Steam Power System Optimization Design And Operation Of Integrated Modeling And Solution Strategy

Steam power system is an important part of the process industry, whose secure and steady operation is the foundation of security, stabilization and long period operation for the whole corporation. The design, operation and control of steam power system affect the effective utilization of energy and economic performance in the process industry. Therefore, the study on the design, operation and control is very important to direct the general optimization of steam power system.(1) In the dissertation, the literature about optimal design, optimal operation and optimal control of steam power system were summarized. The physical structure, flow structure and hierarchical structure of steam power system were expatiated. Besides, the performance models of boiler, steam turbine, gas turbine, steam converter valve and heat recovery steam generator (HRSG) were gotten.(2) Based on the design model and operation model of steam power system, the integrated model of design level and operation level was constructed according to the integrated modeling theory. In this model, the non-linear performance of equipment investment cost, the changes of boiler efficiency and the non-linear performance of steam turbine working were considered. Besides, the cost of changeover between periods of operation was considered in the model.(3) In the model mentioned above, the possible combination dimensions of the system will show exponential growth with the number of unit and periods. Usual algorithm cannot solve the problem effectively. In order to overcome this difficulty, the improved genetic algorithm was introduced. The improved genetic algorithm was improved on many aspects and it was much more simple than before. Using this method to solve the multi-period MINLP problem, the optimal result could be achieved within reasonable time.(4) Based on the integrated modeling theory, two examples were studied. One was the short-term optimal multi-period operational planning problem. The other was the simultaneous optimization of the design and operation for a steam power system. Two MINLP models were constructed and solved by the improved genetic algorithm, which indicated that the integrated model and solving strategy were effective. In the last part of the dissertation, a MILP optimal operational planning model was constructed and solved by LINGO5.0 for an actual steam power system. The satisfying one-year operational planning of the steam power system was gotten, which testified that the integrated model was practicable.