Optimal capacitor placement in radial distribution systems using teaching learning based optimization

This paper presents a new genetic algorithm (GA)-based approach for the simultaneous power quality improvement and optimal placement and sizing of fixed capacitor banks in radial distribution networks in the presence of voltage and current harmonics. The objective function includes the cost of power losses, energy losses and that of the capacitor banks. Constraints include voltage limits, number/size and locations of installed capacitors (at each bus and the entire feeder) and the power quality limits of standard IEEE-519. Candidate buses for capacitor placement are selected based on an initial generation of chromosomes. Using a proposed fitness function, a suitable combination of objective and constraints is defined as a criterion to select (among the candidates) the most suitable buses for capacitor placement. A genetic algorithm computes improved generations of chromosomes and candidate buses until the solution is obtained. Simulation results for two IEEE distorted networks are presented and solutions of the genetic algorithm are compared with those of the maximum-sensitivities-selection (MSS), the maximum sensitivities selection-local variations (MSS-LV), and the fuzzy set algorithms. The main contribution of this paper is the computation of the near global solution, with weak dependency on initial conditions.

Optimal placement, replacement and sizing of capacitor Banks in distorted distribution networks by genetic algorithms

Optimal capacitor placement in radial distribution system using Gravitational Search Algorithm

This paper presents a fuzzy-based approach for optimal placement and sizing of fixed capacitor banks in radial distribution networks in the presence of voltage and current harmonics. The objective function includes the cost of power losses, energy losses, and capacitor banks. Constraints include voltage limits, number/size and locations of installed capacitors, and the power quality limits of IEEE-519 standard. Candidate buses for capacitor placement are selected using the sensitivities of constraints and the objective function with respect to reactive power injection at each bus. Using fuzzy set theory, a suitable combination of objective function and constraints is generated as a criterion to select the most suitable bus for capacitor placement. The /spl alpha/-cut process is applied at each iteration to guarantee simultaneous improvements of objective function and satisfying given constraints. Simulation results for the 18 bus IEEE distorted network show the advantages of the proposed method as compared to the maximum sensitivities selection algorithm.

Fuzzy approach for optimal placement and sizing of capacitor banks in the presence of harmonics

Shunt capacitors are commonly used in distribution system for reactive power compensation. Different analytical, numerical programming, heuristic and artificial intelligent based techniques have been proposed in the literature for optimum shunt capacitor bank (SCB) placement. This paper will present a very detailed overview of optimum SCB placement techniques. Six different approaches of optimum SCB placement based on minimization of power losses, weakest voltage bus approach and maximization of system loadability will be applied on four different radial distribution test systems. The results will be compared on the basis of power loss reduction, voltage profile improvement, system loadability maximization and the line limit constraint.

Optimum shunt capacitor placement in distribution system A review and comparative study

An approximate method for capacitor placement in distribution system using heuristics and greedy search technique

Genetic algorithm has been used to solve the problem of capacitor placement in power distribution systems. A new composition of the genetic string has been proposed for the coding of the capacitor placement problem. The proposed genetic string represents both the optimum location and the size of the capacitor. A number of modifications have also been proposed to improve the performance of the simple genetic algorithm in solving the capacitor placement problem. Test results have been presented in support of the superiority of the proposed modifications.

Solving Capacitor Placement Problems in Distribution Systems Using Genetic Algorithms

The problem in optimal placement of capacitors is to decide on the number, locations, and sizes of capacitors to be placed at different buses of the system such that the reduction of energy losses become maximum considering the load variation and the cost of capacitors. A solution technique using combined simulated annealing and genetic algorithm is presented in this paper. The results for two test networks having 9 and 69 buses are also reported by using only GA and combined GA-SA method to prove the justification of combination.

S. K. Basu

Papers

An approximate method for capacitor placement in distribution system using heuristics and greedy search technique

Solving Capacitor Placement Problems in Distribution Systems Using Genetic Algorithms

Energy loss reduction in distribution system by capacitor placement through combined GA-SA technique