The fuzzy set theory has been proposed in 1965 by Lofti A.
Zadeh from the University of Berkeley 43.
A number of fuzzy based methods have been reported. These methods, however, do
not always find the best possible solutions. But they generally can find an
acceptable suboptimal solution using less computational burden time.
H. Chin and W. Lin 44
have investigated the application of fuzzy set theory in finding suitable buses
for installing capacitor banks. C. Su and C. Tsai 45
present a fuzzy-reasoning method to optimum
shunt capacitor placement and sizing for the radial distribution systems. In
this method, a combinatorial optimization problem with multiple objectives
where capacitor allocation is applied to correct voltage and reduce power
loss for a given load pattern. S.
Mekhamer et al. 46
present a new algorithm determines the exact optimal solution for capacitor
allocation in radial distribution feeders. Results of previous work using fuzzy
and heuristic strategies on this feeder are compared with the exact reference
solution. Different fuzzy decision-making forms are applied to the fuzzy
modeling problem. A recommendation is made for the most efficient way to get a
solution equal or very close to the optimal.
S. Bhattacharya and S. Goswami
have investigated the effectiveness of the fuzzy-based methods in solving the
capacitor placement problem, identify their limitations and also suggest
improvement technique in order to have a superior quality of solutions in 44-46. S. Kannan et al. 48 present a fuzzy logic control
that uses some of the computational procedures to find out the total power loss
and voltage level in the radial distribution system and then coupling of a fuzzy
expert system to find out the candidate sensitivity index for optimal capacitor
placement. A. Siddiqui and F. Rahman 49
have applied the fuzzy sets theory to determine the optimal number, locations
and ratings of capacitors to place in a distribution system. S. Isac, K. Kumar
and P. Kumar 50
have developed an algorithm based on fuzzy logic for capacitor placement in the
radial distribution system to minimize the line loss. The fuzzy expert system
determines the candidate nodes for capacitor placement by striking a compromise
between the possible loss reduction from capacitor installation and voltage
Baysal and I. Altas 50
have developed A fuzzy reasoning based decision maker in order to
determine the optimal capacitor location and sizing in radial distribution
systems for the purpose of minimizing the power loss and capacitor cost with
voltage limit constraints through a fuzzy expert system that selects suitable
candidate buses for capacitor locations in distribution feeder and a fuzzy
optimization system that estimates the optimal capacitor sizing to obtain
maximum savings at the optimal buses determined. V. Shetty and S. Ankaliki 51
present a fuzzy technique based decision maker in order to determine suitable
candidate nodes for optimal capacitor placement and sizing in radial
distribution systems for the purpose of reducing power loss and improving
voltage profile in order to achieve reliability of the entire system.