The rise of environmental protection and the progressive exhaustion of traditional fossil energy sources have increased the interest in integrating renewable energy sources into existing power systems. The energy saving and emission reduction is of most importance. Wind energy could be one of the most promising renewable energy sources. However, the intermittency and unpredictability of wind power generation creates difficulty in control of frequency and generation scheduling. Many problems will arise in the renewable energy based hybrid power system. In this paper, a fuzzy unit commitment model including wind generators is presented. Primary energy consumption, gas emission and the risk of wind are synthetically considered. Through defining membership function, the deterministic problem is transformed into the fuzzy problem. Then it is reformulated into the nonlinear problem by means of the maximum-minimum fuzzy satisfaction. Improved Genetic Algorithms (IGA) is used to solve the fuzzy optimization problem. The simulation results of a 10-unit system demonstrate that the proposed method is feasible. It can compromise between the primary energy consumption and the risk according to the decision-maker’s will. It provides valuable information in both operational and planning problems in the future.