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Multidimensional Firefly Algorithm for Solving Day-Ahead Scheduling Optimization in Microgrid

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Abstract

In this paper, an improved metaheuristic optimization algorithm based on the firefly algorithm, called multidimensional firefly algorithm (MDFA), is presented for solving day-ahead scheduling optimization in a microgrid. The proposed algorithm takes the output of power generations among a quantity of distributed energy resources during 24 h together rather than a single hour as a firefly separately. The proposed algorithm is combined with strategy of solving equality constraint replacing the use of the penalty-function technique. It is also enhanced by using a novel method in parameters self-adaption instead of applying fixed values, resulting in avoiding tuning frequently the algorithm parameters during the process of optimization. The MDFA is utilized for optimization of energy production cost in a microgrid. The superiority of the MDFA is demonstrated by using the classic test power system proved in the previous literature. The solutions obtained by MDFA are compared with the results found by five famous optimization algorithms. The high performance of MDFA is established by the quality with the minimum total cost, the reliability of gained solutions, the speed of convergence, and the ability to satisfy various constraints.

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Acknowledgements

This work was supported by the Guangxi Special Fund for Innovation-Driven Development (AA19254034).

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Authors and Affiliations

  1. School of Electrical Engineering, Guangxi University, No.100, Daxue East Road, Nanning City, Guangxi, China

    YuDe Yang, JinLian Qiu & ZhiJun Qin

  2. Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, No.100, Daxue East Road, Nanning City, Guangxi, China

    YuDe Yang & JinLian Qiu

Authors
  1. YuDe Yang
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  2. JinLian Qiu
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  3. ZhiJun Qin
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Correspondence to JinLian Qiu.

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Appendix

Appendix

The details data of DERs, load, and results obtained by other investigated algorithms.

See Tables 3 , 4 , 5 , 6 , 7 , 8 , 9

Table 3 The details data of DERs and demand
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Table 4 The cost coefficients of DERs
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Table 5 Optimal results obtained by FA
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Table 6 Optimal results obtained by GA
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Table 7 Optimal results obtained by MGA
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Table 8 Optimal results obtained by PSOcf
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Table 9 Optimal results obtained by PSOw
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Yang, Y., Qiu, J. & Qin, Z. Multidimensional Firefly Algorithm for Solving Day-Ahead Scheduling Optimization in Microgrid. J. Electr. Eng. Technol. 16, 1755–1768 (2021). https://doi.org/10.1007/s42835-021-00707-7

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  • DOI: https://doi.org/10.1007/s42835-021-00707-7

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