Notes
This dissertation deals with the integration of the operability topics, such as the flexibility, and the operational, environmental and economic efficiencies, into chemical process design by means of mathematical programming. In the first part, the method was developed for testing the accuracy, complexity, and adequacy of process flow sheets modelling regarding the embedded trade-offs between the invested funds and generated cash flows. This method analyses the cash flow function vs. investment, its derivative, and the differences between optimum solutions obtained by different economic criteria, such as the total annual cost, the profit, the net present value, the payback time, the internal rate of return etc. Suitable process models generate concave monotonically increasing cash flow functions, and flat derivative curves. Optimal designs of such models are substantially different when using different economic objectives. On the contrary, those process models with inappropriate level of accuracy produce unimodal cash flow function with steep derivative, and small differences between optimal results.It is shown that those optimal results obtained by different economic criteria differ not only in the economic indicators but also in the operational efficiency and environmental indicators. Quantitative criteria, such as the profit and costs, generate more expensive yet operationally more efficient, and environmentally less harmful processes at lower profitability. Qualitative criteria, such as the internal rate of return and payback time, produce processes with less efficient usage of resources at higher profitability, and lower investment cost. The net present value generates the compromise solutions regarding the economic, operational, and environmental efficiencies of optimal processes during the single-objective optimization. Multi-objective optimization, however, could provide more precise insight intothe trade-offs among the above mentioned efficiencies. It is shown in thisdissertation that various economic criteria, with regard to the selected environmental criterion, generate the sets of nondominant (Pareto) solutions, which differ in the range of values as well as in the lowest and highest attainable values of particular objective. In the second part of dissertation, a strategy is presented for flexible process flow sheets design with a large number of uncertain parameters. The mathematical formulation is based on the two-stage stochastic problem with recourse, and its transformation into the significantly reduced deterministic equivalent. The latter is solved over the reduced set of critical points, while the expected objective value is approximated in one single point, i.e. the nominal point orthe Central Basic Point. Two methods for scenario reduction were developed: the sensitivity analysis of uncertain parametersć influences on the first-stage variables and the objective function, and the two-level method, which combines GAMS optimization program with the external functions. The results of the examples show that flexible solutions can be generated by usingthe proposed methods at significantly reduced computational effort, even for problems with up to 100 uncertain parameters.