杜洋, 戴义平, 任敬崎, 曹越, 王江峰, 赵攀. 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[J]. 中国电机工程学报, 2021, 41(10): 3434-3446. DOI: 10.13334/j.0258-8013.pcsee.201402
引用本文: 杜洋, 戴义平, 任敬崎, 曹越, 王江峰, 赵攀. 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[J]. 中国电机工程学报, 2021, 41(10): 3434-3446. DOI: 10.13334/j.0258-8013.pcsee.201402
DU Yang, DAI Yiping, REN Jingqi, CAO Yue, WANG Jiangfeng, ZHAO Pan. Performance Optimization of Gas Turbine Combined Cycle Using Modified Particle Swarm Optimization Algorithm[J]. Proceedings of the CSEE, 2021, 41(10): 3434-3446. DOI: 10.13334/j.0258-8013.pcsee.201402
Citation: DU Yang, DAI Yiping, REN Jingqi, CAO Yue, WANG Jiangfeng, ZHAO Pan. Performance Optimization of Gas Turbine Combined Cycle Using Modified Particle Swarm Optimization Algorithm[J]. Proceedings of the CSEE, 2021, 41(10): 3434-3446. DOI: 10.13334/j.0258-8013.pcsee.201402

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

Performance Optimization of Gas Turbine Combined Cycle Using Modified Particle Swarm Optimization Algorithm

  • 摘要: 由传统水蒸汽朗肯循环回收中高温(300~550℃)燃机(gas turbine,GT)余热收益不高,而采用具有变温蒸发特性的卡琳娜循环(Kalina cycle system,KCS)可以有效提升中高温燃机余热利用率。燃机运行经常偏离设计工况,因而燃机-卡琳娜(Kalina cycle system,KCS)联合循环的全工况性能提升存在迫切需求采用模块化建模方式,构建基于核心部件性能曲线的回热式GT-KCS联合循环的全工况性能仿真模型,对比研究了在燃机额定工况下水蒸汽朗肯底循环和KCS底循环的性能差异;提出基于改进粒子群优化算法的GT-KCS联合循环全工况性能多维度优化方法,以联合循环热效率最大化为目标,同时优化燃机IGV开度和底循环增压泵转速。研究结果表明,在燃机额定工况下,GT-KCS联合循环热效率较燃气 蒸汽联合循环高1.57%。在20%额定燃机负荷下,KCS底循环功率占联合循环功率比值可达41.87%。与单独的燃机循环相比,GT-KCS联合循环在变燃机负荷工况下可以使机组热效率提升9.92~14.67%。

     

    Abstract: 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.

     

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