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Constraints in fuel supply, electricity generation, and transmission interact to affect the welfare of strategic generators and price-sensitive consumers. We consider a mixed integer bilevel programming model in which the leader makes capacity expansion decisions in the fuel transportation, generation, and transmission infrastructure of the electricity supply network to maximize social welfare less investment cost. Based on the leader's expansion decisions, the multiple followers including the fuel suppliers, ISO, and generation companies simultaneously optimize their respective objectives of cost, social welfare, and profit. The bilevel program is formulated as a mathematical program with complementarity constraints. The computational challenge posed by the discrete character of transmission expansions has been managed by multiple model reformulations. A lower bound provided by a nonlinear programming reformulation increases the efficiency of solving a binary variable reformulation to global optimality. A single-level optimization relaxation serves as a competitive benchmark to assess the effect of generator strategic operational behavior on the optimal capacity configuration.