In recent years, sustainable development issues are considerably noticed for energy policy-making. In electric industry, major portion of the transition to a sustainable energy system is relying on wind power. However, due to some characteristics of wind power plants (W) such as intermittency, high capital investment, and financial risk, they may not be an attractive investment option for independent investors. Nevertheless, the public demand and the environmental concerns have persuaded energy policy-makers to support the integration of wind power into the power system using different support policies. Although the pursuit of the support schemes lead to development of wind power projects, but they impose a considerable economic aspect on governments. On the other hand, investment in W is tightly conditioned by transmission network expansion. In electricity markets, wind producers generally offer power at zero price and are paid by the Locational Marginal Price (LMP) of the bus where they are located. Therefore, the transmission network and its future expansion plans can play a determinative role in revenue and profitability of a WPP. In an electricity market, transmission system operator (TSO), as the planner, is responsible for efficient expansion of transmission network. Hence, TSO can consider the investors’ concerns in its expansion strategies and provide economic motivation to stimulate more private investment in W. Toward this end, it is necessary to consider the interactions between transmission expansion planning (TEP) and wind power investment in an integrated framework. Moreover, the desired framework must properly represent the market clearing process and inherent uncertainties in the input data of the problem such as load and wind power production. In this dissertation, a stochastic framework is presented for analyzing the role of TEP to make wind projects attractive. The problem is formulated as a bi-level optimization model. In the upper-level (UL) problem, TSO decides on the number and routes of the new transmission lines. The siting and sizing of the economically attractive W are also determined in the UL. The objective functions of the UL optimization problem are minimization of new transmission line costs, maximization of the financial attractive W capacity, and maximization of power system reliability. The mean-variance (MV) theory is used to analyze the attractiveness of W. In the MV theory, the profit and financial risk are simultaneously taken into account. In the lower-level (LL) there is two sets of optimization problems. The first one represents the market clearing which calculates the LMPs of network buses for each load and wind scenario and the second one represents composite power system reliability evaluation which calculates expected energy not served at hierarchical level II (EENS HLII ). In order to demonstrate the feasibility and effectiveness of the proposed methodology, it is implemented to modified versions of the IEEE-RTS and IEEE 118 bus test systems. The obtained results show that adoption a proper strategy for TEP can lead to more private investment absorption in wind power without a significant additional transmission investment cost.