IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i24p3254-d703328.html
   My bibliography  Save this article

Assessment of Voltage Imbalance Improvement and Power Loss Reduction in Residential Distribution Systems in Taiwan

Author

Listed:
  • Nien-Che Yang

    (Department of Electrical Engineering, National Taiwan University of Science and Technology, No. 43, Keelung Road, Section 4, Taipei 10607, Taiwan)

  • Yan-Lin Zeng

    (Department of Electrical Engineering, National Taiwan University of Science and Technology, No. 43, Keelung Road, Section 4, Taipei 10607, Taiwan)

  • Tsai-Hsiang Chen

    (Department of Electrical Engineering, National Taiwan University of Science and Technology, No. 43, Keelung Road, Section 4, Taipei 10607, Taiwan)

Abstract

In this study, the non-dominated sorting genetic algorithm II (NSGA-II) is used to optimize the annual phase arrangement of distribution transformers connected to primary feeders to improve three-phase imbalance and reduce power loss. Based on the data of advanced metering infrastructure (AMI), a quasi-real-time ZIP load model and typical sample distribution systems in Taiwan are constructed. The equivalent circuit models and solution algorithms for typical distribution systems in Taiwan are built using the commercial software package MATLAB. A series of simulations, analyses, comparisons, and explorations is executed. Finally, the quantitative evaluation results for improving the voltage imbalance and reducing the power loss are summarized. For the series of studies, the percentage reductions in (1) total power imbalance T S I , (2) total line loss T L L , (3) average voltage drop A V D , (4) total voltage imbalance factors for zero/negative sequences T d 0 / T d 2 , and (5) neutral current of the main transformer I L C O are up to 45.48%, 4.06%, 16.61%, 63.99%, 21.33%, and 88.01%, respectively. The results obtained in this study can be applied for energy saving and can aid the authorities to implement sustainable development policies in Taiwan.

Suggested Citation

  • Nien-Che Yang & Yan-Lin Zeng & Tsai-Hsiang Chen, 2021. "Assessment of Voltage Imbalance Improvement and Power Loss Reduction in Residential Distribution Systems in Taiwan," Mathematics, MDPI, vol. 9(24), pages 1-17, December.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:24:p:3254-:d:703328
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/24/3254/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/24/3254/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Arun Onlam & Daranpob Yodphet & Rongrit Chatthaworn & Chayada Surawanitkun & Apirat Siritaratiwat & Pirat Khunkitti, 2019. "Power Loss Minimization and Voltage Stability Improvement in Electrical Distribution System via Network Reconfiguration and Distributed Generation Placement Using Novel Adaptive Shuffled Frogs Leaping," Energies, MDPI, vol. 12(3), pages 1-12, February.
    2. Zhe Xu & Yingqing Guo & Huarui Yang & Haotian Mao & Zongling Yu & Rui Li, 2020. "One Convenient Method to Calculate Performance and Optimize Configuration for Annular Radiator Using Heat Transfer Unit Simulation," Energies, MDPI, vol. 13(1), pages 1-19, January.
    3. Elma, Onur & Selamogullari, Ugur Savas, 2015. "A new home energy management algorithm with voltage control in a smart home environment," Energy, Elsevier, vol. 91(C), pages 720-731.
    4. Chia-Sheng Tu & Ming-Tang Tsai, 2020. "Optimal Phase Arrangement of Distribution Transformers for System Unbalance Improvement and Loss Reduction," Energies, MDPI, vol. 13(3), pages 1-15, January.
    5. Mingcong Liu & Shaobo Yang & Hongyu Li & Jiayi Xu & Xingfei Li, 2019. "Energy Consumption Analysis and Optimization of the Deep-Sea Self-Sustaining Profile Buoy," Energies, MDPI, vol. 12(12), pages 1-26, June.
    6. Aydin Jadidi & Raimundo Menezes & Nilmar de Souza & Antonio Cezar de Castro Lima, 2019. "Short-Term Electric Power Demand Forecasting Using NSGA II-ANFIS Model," Energies, MDPI, vol. 12(10), pages 1-14, May.
    7. Konak, Abdullah & Coit, David W. & Smith, Alice E., 2006. "Multi-objective optimization using genetic algorithms: A tutorial," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 992-1007.
    8. Kangji Li & Lei Pan & Wenping Xue & Hui Jiang & Hanping Mao, 2017. "Multi-Objective Optimization for Energy Performance Improvement of Residential Buildings: A Comparative Study," Energies, MDPI, vol. 10(2), pages 1-23, February.
    9. Diju Gao & Xuyang Wang & Tianzhen Wang & Yide Wang & Xiaobin Xu, 2018. "An Energy Optimization Strategy for Hybrid Power Ships under Load Uncertainty Based on Load Power Prediction and Improved NSGA-II Algorithm," Energies, MDPI, vol. 11(7), pages 1-14, July.
    10. Davye Mak & Dae-Hyun Choi, 2018. "Hierarchical Look-Ahead Conservation Voltage Reduction Framework Considering Distributed Energy Resources and Demand Reduction," Energies, MDPI, vol. 11(12), pages 1-20, November.
    11. Mingyu Huang & Chongshi Shi & Yu Zhu & Jiaqiao Zhang & Fubao Zhang, 2021. "Design of Gerotor Pump and Influence on Oil Supply System for Hybrid Transmission," Energies, MDPI, vol. 14(18), pages 1-13, September.
    12. Ting-Chia Ou & Wei-Fu Su & Xian-Zong Liu & Shyh-Jier Huang & Te-Yu Tai, 2016. "A Modified Bird-Mating Optimization with Hill-Climbing for Connection Decisions of Transformers," Energies, MDPI, vol. 9(9), pages 1-12, August.
    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. Hasan M. Salman & Jagadeesh Pasupuleti & Ahmad H. Sabry, 2023. "Review on Causes of Power Outages and Their Occurrence: Mitigation Strategies," Sustainability, MDPI, vol. 15(20), pages 1-34, October.

