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A multiyear DG-incorporated framework for expansion planning of distribution networks using binary chaotic shark smell optimization algorithm

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  • Ahmadigorji, Masoud
  • Amjady, Nima

Abstract

In this paper, a new model for MEPDN (multiyear expansion planning of distribution networks) is proposed. By solving this model, the optimal expansion scheme of primary (i.e. medium voltage) distribution network including the reinforcement pattern of primary feeders as well as location and size of DG (distributed generators) during an ascertained planning period is determined. Furthermore, the time-based feature of proposed model allows it to specify the investments/reinforcements time (i.e. year). Moreover, a minimum load shedding-based analytical approach for optimizing the network's reliability is introduced. The associated objective function of proposed model is minimizing the total investment and operation costs. To solve the formulated MEPDN model as a complex multi-dimensional optimization problem, a new evolutionary algorithm-based solution method called BCSSO (Binary Chaotic Shark Smell Optimization) is presented. The effectiveness of the proposed MEPDN model and solution approach is illustrated by applying them on two widely-used test cases including 12-bus and 33-bus distribution network and comparing the acquired results with the results of other solution methods.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:102:y:2016:i:c:p:199-215
    DOI: 10.1016/j.energy.2016.02.088
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    6. 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.
    7. 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.
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    9. Moradijoz, Mahnaz & Moradijoz, Saeed & Moghaddam, Mohsen Parsa & Haghifam, Mahmoud-Reza, 2020. "Flexibility enhancement in active distribution networks through a risk-based optimal placement of sectionalizing switches," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    10. 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.
    11. Huang, Yalin & Söder, Lennart, 2017. "Evaluation of economic regulation in distribution systems with distributed generation," Energy, Elsevier, vol. 126(C), pages 192-201.
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    14. dos Santos, L.L.C. & Canha, L.N. & Bernardon, D.P., 2018. "Projection of the diffusion of photovoltaic systems in residential low voltage consumers," Renewable Energy, Elsevier, vol. 116(PA), pages 384-401.

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