Multi-period Operational Optimization For Parameters Uncertainty Of Steam Power System

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. Steam power system (SPS) supplies mechanical, electrical, and thermal power, consuming a large amount of energy, so the operational optimization of SPS to reduce the production cost and energy consumption by improving the design, operation and control performance of steam power system is an important way to improve efficiency of a chemical process industry.Firstly, 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 were gotten.Secondly, A mixed-integer linear programming (MILP) model including the cost of equipment start-up and shutdown was established to optimize multi-period operation of steam power system in this paper. The boilers and steam turbines are based on actual performance model for a reasonable linearization. In this way, optimize the operation of the system to ensure accuracy and avoid the difficulties in solving non-linear model. The model are set up to use the example of the Qilu, By using LINGO to solve this model , reasonable optimal operation plan can be obtained and save a lot of running costs.Thirdly, The changes of production planning, market demand, climate, season and other uncertain conditions can cause the external demand of steam and power changes frequently, leading to great difficulties on actual optimal operation management. Based on the profound analysis of operation level activity performance and the importance of optimization, The paper presented a strategy to decrease the problem search space by discrediting the uncertainty parameters in their feasible region and transferring the uncertainty problem into a certainty problem.Finally, A mixed integer linear programming (MILP) model was established for multi-period operational planning of utility system under parameter uncertainty. A case study showed that by using LINGO to solve the operational planning optimization problem significant savings can be obtained as well as operability can be guaranteed. Furthermore, the operational planning optimization result can presents a relation curve for operation cost under different parameter uncertainty levels. This curve provided a quantitative guidance for planner or scheduler.