1. Design of fractional evolutionary processing for reactive power planning with FACTS devices
- Author
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Rahimdad Khan, Muhammad Asif Zahoor Raja, Rizwan Akhtar, J. A. Tenreiro Machado, Farman Ullah, Yasir Muhammad, and Repositório Científico do Instituto Politécnico do Porto
- Subjects
Static Var compensator (SVC) ,Computer science ,020209 energy ,Energy science and technology ,Science ,Static VAR compensator ,02 engineering and technology ,Article ,law.invention ,Compensation (engineering) ,Electric power system ,Engineering ,Control theory ,law ,0202 electrical engineering, electronic engineering, information engineering ,Maximum power transfer theorem ,FACTS ,Power-flow study ,Transformer ,Particle Swarm Optimization (FO-DPSO) ,Power system ,Multidisciplinary ,Thyristor ,Voltage collapse ,AC power ,Medicine ,020201 artificial intelligence & image processing ,Reactive power dispatch ,Alternating current ,Shunt (electrical) ,Voltage - 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.
- Published
- 2021