The Optimal Placement of Capacitor in Order to Reduce Losses and the Profile of Distribution Network Voltage with GA, SA
Most of the losses in a power system relate to
the distribution sector which always has been considered.
From the important factors which contribute to increase losses
in the distribution system is the existence of radioactive flows.
The most common way to compensate the radioactive power
in the system is the power to use parallel capacitors. In
addition to reducing the losses, the advantages of capacitor
placement are the reduction of the losses in the release peak of
network capacity and improving the voltage profile. The point
which should be considered in capacitor placement is the
optimal placement and specification of the amount of the
capacitor in order to maximize the advantages of capacitor
placement.
In this paper, a new technique has been offered for the
placement and the specification of the amount of the constant
capacitors in the radius distribution network on the basis of
Genetic Algorithm (GA). The existing optimal methods for
capacitor placement are mostly including those which reduce
the losses and voltage profile simultaneously. But the
retaliation cost and load changes have not been considered as
influential UN the target function .In this article, a holistic
approach has been considered for the optimal response to this
problem which includes all the parameters in the distribution
network: The price of the phase voltage and load changes. So,
a vast inquiry is required for all the possible responses. So, in
this article, we use Genetic Algorithm (GA) as the most
powerful method for optimal inquiry.
[1] Capacitor Subcommittee of the IEEE Transmission and Distribution
Committee, Bibliography on power capacitors 1975 - 1980, IEEE Trans.
Power Apparatus and Systems, vol. 102 , no. 7, pp. 2331-2334,
July1983.
[2] Ng H.N., Salama M.MA., and Chikhani A.Y., Classification of
Capacitor Allocation Techniques, IEEE Trans. Power Delivery, Vol. 15,
No.1, 2000.
[3] IEEE VAR Management Working Group of the IEEE System Control
Subcommittee, Bibliography on reactive power and voltage control,
IEEE Trans. Power Systems, vol.2, no. 2, pp. 361-370, May 1997.
[4] N.M. Neagle and D.R. Samson, Loss reduction from capacitors on
printary feeders. AIEE Trans., vol.75, pp. 959, Oct. in - stalled 1956.
[5] Optimal capacitor placement in radial distribution networks, IEEE Trans.
Power system, Vol.16, No.4, November 2001.
[6] A. Dwyer, The use of shunt capacitors applied for line loss savings, in
Proc 1992 CEA Conference, Apr. 1992.
[7] M.Chis , M.M. A. Salams , and Jayaram , Capacitor placement in
distribution systems using heuristic search strategies, IEE Proceedings
Generation, Transmission and Distribution, vol. 144, no.2, pp. 225-230,
May 1997.
[8] K.N. Miu, H.D. Chiang, and G. Darling, Capacitor placement , and
control in large scale distribution system by a GA - based re - placement
two - stage algorithm, IEEE Trans. Power System, vol. 12, no.3, pp.
1160 - 1166, Aug.1997.
[1] Capacitor Subcommittee of the IEEE Transmission and Distribution
Committee, Bibliography on power capacitors 1975 - 1980, IEEE Trans.
Power Apparatus and Systems, vol. 102 , no. 7, pp. 2331-2334,
July1983.
[2] Ng H.N., Salama M.MA., and Chikhani A.Y., Classification of
Capacitor Allocation Techniques, IEEE Trans. Power Delivery, Vol. 15,
No.1, 2000.
[3] IEEE VAR Management Working Group of the IEEE System Control
Subcommittee, Bibliography on reactive power and voltage control,
IEEE Trans. Power Systems, vol.2, no. 2, pp. 361-370, May 1997.
[4] N.M. Neagle and D.R. Samson, Loss reduction from capacitors on
printary feeders. AIEE Trans., vol.75, pp. 959, Oct. in - stalled 1956.
[5] Optimal capacitor placement in radial distribution networks, IEEE Trans.
Power system, Vol.16, No.4, November 2001.
[6] A. Dwyer, The use of shunt capacitors applied for line loss savings, in
Proc 1992 CEA Conference, Apr. 1992.
[7] M.Chis , M.M. A. Salams , and Jayaram , Capacitor placement in
distribution systems using heuristic search strategies, IEE Proceedings
Generation, Transmission and Distribution, vol. 144, no.2, pp. 225-230,
May 1997.
[8] K.N. Miu, H.D. Chiang, and G. Darling, Capacitor placement , and
control in large scale distribution system by a GA - based re - placement
two - stage algorithm, IEEE Trans. Power System, vol. 12, no.3, pp.
1160 - 1166, Aug.1997.
@article{"International Journal of Electrical, Electronic and Communication Sciences:60725", author = "Limouzade E. and Joorabian M.", title = "The Optimal Placement of Capacitor in Order to Reduce Losses and the Profile of Distribution Network Voltage with GA, SA", abstract = "Most of the losses in a power system relate to
the distribution sector which always has been considered.
From the important factors which contribute to increase losses
in the distribution system is the existence of radioactive flows.
The most common way to compensate the radioactive power
in the system is the power to use parallel capacitors. In
addition to reducing the losses, the advantages of capacitor
placement are the reduction of the losses in the release peak of
network capacity and improving the voltage profile. The point
which should be considered in capacitor placement is the
optimal placement and specification of the amount of the
capacitor in order to maximize the advantages of capacitor
placement.
In this paper, a new technique has been offered for the
placement and the specification of the amount of the constant
capacitors in the radius distribution network on the basis of
Genetic Algorithm (GA). The existing optimal methods for
capacitor placement are mostly including those which reduce
the losses and voltage profile simultaneously. But the
retaliation cost and load changes have not been considered as
influential UN the target function .In this article, a holistic
approach has been considered for the optimal response to this
problem which includes all the parameters in the distribution
network: The price of the phase voltage and load changes. So,
a vast inquiry is required for all the possible responses. So, in
this article, we use Genetic Algorithm (GA) as the most
powerful method for optimal inquiry.", keywords = "Genetic Algorithm (GA), capacitor placement,voltage profile, network losses, Simulating Annealing (SA),distribution network.", volume = "5", number = "2", pages = "205-6", }