Wind energy has become one of the most cost-effective renewable sources nowadays. However, the stochastic nature associated with wind-energy production represents a great challenge for power-system operations. Therefore, probabilistic techniques are necessary to evaluate the performance of power systems with substantial amounts of wind generation. This paper presents a probabilistic based bi-level optimization approach for evaluating the impact of wind farm location and control strategy on the penetration level of wind farms and electricity market prices. The bi-level optimization model is formulated as mathematical program with equilibrium constraints (MPEC) and solved by means of the NLPEC solver in the General Algebraic Modeling System (GAMS) environment. Several cases studies are presented in this paper to determine to the optimal wind generation penetration and market prices with different locations and control strategies for wind farms. Moreover, some scenarios are discussed in regards to the practical allocation of wind farms. Crown Copyright (C) 2017 Published by Elsevier Ltd. All rights reserved.