Due to the high cost of investment for the development of the transmission network and the key role of transmission networks in the restructured environment, the use of FACTS devices is considered a key issue. In this paper, two issues of location and optimal capacity of TCSC in transmission networks has been investigated. In the proposed method, the objective function is defined in order to reduce losses and increase network load ability. This problem was studied in two technical and economic approaches and its results were presented. For this purpose, first, the problem of locating in peak load conditions of the network was done separately and then simultaneously in the technical approach. Next, in the economic approach, the cost of installing the equipment in question was also included in the optimization problem. In this approach, the profit from installing TCSC is considered as the objective function of the problem and the best place and capacity of the equipment was determined in order to achieve the maximum amount of profit. Average models available in the references have been used to model FACTS devices. Also, due to the contingency in the network, the improvement of the maximum load ability of the network lines under the outages conditions of the line and generator has been discussed. In order to two-objective optimization in the technical approach, the genetic algorithm based on the Pareto front and the multi-objective HSA has been used. This algorithm has a good speed in the convergence of large nonlinear problems. Also, a comprehensive and new model with the combination of TCSC-high-voltage direct current (HVDC)- static VAR compensators (SVC) has been introduced and the intended simulation has been performed. Finally, with the help of a new meta-heuristic algorithm, the topic of optimal power flow in the presence of these devices has been comprehensively presented and the results have been compared with similar methods. The results of numerical studies show that FACTS devices can have a significant effect in reducing losses and increasing network load ability.Also, the type of equipment used has a great impact on the outcome of the problem. As it is clear from the results of the simulations, in the technical approach, in order to achieve the lowest amount of losses in the IEEE 30-buses network by installing the equipment, TCSC should be installed in line number 15 between buses 4 and 12. The best amount of reactance compensation of this line was about 79.90% of the line reactance, as a result of which the network power loss was reduced by about 4.17%. Also, in the continuation of the simulations, the best place and capacity to install TCSC in the network was determined in order to improve the network load ability. As a result of this simulation, the best location of line 36 between buses 27 and 28 was determined, and the best amount of reactance compensation for this line was also 80% of the line reactance. As a result of this compensation, the load index value of the network improved by 23.02%. Also, in the economic approach, the best location and capacity to obtain the maximum profit was obtained in order to reduce power losses and improve the loadability of the network. The simulation was implemented by MATLAB software and the results showed the effectiveness of the proposed method in all case studies.
