Abstract
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.
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