Optimal power flow with SVC devices by using the artificial bee colony algorithm

Abstract

In this paper a simple and efficient heuristic search method based on the artificial bee colony (ABC) algorithm is presented and used for the optimal power flow (OPF) problem in power systems with static VAR compensator (SVC) devices. The total generation cost of a power system with SVC devices (which improve the voltage stability at load buses) is optimally minimized with the use of ABC. The ABC, which is based on the foraging behavior of honey bees searching for the best food source, is a recently proposed optimization algorithm. The performance of the presented ABC algorithm was tested and verified on the IEEE 11-bus and IEEE 30-bus power systems by comparing it with several other optimization methods. Furthermore, ABC is used not only for optimizing the total generation cost and active power loss, but also for improving the voltage stability of the 22-bus power system in Turkey. Our results illustrate that ABC can successfully be used to solve nonlinear problems related to power systems.

A new hybrid gravitational search-teaching-learning-based optimization method for the solution of economic dispatch of power systems

“…Therefore, it is very important to operate the 22-bus Turkish power system with minimum economic cost. Despite some studies on Turkey's 22-bus power system [10,13,28], there are few EDP calculations using the standard and newly developed optimization algorithms. Obtained bus test results were compared with the results of other methods in the literature.…”

“…F (x) is the objective function; in Eq. (12), g(x) is the equality constraints; and in Eq (13),. h(x) is the inequality constraints.…”

A New Method Based on Artifıcial Bee Colony Algorithm for the Optimal Location of Shunt Connected Facts Devices

“…Thus, achieving the optimal number, capacity and the location of shunt var compensator can maximize the voltage profile improvement while maintaining requested high-quality operating conditions. There are different techniques which are used to optimize the FACTS placement in literature such as Lagrange multiplier techniques (LM) [7], the decompositioncoordination method (DCM) [8], genetic algorithm (GA) [9], artificial bee algorithm [10], particle swarm optimization (PSO) and non-dominated sorting particle swarm optimization (NSPSO) [11,12], simulated annealing (SA) [13], harmony search (HS) and improved harmony search (IHS) [14,15]. Lagrange multiplier techniques and simulated annealing algorithm used for optimal SVC planning and voltage stability enhancement in [7].…”

“…Genetic algorithm was used to improve the loadability of the system by using four different devices (TSCS, TCVR, TCPST, SVC) in [9]. In [10], the fuel cost along the loadability of the system is improved significantly by using SVC devices for the appropriate load buses. There are also some papers regarding the voltage profile improvement and reducing power loss which use particle swarm optimization and genetic algorithm [11].…”

Comparison of different heuristic algorithms for location and value determination of STATCOM providing minimum losses in power systems

“…[12], [13]'te iki farklı sezgisel algoritmanın güç sistemi güvenilirliğini arttırmak kullanımı ve karşılaştırması verilmiştir. [14]- [17]…”