摘要
为研究热网换热器水位稳定性的关键影响参数及其调峰前最佳值,首先建立了二拖一联合循环机组供热系统的动态模型并加以验证,然后基于模型仿真循环水流量分别为1050kg/s、1850kg/s、3050kg/s时,汽轮机从120MW降负荷至90MW的系统关键参数变化,仿真结果表明,循环水流量越小则调峰时热网加热器水位波动越小。进一步采用粒子群算法智能反演确保热网换热器水位波动不超安全限值的调峰操作前最大热网循环水流量,为电厂调峰操作前调整热网循环水流量提供了一种有效整定方法,以提高二拖一机组灵活运行的安全性并保证供热。
In order to study the key influencing variables of water level stability of heat exchanger and the optimal values before peak shaving,a dynamic model of heating supply system of two-by-one CCGT unit was established and verified.When the turbine load is reduced from 120MW to 90MW,the key variables of the system are simulated by the established model under the circulating water flow is 1050kg/s,1850kg/s and 3050kg/s respectively.The results show that a small circulating water flow can reduce the fluctuation of the water level of heat exchanger during peak shaving.Furthermore,particle swarm optimization algorithm is used to invert the maximum circulating water flow of heat exchanger before peak shaving to ensure that the water level fluctuation of heat exchanger does not exceed the safety limit,which can provide an effective tuning method for power plant to regulate the circulating water flow of heat exchanger before peak shaving,so as to improve the safety of two-by-on CCGT during flexible operation and guaranteed heat supply.
作者
张德利
陆念慈
刘振祥
潘蕾
吴子瞻
ZHANG De-li;LU Nian-ci;LIU Zhen-xiang;PAN Lei;WU Zi-zhan(North China Electric Power Research Institute,Beijing 100045,China;School of Energy and Environment,Southeast University,Nanjing 211189,China)
出处
《汽轮机技术》
北大核心
2022年第1期55-59,共5页
Turbine Technology
基金
国家自然科学基金青年科学基金项目(51806034)。
关键词
燃气-蒸汽联合循环
热网加热器水位
热网循环水
粒子群算法
灵活性运行
gas-steam combined cycle
water level of thermos-exchanger
circulating water of heating network
particle swarm optimization algorithm
flexible operation
