Decision support method for cost-effective emission control on a regional scale

In the paper an implementation of a decision support algorithm for selection of emission abatement strategy on a regional scale is presented. The approach refers to optimal allocation of financial means for emission reduction in a given set of power and heating plants. The implementation considered is sulfur-oriented. The problem is formally stated as cost-constrained minimization of environmental damage function by the optimal choice of desulfurization technologies, within the set of the controlled plants. The receptor-oriented objective function utilizes air pollution forecast preprocessed by a regional scale dispersion model. An heuristic algorithm is implemented to solve the optimization problem. This is the improved and more general version of the method discussed earlier in 1]. Compared with that version, the cost constraints are considered in a more realistic form; two components of the total costs – investment and operational – are considered individually for each power plant and for the selected emission abatement technology. This requires a special construction of the optimization algorithm. Computational test results are presented for the set of the major power plants in the Silesia Region. This revised version was published online in June 2006 with corrections to the Cover Date.