TY - JOUR
T1 - Particle swarm optimisation for reactive power compensation on oman 6 bus electrical grid
AU - Al Mamari, Adnan Saif
AU - Toha, Siti Fauziah
AU - Ahmad, Salmiah
AU - Al Mamari, Ali Salim
N1 - Funding Information:
The author would like to thank financial support from the international Islamic University Malaysia under research grant IRF19-026-002: Highly efficient Lithium-ion battery recycling with capacity-sorted optimization for secondary energy storage system.
Publisher Copyright:
© 2021, Institute of Advanced Engineering and Science. All rights reserved.
PY - 2021/9
Y1 - 2021/9
N2 - The consistent problem with operators and planners for power systems has been related to minimizing transmission losses. An important role is played by reactive power by keeping voltage stability and reliability in the system in order to support the transfer of real power. The optimal reactive power dispatch is associated with the problem of non-linear optimization along with many constraints. In this paper, a study is highlighted for an algorithm that optimizes reactive power with the help of particle swarm algorithm and compare the result with Newton-Raphson method. Reduction of system active power loss is the goal of the function in the projected algorithm. Here, the control variables identified are transformer tap positions, generator bus voltages, and shunt capacitor banks with switch. This projected algorithm is performed on Oman 6 bus electrical grid as oman electricity transmission company has an instability voltage issue in chosen 6 bus.
AB - The consistent problem with operators and planners for power systems has been related to minimizing transmission losses. An important role is played by reactive power by keeping voltage stability and reliability in the system in order to support the transfer of real power. The optimal reactive power dispatch is associated with the problem of non-linear optimization along with many constraints. In this paper, a study is highlighted for an algorithm that optimizes reactive power with the help of particle swarm algorithm and compare the result with Newton-Raphson method. Reduction of system active power loss is the goal of the function in the projected algorithm. Here, the control variables identified are transformer tap positions, generator bus voltages, and shunt capacitor banks with switch. This projected algorithm is performed on Oman 6 bus electrical grid as oman electricity transmission company has an instability voltage issue in chosen 6 bus.
KW - Load flow algorithm
KW - Newton-Raphson
KW - Particle swarm optimization
KW - Reactive power compensation
KW - Voltage stability
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U2 - 10.11591/ijpeds.v12.i3.pp1912-1918
DO - 10.11591/ijpeds.v12.i3.pp1912-1918
M3 - Article
AN - SCOPUS:85113673722
SN - 2088-8694
VL - 12
SP - 1912
EP - 1918
JO - International Journal of Power Electronics and Drive Systems
JF - International Journal of Power Electronics and Drive Systems
IS - 3
ER -