This paper presents a novel optimization based methodology to allocate Flexible AC Transmission Systems (FACTS) devices in an attempt to improve the previously mentioned researches in this field. Static voltage stability enhancement, voltage profile improvement, line congestion alleviation, and FACTS devices investment cost reduction, have been considered, simultaneously, as objective functions. Therefore, multi-objective optimization without simplification has been used in this paper to find a logical solution to the ALLOCATION problem. The optimizations are carried out on the basis of location, size and type of FACTS devices. Thyristor Controlled Series Compensator (TCSC) and Static Var Compensator (SVC) are utilized to achieve the determined objectives. The problem is formulated according to Sequential Quadratic Programming (SQP) problem in the first stage. This formulation is used to accurately evaluate static security margin with congestion alleviation constraint incorporating voltage dependence of loads in the presence of FACTS devices and estimated annual load profile. The best trade-off between conflicting objectives has been obtained through Genetic Algorithm (GA) based fuzzy multi-objective optimization approach, in the next stage. The IEEE 14-bus test system is selected to validate the allocated devices for all load-voltage characteristics determined by the proposed approach.

Flexible AC Transmission Systems (FACTS) controllers with its ability to directly control the power flow can offer great opportunities in modern power system, allowing better and safer operation of transmission network. In this paper, in order to find type, size and location of FACTS devices in a power system a Dedicated Improved Particle Swarm Optimization (DIPSO) algorithm is developed for decreasing the overall costs of power generation and maximizing of profit. Thyristor-Controlled Series Capacitor (TCSC) and Static VAr compensator (SVC) are two types of FACTS devices that are considered to be installed in power network. The purpose of this study is reducing the power generation costs and the costs of FACTS devices with considering different load levels. The main bases of this paper are using of Optimal Power Flow (OPF) and DIPSO algorithm to techno-economical analysis of the system for finding optimal operation. The Net Present Value (NPV) method is used to economic analysis of the system and power losses and maximum possibility load demand are considered for technical analysis. The proposed method is implemented on IEEE 57-bus test system and the achieved results are compared with genetic algorithm and particle swarm optimization methods to illustrate its effectiveness.

In this investigation, a novel approach is presented to find the optimum locations and capacity of Flexible AC Transmission Systems (FACTS) devices in a power system using a fuzzy multi-objective function. Maximising the fuzzy satisfaction allows the optimization algorithm to simultaneously consider the multiple objectives of the network to obtain active power loss reduction; i.e., new FACTS devices cost reduction, robustifying the security margin against voltage collapse, network loadability enhancement and a voltage deviation reduction of the power system. A Genetic Algorithm (GA) optimization technique is then implemented to solve the fuzzy multi-objective problem. Operational and control constraints, as well as load constraints, are considered for optimum device ALLOCATION. Also, an estimated annual load profile has been utilized in a Sequential Quadratic Programming (SQP) optimization sub-problem to find the optimum location and capacity of FACTS devices, accurately. A Thyristor Controlled Series Compensator (TCSC) and a Static Var Compensator (SVC) are utilized as series and shunt FACTS devices in this study. The Fars regional electric network is selected as a practical system to validate the performance and effectiveness of the proposed method.

Flexible AC Transmission Systems (FACTS) devices have shown satisfactory performance in alleviating the problems of electrical transmission systems. Optimal FACTS ALLOCATION problem, which includes finding optimal type and location of these devices, have been widely studied by researchers for improving variety of power system technical parameters. In this paper, a DIgSILENT-based Discrete Particle Swarm Optimization (DPSO) algorithm is employed to manage the power flow, alleviate the congestion, and improve the voltage profile in a real case study. The DPSO have been programmed in DPL environment of DIgSILENT software and applied to the power grid of Gilan Regional Electric Company (GilREC), located in north of Iran. The conducted approach is a user-friendly decision making tool for the engineers of power networks as it is executed in DIgSILENT software which is widely used in electric companies for the power system studies. The simulation results demonstrate the effectiveness of the presented method in improving technical parameters of the test system through several case studies.