The power sector is undergoing a series of transformations to accommodate the energy transition. Among these changes, the market liberalization stands out, with greater consumer autonomy and the possibility of migration between the regulated and free markets. This context adds complexity to the task of energy distribution companies to project their future demand and to contract energy to serve the captive market, as these contracts should serve increasingly dynamic consumers and, consequently, a more unstable portfolio. Moreover, the migration of consumers to the free market may generate over-contracting of distributors, incurring extra costs for it and for the remaining captive consumers. This work proposes an optimization model to determine the equilibrium prices in the free and regulated environments in a liberalized market. Given the interdependence of agents decisions (distributors, captive consumers, free consumers and generators), their interactions are modeled as Multiple Optimization Problems with Equilibrium Constraints (MOPEC), in which each agent s revenue maximization problems are combined into a single optimization problem, and connected by equilibrium constraints. It is demonstrated that the proposed MOPEC can be represented by a linear programming problem. The agents are modeled as risk-averse, with their individual objective functions represented as the convex combination of the expected value and the Conditional Value at Risk (CVaR) of their revenues. Among the results of the model, we highlight the optimal levels of consumer migration, contracting decisions, and contract prices in the free market and tariffs in the regulated market, for a given system configuration. In addition, different regulatory proposals are presented and modeled for the treatment of liabilities associated with the over-contracting of distributors. The model is applied in a simplified case study and another one with realistic data of the Brazilian power system. Finally, the model is integrated in an iterative process that determines the optimal system expansion, so that the resulting contracting decisions and prices generate economic signals for investments in generation capacity expansion. This methodology is applied in a case study comprising generation expansion exercises of the Brazilian power system.