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Title: | Placement of active power line conditioner in distribution system using differential evolution [articol] |
Subjects: | Active power-line conditioner (APLC) Genetic algorithm (GA) Harmonics Particle swarm optimization (PSO) Differential evolution Distorted distribution system |
Issue Date: | 2019 |
Publisher: | Timișoara : Editura Politehnica |
Citation: | Kavitha, D.: Placement of active power line conditioner in distribution system using differential evolution. Timişoara: Editura Politehnica, 2019. |
Series/Report no.: | Journal of Electrical Engineering;Vol 19 No 5 |
Abstract: | Active Power Line Conditioners (APLCs) are considered the most efficient device for mitigation of power system harmonics. In this paper, a problem of allocation and sizing of multiple active power-line conditioners (APLCs) in distorted power distribution systems is handled with novel formulation. The utilized objective function comprises two main factors such as reduction of total harmonic distortion and the total cost of APLCs. The formulated problem is solved by four different optimization techniques GA, PSO, Hybrid GA-PSO and DE. To evaluate the competence of the proposed formulation, the IEEE 18- bus and 69 bus distorted distribution test systems are employed and investigated with various number of APLCs placement. These cases are based on the discrete and limited size for APLCs, requiring the optimization method to solve the constrained and discrete nonlinear problems. Therefore, all the evolutionary algorithms used utilize an integer optimizer. Simulation results confirmed the capability and effectiveness of the proposed formulation and DE algorithm works well in the allocation and sizing of multiple APLCs in a test power system compared with other heuristic algorithms. |
URI: | https://dspace.upt.ro/xmlui/handle/123456789/6731 |
ISSN: | 1582-4594 |
Appears in Collections: | Articole științifice/Scientific articles |
Files in This Item:
File | Description | Size | Format | |
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BUPT_ART_Kavitha_f.pdf | 3.51 MB | Adobe PDF | View/Open |
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