A hybrid optimization approach for distribution capacitor allocation considering varying load conditions

This work presents a new algorithm based on a combination of fuzzy (FUZ), Forward Update (FWD), and Genetic Algorithm (GA) approaches for capacitor allocation in distribution feeders. The problem formulation considers three distinct objectives related to total cost of energy loss and total cost of capacitors including the purchase and installation costs and one term related to total cost of produced power under peak load condition. The novel formulation is a multi-objective and non-differentiable optimization problem. The proposed methodology of this article uses an iterative optimization technique based on Forward Update approach which is embedded in a Genetic Algorithm framework. The fuzzy reasoning supported by the fuzzy set theory is used for sitting of capacitors and the GA is employed for finding the optimum shape of membership functions. The proposed method has been implemented in a software package and its effectiveness has been verified through a 9-bus radial distribution feeder along with a 34-bus radial distribution feeder for the sake of conclusions supports. A comparison has been done among the proposed method of this paper and similar methods in other research works that shows the effectiveness of the proposed method of this paper for solving optimum capacitor planning problem.