A New Attempt to Optimize Optimal Power Flow Based Transmission Losses Using Genetic Algorithm

Abstract

This paper presents a new method using GADS Toolbox in MATLAB (A Genetic Algorithm Approach) to find the optimal solution of optimal power flow based transmission losses. Optimal power flow (OPF) is a key area of concern in electric industries. The basic OPF solution is obtained with objective function as production cost minimization while satisfying a set of system operating constraints. For reactive power optimization the OPF problem is formulated as minimization of system active power losses and improvement in voltage stability of the system. In this paper GA based optimal power flow solution is presented for IEEE 30-bus test power system with objective as transmission losses minimization and optimal results by GA are also compared with solution obtained by using Particle Swarm Optimization Technique.

An Ancillary Services Model for Data Centers and Power Systems

“…Equation 5 is a set of nonlinear expressions that need to converge as ( , , ) ≅ 0 [16]. We employed different optimization algorithms, such as Newton-Raphson (NR) [15], Particle Swarm Optimization (PSO) [16], Genetic Algorithm (GA) [17], Semi-Definite Programming (SDP) [19], Simulated Annealing (SA) [20], and Genitor Genetic Algorithm (GGA) [17] to solve the OPF, where the tolerance of the power injection and consumption mismatch is 10 −6 [15]. If the tolerance is below or equal to 10 −6 , the OPF solution is considered to be converged.…”

New Enhanced Artificial Bee Colony (JA-ABC5) Algorithm with Application for Reactive Power Optimization

“…RPO basically serves to determine the optimal setting of the power system network to satisfy few constraints such as the power flow equation system security and equipment operating limits [ 32 ]. This problem has been discovered by Carpentier in 1962 [ 33 ] and, since then, many have tried to solve it. Researchers and engineers have tried to solve it by developing various search strategies since this kind of problem is very essential to be solved.…”

EA Techniques for Optimal Power Flow. Parameter Tuning by Mathematical Test Functions

“…The results refer to the IEEE30 test system, as well as to two real power systems. In [7], the Matlab-integrated genetic algorithm toolbox is used to solve the OPF. The results for the IEEE30 test system are compared to the ones arrived at by means of a particle swarm optimization (PSO) algorithm.…”