    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. Gupta, Pankaj & Mittal, Garima & Mehlawat, Mukesh Kumar, 2013. "Expected value multiobjective portfolio rebalancing model with fuzzy parameters," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 190-203.
    2. Weifan Zhong & Lijing Du, 2023. "Predicting Traffic Casualties Using Support Vector Machines with Heuristic Algorithms: A Study Based on Collision Data of Urban Roads," Sustainability, MDPI, vol. 15(4), pages 1-18, February.
    3. A.S. Jameel Hassan & Umar Marikkar & G.W. Kasun Prabhath & Aranee Balachandran & W.G. Chaminda Bandara & Parakrama B. Ekanayake & Roshan I. Godaliyadda & Janaka B. Ekanayake, 2021. "A Sensitivity Matrix Approach Using Two-Stage Optimization for Voltage Regulation of LV Networks with High PV Penetration," Energies, MDPI, vol. 14(20), pages 1-24, October.
    4. Pengfei Wang & Jialiang Yi & Mansoureh Zangiabadi & Pádraig Lyons & Phil Taylor, 2017. "Evaluation of Voltage Control Approaches for Future Smart Distribution Networks," Energies, MDPI, vol. 10(8), pages 1-17, August.
    5. Cai, Yuhao & Qian, Xin & Su, Ruihang & Jia, Xiongjie & Ying, Jinhui & Zhao, Tianshou & Jiang, Haoran, 2024. "Thermo-electrochemical modeling of thermally regenerative flow batteries," Applied Energy, Elsevier, vol. 355(C).
    6. Nantian Huang & Hua Peng & Guowei Cai & Jikai Chen, 2016. "Power Quality Disturbances Feature Selection and Recognition Using Optimal Multi-Resolution Fast S-Transform and CART Algorithm," Energies, MDPI, vol. 9(11), pages 1-21, November.
    7. Changyu Zhou & Guohe Huang & Jiapei Chen, 2019. "A Type-2 Fuzzy Chance-Constrained Fractional Integrated Modeling Method for Energy System Management of Uncertainties and Risks," Energies, MDPI, vol. 12(13), pages 1-21, June.
    8. Ahmadi, Mohammad H. & Amin Nabakhteh, Mohammad & Ahmadi, Mohammad-Ali & Pourfayaz, Fathollah & Bidi, Mokhtar, 2017. "Investigation and optimization of performance of nano-scale Stirling refrigerator using working fluid as Maxwell–Boltzmann gases," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 337-350.
    9. Hausken, Kjell & Levitin, Gregory, 2009. "Minmax defense strategy for complex multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 577-587.
    10. Akhlaque Ahmad Khan & Ahmad Faiz Minai & Rupendra Kumar Pachauri & Hasmat Malik, 2022. "Optimal Sizing, Control, and Management Strategies for Hybrid Renewable Energy Systems: A Comprehensive Review," Energies, MDPI, vol. 15(17), pages 1-29, August.
    11. Janssens, Jochen & Van den Bergh, Joos & Sörensen, Kenneth & Cattrysse, Dirk, 2015. "Multi-objective microzone-based vehicle routing for courier companies: From tactical to operational planning," European Journal of Operational Research, Elsevier, vol. 242(1), pages 222-231.
    12. H. Liao & Q. Wu, 2013. "Multi-objective optimization by learning automata," Journal of Global Optimization, Springer, vol. 55(2), pages 459-487, February.
    13. Ahmadi, Mohammad H. & Ahmadi, Mohammad-Ali & Maleki, Akbar & Pourfayaz, Fathollah & Bidi, Mokhtar & Açıkkalp, Emin, 2017. "Exergetic sustainability evaluation and multi-objective optimization of performance of an irreversible nanoscale Stirling refrigeration cycle operating with Maxwell–Boltzmann gas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 80-92.
    14. Abokersh, Mohamed Hany & Vallès, Manel & Cabeza, Luisa F. & Boer, Dieter, 2020. "A framework for the optimal integration of solar assisted district heating in different urban sized communities: A robust machine learning approach incorporating global sensitivity analysis," Applied Energy, Elsevier, vol. 267(C).
    15. Nizami, M.S.H. & Hossain, M.J. & Amin, B.M. Ruhul & Fernandez, Edstan, 2020. "A residential energy management system with bi-level optimization-based bidding strategy for day-ahead bi-directional electricity trading," Applied Energy, Elsevier, vol. 261(C).
    16. Briš, Radim & Byczanski, Petr & Goňo, Radomír & Rusek, Stanislav, 2017. "Discrete maintenance optimization of complex multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 80-89.
    17. Schmidt, Adam & Albert, Laura A. & Zheng, Kaiyue, 2021. "Risk management for cyber-infrastructure protection: A bi-objective integer programming approach," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    18. Zio, E. & Pedroni, N., 2010. "An optimized Line Sampling method for the estimation of the failure probability of nuclear passive systems," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1300-1313.
    19. Juan Carlos Bravo-Rodríguez & Juan Carlos del-Pino-López & Pedro Cruz-Romero, 2019. "A Survey on Optimization Techniques Applied to Magnetic Field Mitigation in Power Systems," Energies, MDPI, vol. 12(7), pages 1-20, April.
    20. Sarid, A. & Tzur, M., 2018. "The multi-scale generation and transmission expansion model," Energy, Elsevier, vol. 148(C), pages 977-991.

    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:jmathe:v:9:y:2021:i:24:p:3254-:d:703328. 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.