HYSYS.Plant optimization

Emphasis is placed in this chapter on the usage of process simulators to carry out the optimization simultaneously with converging the recycle loops and/or decision variables. To do the optimization efficiently, simulators use one of three methods (1) successive linear programming (SLP), (2) successive quadratic programming (SQP), and (3) generalized reduced gradient (GRG). Emphasis in this chapter is placed on SQP, used by ASPEN PLUS and HYSYS.Plant. GRG, which is used by CHEMCAD, is not discussed here, but is covered by Edgar et al. (2001). 

Be able to optimize a process using ASPEN PLUS and HYSYS.Plant beginning with the results of a steady-state simulation. 

Unsteady-state or dynamic simulation accounts for process transients, from an initial state to a final state. Dynamic models for complex chemical processes typically consist of large systems of ordinary differential equations and algebraic equations. Therefore, dynamic process simulation is computationally intensive. Dynamic simulators typically contain three units (i) thermodynamic and physical properties packages, (ii) unit operation models, (hi) numerical solvers. Dynamic simulation is used for batch process design and development, control strategy development, control system check-out, the optimization of plant operations, process reliability/availability/safety studies, process improvement, process start-up and shutdown. There are countless dynamic process simulators available on the market. One of them has the commercial name Hysis [2.3]. 

Hysys.Process steady state flowsheeting for optimal new designs and modelling of existing plants, evaluate retrofits and improve the process. 

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