Original scientific paper

https://doi.org/10.17559/TV-20200813105532

Power Loss Minimization for Distribution Networks with Load Tap Changing Using Genetic Algorithm and Environmental Impact Analysis

Talha Enes Gümüş* orcid.org/0000-0002-6716-6414 ; Institution Electrical and Electronics Eng. Department, Eng. Faculty, Sakarya University, Turkey
Ceyda Aksoy Tirmikçi ; Institution Electrical and Electronics Eng. Department, Eng. Faculty, Sakarya University, Turkey
Cenk Yavuz orcid.org/0000-0002-4325-2852 ; Institution Electrical and Electronics Eng. Department, Eng. Faculty, Sakarya University, Turkey
Mehmet Ali Yalçin orcid.org/0000-0003-3846-177X ; Institution Electrical and Electronics Eng. Department, Eng. Faculty, Sakarya University, Turkey
Mustafa Turan orcid.org/0000-0002-9184-1061 ; Institution Electrical and Electronics Eng. Department, Eng. Faculty, Sakarya University, Turkey

Abstract

This paper presents an investigation of the IEEE 34 bus test system benefits with deployment of distribution static compensator (DSTATCOM) and distributed generation (DG) in the aspect of power loss minimization, bus voltage stability and greenhouse gas emission mitigation. Power loss minimization is carried out by adjusting tap changer positions of the load tap changing transformer with one of the well-known metaheuristic algorithms, Genetic Algorithm (GA). To check the voltage stability of the system after minimization, bus voltage profile index is developed. Similarly, environmental profile is evaluated by three different indices. The behaviour of the system is analysed for four different cases as follows. In Case 1, voltage and reactive power control is provided by capacitor banks. In Case 2, capacitor banks are replaced with DSTATCOM. In Case 3 and Case 4, Case 1 and Case 2 are reinvestigated in the presence of additional DG. All cases are evaluated with both traditional Newton- Raphson optimization algorithm and evolutionary-based GA optimization algorithm. The results indicate that GA optimization provides more energy savings than traditional optimization in all cases with bus voltage index within the allowed range. Besides voltage profile of the system in all cases with two algorithms supports the fact that evolutionary-based metaheuristics offer the best choices for a non-linear optimization problem in comparison with the traditional optimization methods. The overall results reveal that Case 4, test system with DSTATCOM and DG, is the best case which provides minimum power losses and a significant amount of emission savings with greenhouse payback time (GPBT) of 0.458 years.

Keywords

bus voltage stability; distributed generation; distribution static compensator; emission mitigation; Genetic Algorithm; Load tap changing; power loss minimization

Hrčak ID:

264051

URI

https://hrcak.srce.hr/264051

Publication date:

7.11.2021.

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