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2026, 01, v.53 138-148
基于螺杆膨胀机的太阳能辅助热电联产系统性能分析
基金项目(Foundation): 北京市自然科学基金资助项目(3172031)
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摘要:

由于热电联产机组供热蒸汽参数的不匹配和机组调峰能力的不足,导致了抽汽能量的浪费和较低的可再生能源利用率。为此,在能源系统变革与新能源体系建设的背景下,以提高热电联产机组能效水平,增加运行灵活性为目的构建了基于螺杆膨胀机的太阳能辅助热电联产系统。以某600 MW机组为例,利用Ebsilon软件建立热力学模型,对不同运行模式下互补系统的调峰能力、典型日运行特性以及结合碳交易的经济收益进行分析。结果表明,互补系统在两种运行模式下,均能有效拓展热电特性区域和提高系统调峰能力,调峰能力比原机组最大可增加19.94%,夜间风电消纳能力提升46.3 MW;采暖季典型日内,螺杆膨胀机发电量293.36 MW,互补系统节省标准煤耗量64.17 t(1.66%);非采暖季典型日内,系统太阳能累计发电量144.41 MW,平均光电效率可达18.08%。互补系统每年可减少43 713.27 t的碳排放量,节省了349.71万元的碳交易成本。

Abstract:

Due to the mismatch in heating steam parameters and the insufficient peak-shaving capacity of cogeneration units, extracted steam energy is wasted and the utilization rate of renewable energy remains low. In the context of energy system transformation and the development of new energy systems, a solar-assisted cogeneration system based on a screw expander(SE) has been established to enhance the energy efficiency and operational flexibility of the units. Taking a 600 MW unit as an example, the thermodynamic model is constructed using Ebsilon software to analyze the peak shaving capacity, typical daily operational characteristics and economic benefits incorporating carbon trading under different operation modes. The results show that the hybrid system effectively expands the thermoelectric operating range and enhances peak-shaving capacity under both operating modes. The maximum increase in peak-shaving capacity reaches 19.94% compared to the original unit, and the wind power consumption capacity at night is increased by 46.3 MW. On a typical heating season day, the power generation of SE is 293.36 MW, and it saves 64.17 t(1.66%) of standard coal consumption. On a typical non-heating season day, the cumulative solar power generation reaches 144.41 MW, with an average photovoltaic efficiency of 18.08%. The cogeneration system can reduce 43 713.27 tons of carbon emissions per year, saving 3.497 1 million yuan of carbon transaction costs.

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基本信息:

中图分类号:TK519;TM621

引用信息:

[1]柴萍涛,顾煜炯,朱萍.基于螺杆膨胀机的太阳能辅助热电联产系统性能分析[J].华北电力大学学报(自然科学版),2026,53(01):138-148.

基金信息:

北京市自然科学基金资助项目(3172031)

发布时间:

2024-04-16

出版时间:

2024-04-16

网络发布时间:

2024-04-16

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