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A practical eco-environmental distribution network planning model including fuel cells and non-renewable distributed energy resources

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  • Soroudi, Alireza
  • Ehsan, Mehdi
  • Zareipour, Hamidreza

Abstract

This paper presents a long-term dynamic multi-objective planning model for distribution network expansion along with distributed energy options. The proposed model optimizes two objectives, namely costs and emissions and determines the optimal schemes of sizing, placement and specially the dynamics (i.e., timing) of investments on distributed generation units and network reinforcements over the planning period. An efficient two-stage heuristic method is proposed to solve the formulated planning problem. The effectiveness of the proposed model is demonstrated by applying it to a distribution network and comparing the simulation results with other methods and models.

Suggested Citation

  • Soroudi, Alireza & Ehsan, Mehdi & Zareipour, Hamidreza, 2011. "A practical eco-environmental distribution network planning model including fuel cells and non-renewable distributed energy resources," Renewable Energy, Elsevier, vol. 36(1), pages 179-188.
  • Handle: RePEc:eee:renene:v:36:y:2011:i:1:p:179-188
    DOI: 10.1016/j.renene.2010.06.019
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    References listed on IDEAS

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    Cited by:

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    9. Ahmadian, Ali & Sedghi, Mahdi & Fgaier, Hedia & Mohammadi-ivatloo, Behnam & Golkar, Masoud Aliakbar & Elkamel, Ali, 2019. "PEVs data mining based on factor analysis method for energy storage and DG planning in active distribution network: Introducing S2S effect," Energy, Elsevier, vol. 175(C), pages 265-277.
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    12. Mallikarjun, Sreekanth & Lewis, Herbert F., 2014. "Energy technology allocation for distributed energy resources: A strategic technology-policy framework," Energy, Elsevier, vol. 72(C), pages 783-799.
    13. Valdés, R. & Lucio, J.H. & Rodríguez, L.R., 2013. "Operational simulation of wind power plants for electrolytic hydrogen production connected to a distributed electricity generation grid," Renewable Energy, Elsevier, vol. 53(C), pages 249-257.
    14. Singh, Bindeshwar & Pal, Charitra & Mukherjee, V. & Tiwari, Prabhakar & Yadav, Manish Kumar, 2017. "Distributed generation planning from power system performances viewpoints: A taxonomical survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1472-1492.
    15. Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Narimani, Mohammad Rasoul, 2012. "An efficient scenario-based stochastic programming framework for multi-objective optimal micro-grid operation," Applied Energy, Elsevier, vol. 99(C), pages 455-470.
    16. Canizes, Bruno & Soares, João & Lezama, Fernando & Silva, Cátia & Vale, Zita & Corchado, Juan M., 2019. "Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generation," Renewable Energy, Elsevier, vol. 138(C), pages 937-954.
    17. 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.
    18. Niknam, Taher & Meymand, Hamed Zeinoddini & Mojarrad, Hasan Doagou, 2011. "A practical multi-objective PSO algorithm for optimal operation management of distribution network with regard to fuel cell power plants," Renewable Energy, Elsevier, vol. 36(5), pages 1529-1544.
    19. Wakui, Tetsuya & Hashiguchi, Moe & Sawada, Kento & Yokoyama, Ryohei, 2019. "Two-stage design optimization based on artificial immune system and mixed-integer linear programming for energy supply networks," Energy, Elsevier, vol. 170(C), pages 1228-1248.
    20. Rabiee, Abdorreza & Sadeghi, Mohammad & Aghaeic, Jamshid & Heidari, Alireza, 2016. "Optimal operation of microgrids through simultaneous scheduling of electrical vehicles and responsive loads considering wind and PV units uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 721-739.
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    22. 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.

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