采用改进粒子群优化算法的燃机联合循环全工况性能优化方法

The medium-high temperature gas turbine (GT) waste heat recovery is inefficient with the traditional steam Rankine cycle, while the Kalina cycle system (KCS) with the temperature glide of ammonia-water in evaporation process could enhance its utilization efficiency. The operating condition of gas turbine always deviates from its design value, and thus it is essential to improve the off-design performance of GT-KCS system. Based on the performance curves of the key components, a mathematical model for predicting the performances of regenerative GT-KCS system under all operation conditions was constructed by the modular modelling approach. The performance difference between the steam Rankine bottoming cycle and KCS bottoming cycle is compared at the rated gas turbine condition. A multi-dimensional performance optimization method for the GT-KCS system on the basis of modified particle swarm optimization algorithm was proposed. The objective function is the maximal thermal efficiency of the combined cycle by optimizing IGV opening and rotational speed of KCS boosting pump. The results show that the thermal efficiency of GT-KCS system is 1.57% higher than that of traditional gas-steam system at the rated gas turbine condition. At 20% rated load of gas turbine, the net power contribution proportion of the bottoming cycle to GT-KCS system is 41.87%. Compared with the single gas turbine cycle, the power plant thermal efficiency could be improved by 9.92%~14.67% under different gas turbine loads by introducing the KCS bottoming cycle.