NDLI: On comparing the performance of Genetic Algorithm optimized PI and fractional order PI controller for power quality enhancement

Content Provider	IEEE Xplore Digital Library
Author	Srivastava, S. Manaktala, A. Sadhwani, K. Gupta, M.
Copyright Year	2011
Description	Author affiliation: Department of Instrumentation & Control, Netaji Subhas Institute Of Technology, New Delhi, India (Srivastava, S.; Manaktala, A.; Sadhwani, K.) \|\| Department of Electrical & Electronics Engg., Maharaja Agrasen Institute Of Technology, New Delhi, India (Gupta, M.)
Abstract	This paper deals with the application of a optimization technique inspired by natural evolution, namely Genetic Algorithm (GA) for the design of Fractional order Proportional and Integral (FOPI) based DSTATCOM (Distributed Static Compensator) and ELC (Electronic Load Controller). The GA technique helps search efficiently the optimal parameters of the FOPI controller. Conventional controllers use integral order control which is less robust as compared to fractional order control. This paper is based on a novel application of fractional order controller optimized by genetic algorithm for power quality improvement using DSTATCOM and ELC in a power system. With the help of modelling carried out in a MATLAB based environment and a set of simulation results, the superiority of the designed FOPI over PI (Proportional — Integral) based DSTATCOM and ELC controllers used in power distribution system is affirmed and a comparative study in terms of overshoots and undershoots is presented.
Starting Page	1
Ending Page	6
File Size	588942
Page Count	6
File Format	PDF
e-ISBN	9781457715105
DOI	10.1109/ICPES.2011.6156674
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-22
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Power Quality (PQ) Electronic Load Controller (ELC) Distribution Static Compensator (DSTATCOM) Fractional Order Proportional Integral (FOPI) Controller Artificial neural networks Power factor correction Load management Genetic Algorithm (GA) Voltage control Optimization Frequency control Genetic algorithms
Content Type	Text
Resource Type	Article

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