Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/12464
Title: Optimum design of passive power filter (PPF) at the output of 5-level CHB-MLI using genetic algorithm (GA)
Authors: Alamri, Basem 
Marouchos, Christos 
Darwish, Mohamed 
Keywords: Cascaded H-Bridge Multilevel Inverter (CHB-MLI);Genetic Algorithm (GA);Harmonics;Passive Power Filters (PPF)
Category: Electrical Engineering - Electronic Engineering - Information Engineering
Field: Engineering and Technology
Issue Date: Dec-2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: 52nd International Universities Power Engineering Conference, 2017, Crete, Greece, 28-31 August
Conference: International Universities Power Engineering Conference 
Abstract: While harmonics have adverse effects on both power utilities and customers, harmonic filtering is considered the most widely applied method among different harmonic-mitigation techniques. Passive power filters (PPFs) are currently more economical and commonly applied than active power filters (APFs). The problem of passive power filter (PPF) design is considered to be a combinatorial optimisation problem that can be solved by applying artificial intelligence. For PPF design, heuristic methods are powerful optimisation techniques and have many advantages such as: no requirement for detailed information about the power system and ability to achieve optimum PPF design compared to the conventional method. In addition, the cost of PPF implementation can be added to the optimisation objective, which is not considered in conventional design. The Authors of this paper propose an optimisation model based on genetic algorithm (GA) to design a composite PPF. As a case study, the model is applied to find the optimum filter design at the output of 5-level cascaded H-bridge multilevel invert (CHB-MLI). MATLAB-SIMULINK is used for the modelling and simulation.
URI: http://ktisis.cut.ac.cy/handle/10488/12464
ISBN: 978-1-5386-2344-2
DOI: 10.1109/UPEC.2017.8231980
Rights: © 2017 IEEE.
Type: Conference Papers
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

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