Optimized Network Reconfiguration with Integrated Generation Using Tangent Golden Flower Algorithm

Dhivya Swaminathan () and Arul Rajagopalan ()
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Dhivya Swaminathan: School of Electrical Engineering, Vellore Institute of Technology, Chennai 600127, Tamil Nadu, India
Arul Rajagopalan: School of Electrical Engineering, Vellore Institute of Technology, Chennai 600127, Tamil Nadu, India

Energies, 2022, vol. 15, issue 21, 1-19

Abstract: The importance of integrating distributed generation (DG) units into the distribution network (DN) recently developed. To decrease power losses (PL), this article presents a meta-heuristic population-based tangent golden flower pollination algorithm (TGFPA) as an optimization technique for selecting the ideal site for DG. Furthermore, the proposed algorithm also finds the optimal routing configuration for power flow. TGFPA requires very few tuning parameters and is comprised of a golden section and a tangent flight algorithm (TFA). Hence, it is easy to update these parameters to obtain the best values, which provide highly reliable results compared to other existing techniques. In different case studies, the TGFPA’s performance was assessed on four test bus systems: IEEE 33-bus, IEEE 69-bus, IEEE 119-bus, and Indian-52 bus. According to simulation results, TGFPA computes the optimal reconfigured DN embedded along with DG, achieving the goal of minimal power loss.

Keywords: distributed generation; optimization; power loss reduction; tangent golden flower pollination algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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