Presenting a fuzzy multi-objective approach for dynamic reconfiguration of the distribution network in the presence of distributed generation units and energy storage systems

Document Type : Power Article

Authors

1 Department of Electrical and Computer Engineering, Hakim Sabzevari University, Sabzevar

2 Hakim Sabzevari University

3 Electrical and Computer Engineering Faculty, Hakim Sabzevari univerisity, Sabzevar, Iran.

Abstract

The penetration of distributed generation resources and energy storage units in distribution networks is increasing and the effect of these units can affect the efficiency of the network. In this study, the problem of distribution network reconfiguration in the presence of distributed generation units and energy storage systems is modeled in a dynamic framework. Conventional distribution network reconfiguration studies usually pay more attention to the loss objective function, but the importance of newer objective functions such as network reliability and security has been less explored. In this paper, the objective functions of energy not supplied as a reliability index, voltage stability index as a function of network security along with operational cost for the dynamic distribution network reconfiguration problem are introduced. The problem of distribution network reconfiguration is a nonlinear and non-convex problem, considering the effect of distributed generation and energy storage units further complicates the optimization problem. Hence, the fuzzy logic-based student psychology optimization algorithm for the single-objective and multi-objective optimization problem of the dynamic distribution network reconfiguration problem is proposed. The accuracy of the proposed method is evaluated on two test systems of 33 bass and 119 bass test and its superiority is shown by comparison with other evolutionary methods.

Keywords

Main Subjects

References

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Journal of Modeling in Engineering
Volume 20, Issue 71
November 2022
Pages 175-188

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History

  • Receive Date: 19 February 2022
  • Revise Date: 10 July 2022
  • Accept Date: 21 August 2022

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