: Transmission Switching (TS) is one of the most important tools in power system operation. Practically, TS is able to bring down the operating costs of the power system. On the other hand, increasing the competition level in electricity markets is one of the main concerns of electricity market operators. Decreasing the market power is an usual way to attain a higher level of competition. Since the market power is influenced by the network topology, in this thesis, the TS impacts on the market power and the method to consider this impact within the TS process are investigated. At first, the TS impacts on the market power are studied. For this porpose, Competition Boundary (CB) problem is developed to consider the TS. In this problem, minimizing or maximizing Herfindahl - Hirschman Index (HHI, as a measure of market concentration) subject to DC power flow constraints of the electrical network is modeled as a Quadratically Constrained Programming (QCP) problem. Since HHI is a quadratic function of the firms production, maximizing HHI results in a nonconvex optimization problem. To be confident with achieving global optimum, HHI is approximated as a piecewise linear function. This approximation converts the extended CB problem to a Mixed Integer Linear Programming (MILP) problem. Implementing the MILP model to the test cases shows that TS can influence the market power level through the network. The impact is significant, where the maximum HHI is considerd. Moreover, peak load conditions intensify the impact of TS on the market power. These results point out that TS can adversely affects the market power, and as a consecuence, completion level, if the TS is employed without considering this impact. Next, seasonally optimal transmission switching framework is proposed to minimize the operation cost over the study horizon, considering market power of market participants. The upper level problem determines the transmission line(s) to be switched out in order to minimize the operation cost over the horizon. In the second level, the profit of each generation companies is maximized by considering its market power. Market clearing conditions which are common to all generation companies are modeled in the third level. By using strong duality theorem and Karush–Kuhn–Tucker (KKT) conditions, profit maximization problem of each generation company is modelled as a single level Mathematical Programming with Equilibrium Constraints (MPEC) problem. To find the equilibrium among generation companies, we should consider all the MPECs, simultaneously, which results in an Equilibrium Problem with Equilibrium Constraint (EPEC) model. The EPEC is a set of equality and inequality constraints that represents the equilibrium conditions. The second and the third levels of the mentioned three level optimization problem are replaced by the subsequent EPEC. Therefore, the three level optimization problem is converted to a single level optimization problem. By using some linearization techniques, the resultant single level optimization problem is converted to an MILP problem and is implemented on a three-bus test case. Numerical results show that employing proposed seasonal transmission switching framework can reduce the operation costs over the study horizon. Moreover, the lower market power level is achieved in comparison with the case in which the TS is not employed. Keywords: Transmission switching, market power, mixed integer linear programming, electricity market equilibrium, multi level optimization problem