Genetic optimization of steam multi-turbines system

• Genetic optimization model for a set of five various steam turbines was presented.
• Four various thermodynamic optimization strategies were proposed and discussed.
• Operational parameters (steam pressure, temperature, flow) influence was examined.
• Genetic algorithm generated optimal solutions giving the best estimators values.
• It has been found that similar energy effect can be obtained for various inputs.

Optimization analysis of partially loaded cogeneration, multiple-stages steam turbines system was numerically investigated by using own-developed code (C++). The system can be controlled by following variables: fresh steam temperature, pressure, and flow rates through all stages in steam turbines. Five various strategies, four thermodynamics and one economical, which quantify system operation, were defined and discussed as an optimization functions. Mathematical model of steam turbines calculates steam properties according to the formulation proposed by the International Association for the Properties of Water and Steam. Genetic algorithm GENOCOP was implemented as a solving engine for non–linear problem with handling constrains.Using formulated methodology, example solution for partially loaded system, composed of five steam turbines (30 input variables) with different characteristics, was obtained for five strategies. The genetic algorithm found multiple solutions (various input parameters sets) giving similar overall results. In real application it allows for appropriate scheduling of machine operation that would affect equable time load of every system compounds. Also based on these results three strategies where chosen as the most complex: the first thermodynamic law energy and exergy efficiency maximization and total equivalent energy minimization. These strategies can be successfully used in optimization of real cogeneration applications.