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Multistage distribution system expansion planning considering distributed generation using hybrid evolutionary algorithms

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  • Gitizadeh, Mohsen
  • Vahed, Ali Azizi
  • Aghaei, Jamshid

Abstract

The main goal of this paper is to present a Multistage Distribution network Expansion Planning (MDEP) problem in the presence of Distributed Generations (DGs) in a multi-objective optimization framework. The proposed model simultaneously optimizes two objectives: minimization of investment and operation costs and maximization of reliability index. The proposed optimization model is solved subject to AC power flow constraints to obtain the optimal configuration of feeders (adding and removing lines) including the optimal size of branch conductor, replacement of conductor for reserve feeders, and generated power of DGs. To include reliability concerns in the proposed MDEP problem, an analytical approach on the basis of graph theory is implemented to evaluate the Energy-Not-Supplied (ENS) index as an extra objective function. Also, in this paper, in order to identify Pareto optimal solutions of the multi-objective MDEP problem, a hybrid Particle Swarm Optimization (PSO) and Shuffled Frog Leaping (SFL) algorithm is implemented. A synthetic distribution test system is considered for the MDEP problem in a 4-year planning horizon. The results of the hybrid PSO and SFL algorithm are compared with those of the classical PSO and SFL methods.

Suggested Citation

  • Gitizadeh, Mohsen & Vahed, Ali Azizi & Aghaei, Jamshid, 2013. "Multistage distribution system expansion planning considering distributed generation using hybrid evolutionary algorithms," Applied Energy, Elsevier, vol. 101(C), pages 655-666.
    • Handle: RePEc:eee:appene:v:101:y:2013:i:c:p:655-666
    DOI: 10.1016/j.apenergy.2012.07.010
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    References listed on IDEAS

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    1. Soroudi, Alireza & Ehsan, Mehdi, 2010. "A distribution network expansion planning model considering distributed generation options and techo-economical issues," Energy, Elsevier, vol. 35(8), pages 3364-3374.
    2. Niknam, Taher & Taheri, Seyed Iman & Aghaei, Jamshid & Tabatabaei, Sajad & Nayeripour, Majid, 2011. "A modified honey bee mating optimization algorithm for multiobjective placement of renewable energy resources," Applied Energy, Elsevier, vol. 88(12), pages 4817-4830.
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    7. Bayat, A. & Bagheri, A., 2019. "Optimal active and reactive power allocation in distribution networks using a novel heuristic approach," Applied Energy, Elsevier, vol. 233, pages 71-85.
    8. Jordehi, A. Rezaee, 2015. "Optimisation of electric distribution systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1088-1100.
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    13. Ahmadigorji, Masoud & Amjady, Nima, 2015. "Optimal dynamic expansion planning of distribution systems considering non-renewable distributed generation using a new heuristic double-stage optimization solution approach," Applied Energy, Elsevier, vol. 156(C), pages 655-665.
    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. Ramdhan Halid Siregar & Yuwaldi Away & Tarmizi & Akhyar, 2023. "Minimizing Power Losses for Distributed Generation (DG) Placements by Considering Voltage Profiles on Distribution Lines for Different Loads Using Genetic Algorithm Methods," Energies, MDPI, vol. 16(14), pages 1-25, July.
    16. Shivaie, Mojtaba & Ameli, Mohammad T. & Sepasian, Mohammad S. & Weinsier, Philip D. & Vahidinasab, Vahid, 2015. "A multistage framework for reliability-based distribution expansion planning considering distributed generations by a self-adaptive global-based harmony search algorithm," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 68-81.
    17. Mandhir Kumar Verma & Vivekananda Mukherjee & Vinod Kumar Yadav & Santosh Ghosh, 2020. "Constraints for effective distribution network expansion planning: an ample review," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(3), pages 531-546, June.
    18. Lei Yang & Xiaohui Yang & Yue Wu & Xiaoping Liu, 2018. "Applied Research on Distributed Generation Optimal Allocation Based on Improved Estimation of Distribution Algorithm," Energies, MDPI, vol. 11(9), pages 1-17, September.
    19. Xie, Shiwei & Hu, Zhijian & Zhou, Daming & Li, Yan & Kong, Shunfei & Lin, Weiwei & Zheng, Yunfei, 2018. "Multi-objective active distribution networks expansion planning by scenario-based stochastic programming considering uncertain and random weight of network," Applied Energy, Elsevier, vol. 219(C), pages 207-225.
    20. Ahmadigorji, Masoud & Amjady, Nima, 2016. "A multiyear DG-incorporated framework for expansion planning of distribution networks using binary chaotic shark smell optimization algorithm," Energy, Elsevier, vol. 102(C), pages 199-215.
    21. Esmaili, Masoud & Firozjaee, Esmail Chaktan & Shayanfar, Heidar Ali, 2014. "Optimal placement of distributed generations considering voltage stability and power losses with observing voltage-related constraints," Applied Energy, Elsevier, vol. 113(C), pages 1252-1260.

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