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Load Concentration Factor Based Analytical Method for Optimal Placement of Multiple Distribution Generators for Loss Minimization and Voltage Profile Improvement

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  • Mohsin Shahzad

    (Energy Department, AIT Austrian Institute of Technology, Vienna 1210, Austria
    These authors contributed equally to this work.)

  • Ishtiaq Ahmad

    (Energy Department, AIT Austrian Institute of Technology, Vienna 1210, Austria
    These authors contributed equally to this work.)

  • Wolfgang Gawlik

    (Institute of Energy Systems and Electrical Drives, TU Wien, Wien 1040, Austria
    These authors contributed equally to this work.)

  • Peter Palensky

    (Department Electrical Sustainable Energy, TU Delft, Delft 2628 CD, The Netherlands
    These authors contributed equally to this work.)

Abstract

This paper presents novel separate methods for finding optimal locations, sizes of multiple distributed generators (DGs) simultaneously and operational power factor in order to minimize power loss and improve the voltage profile in the distribution system. A load concentration factor (LCF) is introduced to select the optimal location(s) for DG placement. Exact loss formula based analytical expressions are derived for calculating the optimal sizes of any number of DGs simultaneously. Since neither optimizing the location nor optimizing the size is done iteratively, like existing methods do, the simulation time is reduced considerably. The exhaustive method is used to find the operational power factor, and it is shown with the results that the losses are further reduced and voltage profile is improved by operating the DGs at operational power factor. Results for power loss reduction and voltage profile improvement in IEEE 37 and 119 node radial distribution systems are presented and compared with the the loss sensitivity factor (LSF) method, improved analytical (IA) and exhaustive load flow method (ELF). The comparison for operational power factor and other power factors is also presented.

Suggested Citation

  • Mohsin Shahzad & Ishtiaq Ahmad & Wolfgang Gawlik & Peter Palensky, 2016. "Load Concentration Factor Based Analytical Method for Optimal Placement of Multiple Distribution Generators for Loss Minimization and Voltage Profile Improvement," Energies, MDPI, vol. 9(4), pages 1-21, April.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:4:p:287-:d:68208
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    References listed on IDEAS

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    1. Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2013. "Analytical strategies for renewable distributed generation integration considering energy loss minimization," Applied Energy, Elsevier, vol. 105(C), pages 75-85.
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    Cited by:

    1. Ahmed Al Ameri & Aouchenni Ounissa & Cristian Nichita & Aouzellag Djamal, 2017. "Power Loss Analysis for Wind Power Grid Integration Based on Weibull Distribution," Energies, MDPI, vol. 10(4), pages 1-16, April.
    2. Kadir Doğanşahin & Bedri Kekezoğlu & Recep Yumurtacı & Ozan Erdinç & João P. S. Catalão, 2018. "Maximum Permissible Integration Capacity of Renewable DG Units Based on System Loads," Energies, MDPI, vol. 11(1), pages 1-16, January.
    3. Sachin Kumar & Kumari Sarita & Akanksha Singh S Vardhan & Rajvikram Madurai Elavarasan & R. K. Saket & Narottam Das, 2020. "Reliability Assessment of Wind-Solar PV Integrated Distribution System Using Electrical Loss Minimization Technique," Energies, MDPI, vol. 13(21), pages 1-30, October.
    4. Mohsin Shahzad & Arsalan Qadir & Noman Ullah & Zahid Mahmood & Naufal Mohamad Saad & Syed Saad Azhar Ali, 2022. "Optimization of On-Grid Hybrid Renewable Energy System: A Case Study on Azad Jammu and Kashmir," Sustainability, MDPI, vol. 14(10), pages 1-21, May.
    5. Seyed Siavash Karimi Madahi & Andrija T. Sarić, 2020. "Multi-Criteria Optimal Sizing and Allocation of Renewable and Non-Renewable Distributed Generation Resources at 63 kV/20 kV Substations," Energies, MDPI, vol. 13(20), pages 1-22, October.
    6. Mohsin Shahzad & Waseem Akram & Muhammad Arif & Uzair Khan & Barkat Ullah, 2021. "Optimal Siting and Sizing of Distributed Generators by Strawberry Plant Propagation Algorithm," Energies, MDPI, vol. 14(6), pages 1-13, March.
    7. Jingmin Wang & Wenhai Yang & Huaxin Cheng & Lingyu Huang & Yajing Gao, 2017. "The Optimal Configuration Scheme of the Virtual Power Plant Considering Benefits and Risks of Investors," Energies, MDPI, vol. 10(7), pages 1-12, July.
    8. 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.

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