Optimal Allocation of DERs Considering Existing Distribution Infrastructure Using Mountain Gazelle Optimizer: Practical Case Study

Chintan Patel; Tarun Tailor

Authors

Chintan Patel Nirma University, India
Tarun Tailor Nirma University, India

Keywords:

distributed energy resources, on-load tap changing transformer, MGO algorithm, distribution Network

Abstract

The inclusion of distributed energy resources (DERs) in the power distribution network (DN) encountered rapid growth across the countries due to technological and environmental advantages. Moreover, this inclusion not only enhances diversity in resources but can improve the quality of service to users as well. However, the unplanned integration of DERs and their deployment in non-optimal locations can adversely affect the performance of DN. Hence, optimal positioning and sizing of DERs is very important aspects. Further, few studies have focused on DER and shunt capacitors (SCs) allocation in combination with the presence or absence of OLTC infrastructure. Therefore, in this paper, the recently developed Mountain Gazelle Optimizer (MGO) algorithm suitable for solving complex problem and addressing global optimization issues, is applied for optimal positioning of the DERs along with existent distribution infrastructure. In this work, considered objective is decreasing the cost of annual energy loss (CAEL). In order to showcase the usefulness of MGO algorithm in solving DER allocation problem this has been implemented on IEEE 33 bus and Indian 108 bus radial DN (real-life practical DN). The comparative analysis between MGO and other applied methods in the literature on same problem has also been presented. The obtained results indicate that simultaneous consideration of DERs, SCs and existing OLTC not only offers improved utilization of existing DN infrastructure but also minimizes the overall cost. The considerable improvement in results pertaining to CAEL for different scenarios, for an example around 10.6 % better compared to best reported results (IEEE-33 bus system, scenario-5), confirm the suitability of MGO algorithm.

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