Multi-parameter Joint Optimization Based on Steam Turbine Thermal System Characteristic Reconstruction Model

Abstract

Steam turbine thermal system characteristic reconstruction model for multi-parameter joint optimization is proposed in this paper. This paper has two main improvements. First, a steam turbine thermal system characteristic reconstruction model is conducted, which includes turbine, condenser and heater. There are three iterative nested algorithms in this model. In the innermost layer, avariable condition calculation model of condenser is nested, and the exhaust flow and exhaust steam pressure can be calculated. In the outermost layer, the power equation is applied as the iteration ends. In this model, simulation of thermal system of steam turbine three kinds of disturbing factors demand can be realized well and the joint optimization of thermal system of steam turbine flow section and the cold end can be realized. Through calculation and comparison, the model constructed in this paper is proved to have high accuracy, and the calculation process is stable and convergent. At the same time, the joint optimization method involving turbine main steam pressure and exhaust pressure is proposed here. In this method, heat consumption rate is the optimization objective, with steam turbine thermal system characteristic reconstruction model, the optimal main steam condenser and vacuum pressure were obtained. The result of A 600MW condensing unit showed that the method could be synchronized to determine the optimal combination of circulating pump, the best vacuum and sliding pressure curve of main steam under different load and different ambient temperature. Comparison results also showed that the joint optimization solution of main steam pressure and exhaust pressure is superior to optimized solution main steam pressure individually.