Coal blending optimization under uncertainty

Coal blending is one of several options available for reducing sulfur emissions from coal-fired power plants. However, decisions about coal blending must deal with uncertainty and variability in coal properties, and with the effect of off-design coal characteristics on power plant performance and cost. To deal with these issues, a multi-objective chance-constrained optimization model is developed for an illustrative coal blending problem. Sulfur content, ash content and heating value are treated as normally distributed random variables. The objectives of the model include minimizing the: (1) expected (mean) costs of coal blending; (2) standard deviation of coal blending costs; (3) expected sulfur emissions; and (4) standard deviation in sulfur emissions. The cost objective function includes coal purchasing cost, ash disposal cost, sulfur removal cost, and fuel switching costs. Chance constraints include several risk measures, such as the probability of exceeding the sulfur emission standard. Several results are presented to illustrate the model.