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Abstract
With regards to optimal power flow models of FACTs devices, several models have been published. These encompass both DCOPF and ACOPF models incorporating Series as well as Shunt devices. Finding a feasible solution is of utmost importance with respect to OPF solutions. Feasibility not only encompasses feasibility with regards to voltage limits and line flows limits but it includes any constraints related to power flow control devices installed in the power system. These include FACTs devices. Several models have been published where the constraints have been included in non-Linear ACOPF models. However, few exist where the power rating constraints have been incorporated in a Linear ACOPF model.An LPOPF model is proposed for line loading managment of a power system without any change in real and reactive generation output. The proposed LPOPF model aims to minimze congestion. The accuracy of the proposed model is improved by adjusting the control variables depending on the feasibility and accuracy of linearization of each LPOPF iteration. Furthermore, in order to obtain larger reduction in line loading, the solution space of LPOPF is updated at every iteration regardless of if the solution of the current LPOPF model is feasible or infeasible. This enlarges the solution space of LPOPF and hence helps in obtaining a feasible solution which is more optimal. Morevoer, an LPOPF formulation has been proposed which combines UPFC control along generation control. The co-optimization of the two controls can be used to effectively manage the line loading of the power system. Generation control considered is of three categories which are real generation control, reactive generation control and the combined used of real and reactive generation control. By doing so, the degree of effectiveness of a UPFC can be highlighted in the presence of generation control. Furthermore, for optimal location of UPFC, a computationally efficient algorithm,namely the teaching learning based optimization(TLBO) has been applied. This method is easy to implement relative to other population based algorithms like particle swarm optimization. The algorithm has been adapted and modified to obtain the optimal combination of UPFC placements on a power system. The discrete version of TLBO has been used which is called DTLBO. The DTBLO has been modified further in order to take into account the combinatorial optimization for the placement of 2 UPFCs. Further modifications have been made for the given DTLBO placement algorithm to improve convergence using steps used in the continuous TLBO algorithm. To the best of authors knowledge, an easy to implement algorithm such as the DTLBO has not been used previously to determine the optimal location of UPFC for line loading management. Lastly, an algorithm is introduced to find the optimal rating of the UPFC considering three generation control scenarios: No generation control, real generation control only and reactive generation control only. A cost-benefit analysis is shown to discuss the trade off between cost of UPFC and degree of control over line loading of the power system.