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Grey wolf optimizer based placement and sizing of multiple distributed generation in the distribution system

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  • Sultana, U.
  • Khairuddin, Azhar B.
  • Mokhtar, A.S.
  • Zareen, N.
  • Sultana, Beenish

Abstract

The role of distributed generation (DG) for empowering the performance of the distribution system is becoming better known in the power sector. This paper presents a competent optimization approach based on the Grey Wolf Optimizer (GWO) for multiple DG allocation (i.e. siting and sizing) in the distribution system. The multiple objectives are to minimize reactive power losses and improve the voltage profile of the distribution system, without violating power system constraints. GWO is a newly proposed meta-heuristic optimization algorithm, inspired by grey wolves (Canis lupus). Alpha, beta, delta, and omega are the four categories of grey wolves, which are utilized to simulate leadership hierarchy. Despite this, GWO takes three main steps in hunting: searching for prey, encircling prey and attacking prey in order to complete the optimization process. The proposed study, based on GWO, is compared with the Gravitational Search Algorithm (GSA) and the Bat Algorithm (BA) based meta-heuristic methods. The different case studies of multiple DG type allocations in a 69-bus distribution system are carried out to show the effectiveness of the proposed methodology and distribution system performance. The comparative numeric results, voltage profile and convergence characteristic curves indicate better performance of the GWO against the GSA and BA.

Suggested Citation

  • Sultana, U. & Khairuddin, Azhar B. & Mokhtar, A.S. & Zareen, N. & Sultana, Beenish, 2016. "Grey wolf optimizer based placement and sizing of multiple distributed generation in the distribution system," Energy, Elsevier, vol. 111(C), pages 525-536.
    • Handle: RePEc:eee:energy:v:111:y:2016:i:c:p:525-536
    DOI: 10.1016/j.energy.2016.05.128
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    9. Shahid Nawaz Khan & Syed Ali Abbas Kazmi & Abdullah Altamimi & Zafar A. Khan & Mohammed A. Alghassab, 2022. "Smart Distribution Mechanisms—Part I: From the Perspectives of Planning," Sustainability, MDPI, vol. 14(23), pages 1-109, December.
    10. Salil Madhav Dubey & Hari Mohan Dubey & Surender Reddy Salkuti, 2022. "Modified Quasi-Opposition-Based Grey Wolf Optimization for Mathematical and Electrical Benchmark Problems," Energies, MDPI, vol. 15(15), pages 1-29, August.
    11. Ahmadi, Abdollah & Charwand, Mansour & Siano, Pierluigi & Nezhad, Ali Esmaeel & Sarno, Debora & Gitizadeh, Mohsen & Raeisi, Fatima, 2016. "A novel two-stage stochastic programming model for uncertainty characterization in short-term optimal strategy for a distribution company," Energy, Elsevier, vol. 117(P1), pages 1-9.
    12. Dong Zhang & GM Shafiullah & Choton Kanti Das & Kok Wai Wong, 2023. "Optimal Allocation of Battery Energy Storage Systems to Enhance System Performance and Reliability in Unbalanced Distribution Networks," Energies, MDPI, vol. 16(20), pages 1-35, October.
    13. Mahesh Kumar & Amir Mahmood Soomro & Waqar Uddin & Laveet Kumar, 2022. "Optimal Multi-Objective Placement and Sizing of Distributed Generation in Distribution System: A Comprehensive Review," Energies, MDPI, vol. 15(21), pages 1-48, October.
    14. Panda, Mitali & Nayak, Yogesh Kumar, 2022. "Impact analysis of renewable energy Distributed Generation in deregulated electricity markets: A Context of Transmission Congestion Problem," Energy, Elsevier, vol. 254(PC).
    15. Chih-Hong Lin, 2020. "Permanent-Magnet Synchronous Motor Drive System Using Backstepping Control with Three Adaptive Rules and Revised Recurring Sieved Pollaczek Polynomials Neural Network with Reformed Grey Wolf Optimizat," Energies, MDPI, vol. 13(22), pages 1-33, November.
    16. Der-Fa Chen & Yi-Cheng Shih & Shih-Cheng Li & Chin-Tung Chen & Jung-Chu Ting, 2020. "Permanent-Magnet SLM Drive System Using AMRRSPNNB Control System with DGWO," Energies, MDPI, vol. 13(11), pages 1-25, June.
    17. Mirna Fouad Abd El-salam & Eman Beshr & Magdy B. Eteiba, 2018. "A New Hybrid Technique for Minimizing Power Losses in a Distribution System by Optimal Sizing and Siting of Distributed Generators with Network Reconfiguration," Energies, MDPI, vol. 11(12), pages 1-26, November.
    18. Saeed Behzadpoor & Iraj Faraji Davoudkhani & Almoataz Youssef Abdelaziz & Zong Woo Geem & Junhee Hong, 2022. "Power System Stability Enhancement Using Robust FACTS-Based Stabilizer Designed by a Hybrid Optimization Algorithm," Energies, MDPI, vol. 15(22), pages 1-30, November.
    19. Sultana, U. & Khairuddin, Azhar B. & Sultana, Beenish & Rasheed, Nadia & Qazi, Sajid Hussain & Malik, Nimra Riaz, 2018. "Placement and sizing of multiple distributed generation and battery swapping stations using grasshopper optimizer algorithm," Energy, Elsevier, vol. 165(PA), pages 408-421.
    20. Soheil Younesi & Bahman Ahmadi & Oguzhan Ceylan & Aydogan Ozdemir, 2022. "Optimum Parallel Processing Schemes to Improve the Computation Speed for Renewable Energy Allocation and Sizing Problems," Energies, MDPI, vol. 15(24), pages 1-18, December.
    21. Der-Fa Chen & Yi-Cheng Shih & Shih-Cheng Li & Chin-Tung Chen & Jung-Chu Ting, 2020. "Mixed Modified Recurring Rogers-Szego Polynomials Neural Network Control with Mended Grey Wolf Optimization Applied in SIM Expelling System," Mathematics, MDPI, vol. 8(5), pages 1-28, May.
    22. Ahmed M. Nassef & Mohammad Ali Abdelkareem & Hussein M. Maghrabie & Ahmad Baroutaji, 2023. "Review of Metaheuristic Optimization Algorithms for Power Systems Problems," Sustainability, MDPI, vol. 15(12), pages 1-27, June.
    23. Rastgou, Abdollah & Moshtagh, Jamal & Bahramara, Salah, 2018. "Improved harmony search algorithm for electrical distribution network expansion planning in the presence of distributed generators," Energy, Elsevier, vol. 151(C), pages 178-202.
    24. Moradijoz, M. & Moghaddam, M. Parsa & Haghifam, M.R., 2018. "A flexible active distribution system expansion planning model: A risk-based approach," Energy, Elsevier, vol. 145(C), pages 442-457.

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