Small wind turbine installations have a variety of potential uses, each with unique performance demands and operating conditions. Many applications require that the turbine is placed in wind conditions that are not ideal for optimum operation. Better predictive techniques can improve wind turbine performance through improved control strategies and enhanced designs. Conventional methods of wind power design and control utilize an average power coefficient. In this thesis, various techniques to predict the transient power coefficient of a wind turbine are developed. The operation of a Savonius wind turbine is accurately represented, with a new model which considers the flow distributions to predict the changes in power output at all rotor positions. Another model is developed that represents the dynamics of a small horizontal wind turbine, including the effect of transient wind conditions on rotor speed and acceleration. These can supplement current methods to determine turbine placement, selection and categorization.