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Information Journal Paper

Title

IMPROVING THE PERFORMANCE OF UPQC UNDER UNBALANCED AND DISTORTIONAL LOAD CONDITIONS: A NEW CONTROL METHOD

Pages

  225-234

Abstract

 This paper presents a new control method for a three-phase four-wire Unified POWER QUALITY Conditioner (UPQC) to deal with the problems of POWER QUALITY under distortional and unbalanced load conditions. The proposed control approach is the combination of instantaneous power theory and Synchronous Reference Frame (SRF) theory which is optimized by using a self-tuning filter (STF) and without using load or filter currents measurement. In this approach, load and source voltages are used to generate the reference voltages of series active power filter (APF) and source currents are used to generate the reference currents of shunt APF. Therefore, the number of current measurements is reduced and system performance is improved. The performance of proposed control system is tested for cases of power factor correction, reducing source neutral current, load balancing and current and voltage harmonics in a three-phase four-wire system for distortional and unbalanced loads. Results obtained through MATLAB/SIMULINK software show the effectiveness of proposed control technique in comparison to the conventional p-q method.

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  • Cite

    APA: Copy

    GHANIZADEH, R., & EBADIAN, M.. (2015). IMPROVING THE PERFORMANCE OF UPQC UNDER UNBALANCED AND DISTORTIONAL LOAD CONDITIONS: A NEW CONTROL METHOD. JOURNAL OF ARTIFICIAL INTELLIGENCE AND DATA MINING, 3(2), 225-234. SID. https://sid.ir/paper/255371/en

    Vancouver: Copy

    GHANIZADEH R., EBADIAN M.. IMPROVING THE PERFORMANCE OF UPQC UNDER UNBALANCED AND DISTORTIONAL LOAD CONDITIONS: A NEW CONTROL METHOD. JOURNAL OF ARTIFICIAL INTELLIGENCE AND DATA MINING[Internet]. 2015;3(2):225-234. Available from: https://sid.ir/paper/255371/en

    IEEE: Copy

    R. GHANIZADEH, and M. EBADIAN, “IMPROVING THE PERFORMANCE OF UPQC UNDER UNBALANCED AND DISTORTIONAL LOAD CONDITIONS: A NEW CONTROL METHOD,” JOURNAL OF ARTIFICIAL INTELLIGENCE AND DATA MINING, vol. 3, no. 2, pp. 225–234, 2015, [Online]. Available: https://sid.ir/paper/255371/en

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