C), pages 893-903.
    14. Fu, Xueqian & Chen, Haoyong & Cai, Runqing & Yang, Ping, 2015. "Optimal allocation and adaptive VAR control of PV-DG in distribution networks," Applied Energy, Elsevier, vol. 137(C), pages 173-182.
    15. Habib Ur Rehman & Arif Hussain & Waseem Haider & Sayyed Ahmad Ali & Syed Ali Abbas Kazmi & Muhammad Huzaifa, 2023. "Optimal Planning of Solar Photovoltaic (PV) and Wind-Based DGs for Achieving Techno-Economic Objectives across Various Load Models," Energies, MDPI, vol. 16(5), pages 1-38, March.
    16. Kwon, Sunghoon & Won, Wangyun & Kim, Jiyong, 2016. "A superstructure model of an isolated power supply system using renewable energy: Development and application to Jeju Island, Korea," Renewable Energy, Elsevier, vol. 97(C), pages 177-188.
    17. Srećković, Nevena & Lukač, Niko & Žalik, Borut & Štumberger, Gorazd, 2016. "Determining roof surfaces suitable for the installation of PV (photovoltaic) systems, based on LiDAR (Light Detection And Ranging) data, pyranometer measurements, and distribution network configuratio," Energy, Elsevier, vol. 96(C), pages 404-414.
    18. Mahmoud Aref & Vladislav Oboskalov & Adel El-Shahat & Almoataz Y. Abdelaziz, 2023. "Modified Analytical Technique for Multi-Objective Optimal Placement of High-Level Renewable Energy Penetration Connected to Egyptian Power System," Mathematics, MDPI, vol. 11(4), pages 1-31, February.
    19. Gassar, Abdo Abdullah Ahmed & Cha, Seung Hyun, 2021. "Review of geographic information systems-based rooftop solar photovoltaic potential estimation approaches at urban scales," Applied Energy, Elsevier, vol. 291(C).
    20. Oludamilare Bode Adewuyi & Komla A. Folly & David T. O. Oyedokun & Emmanuel Idowu Ogunwole, 2022. "Power System Voltage Stability Margin Estimation Using Adaptive Neuro-Fuzzy Inference System Enhanced with Particle Swarm Optimization," Sustainability, MDPI, vol. 14(22), pages 1-17, November.

    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:15:y:2022:i:15:p:5592-:d:877938. 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.