Literature DB >> 33436809

Design of fractional evolutionary processing for reactive power planning with FACTS devices.

Yasir Muhammad1,2, Rizwan Akhtar3, Rahimdad Khan1, Farman Ullah4, Muhammad Asif Zahoor Raja4,5, J A Tenreiro Machado6.   

Abstract

Reactive power dispatch is a vital problem in the operation, planning and control of power system for obtaining a fixed economic load expedition. An optimal dispatch reduces the grid congestion through the minimization of the active power loss. This strategy involves adjusting the transformer tap settings, generator voltages and reactive power sources, such as flexible alternating current transmission systems (FACTS). The optimal dispatch improves the system security, voltage profile, power transfer capability and overall network efficiency. In the present work, a fractional evolutionary approach achieves the desired objectives of reactive power planning by incorporating FACTS devices. Two compensation arrangements are possible: the shunt type compensation, through Static Var compensator (SVC) and the series compensation through the Thyristor controlled series compensator (TCSC). The fractional order Darwinian Particle Swarm Optimization (FO-DPSO) is implemented on the standard IEEE 30, IEEE 57 and IEEE 118 bus test systems. The power flow analysis is used for determining the location of TCSC, while the voltage collapse proximity indication (VCPI) method identifies the location of the SVC. The superiority of the FO-DPSO is demonstrated by comparing the results with those obtained by other techniques in terms of measure of central tendency, variation indices and time complexity.

Entities:  

Year:  2021        PMID: 33436809      PMCID: PMC7804412          DOI: 10.1038/s41598-020-79838-2

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  1 in total

1.  Fractional-order Darwinian PSO-based feature selection for media-adventitia border detection in intravascular ultrasound images.

Authors:  Yuan-Yuan Wang; Wen-Xian Peng; Chen-Hui Qiu; Jun Jiang; Shun-Ren Xia
Journal:  Ultrasonics       Date:  2018-06-18       Impact factor: 2.890

  1 in total
  1 in total

1.  Artificial intelligence knacks-based stochastic paradigm to study the dynamics of plant virus propagation model with impact of seasonality and delays.

Authors:  Nabeela Anwar; Iftikhar Ahmad; Muhammad Asif Zahoor Raja; Shafaq Naz; Muhammad Shoaib; Adiqa Kausar Kiani
Journal:  Eur Phys J Plus       Date:  2022-01-20       Impact factor: 3.758

  1 in total

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