OPTIMAL SO2 COMPLIANCE PLANNING USING PROBABILISTIC PRODUCTION COSTING AND GENERALIZED BENDERS DECOMPOSITION

In 1990, the U.S. Congress passed a new Clean Air Act which contains provisions to control sulfur dioxide (SO2, a primary cause of acid rain) emitted from electric generation plants in the United States. Under this Act, electric utilities will be able to choose from a wide range of SO2 emissions control measures. This paper presents a comprehensive emissions control model which can systematically examine all available emissions control options and construct an optimal compliance plan. The model is a nonlinear integer program that uses probabilistic production costing to simulate system generation. A solution procedure based on Generalized Benders Decomposition (GBD) is developed, exploiting the special structure of the problem formulation. The GBD solution procedure employs an efficient method to calculate the derivatives of the expected generation of a unit with respect to the capacity of another unit. The model is applied to a utility system to construct least-cost compliance strategies under a range of prices of allowances. The model can also be used to derive a supply curve for emissions reductions that accounts for emissions dispatch and interactions among control options.