In this paper, a computation framework for addressing combined economic and emission dispatch(CEED) problem with valve-point effects as well as stochastic wind power considering unit commitment (UC)using a hybrid approach connecting sequential quadratic programming (SQP) and particle swarm optimization(PSO) is proposed. The CEED problem aims to minimizethe scheduling cost and greenhouse gases (GHGs) emission cost. Here the GHGs include carbon dioxide (CO2), nitrogendioxide (NO2), and sulphur oxides (SOx). A dispatchmodel including both thermal generators and wind farms is developed. The probability of stochastic wind power basedon the Weibull distribution is included in the CEED model.The model is tested on a standard system involving sixthermal units and two wind farms. A set of numerical casestudies are reported. The performance of the hybrid computation almethod is validated by comparing with othersolvers on the test system.