Modelling long-run cost minimization and environmental provisions for utility expansion

A realistic long-run cost minimization model for electric power expansion is presented. The model uses mixed integer and dynamic programming methods to minimize electric power costs while considering alternative generation technologies and fuel choices and satisfying demand, the environmental regulations of the Clean Air Act Amendment (CAAA) of 1990 and reliability constraints. The model can be used to produce the optimal production schedule for a combination of existing and projected new plants. Actual data from a large eastern US utility are used to provide a realistic test of the model and to reach conclusions about the optimal path to take to comply with the CAAA. Application of the model to these data indicates that in order to comply with the CAAA, fuel switching is preferred over scrubbing the flue gases. For this case, fuel switching proved to be 9.5% less costly than scrubbing.