超临界回热燃煤发电系统热力循环的构建及分析

Construction and analysis of the thermal cycle of the supercritical regenerative coal-fired power generation system

回热过程对朗肯循环热效率的提升起重要作用,但当前有关回热的研究仅局限在亚临界区域,并未对超临界区域进行深入的探索.本文提出超临界回热方式,构建了超临界回热循环,从效率角度探明了该回热过程的优势.以某二次再热燃煤发电系统为例,基于热力学第一、第二定律对其与BEST小机回热进行热力学理论计算与对比分析.结果表明,超临界回热可有效提高发电效率,在本文案例中,当主汽参数为32 MPa和610/625/622℃时,所提出的两种超临界回热过程可在发电效率47.57%基础上,分别提升0.96%与1.02%, BEST小机回热可使发电效率提升0.1%.同时发现BEST小机回热可有效降低循环回热过程的?损,超临界回热则可大幅降低锅炉?损,当两者耦合时,可以实现效率的进一步提升(48.7%和48.76%).本文提出的超临界回热过程是在亚临界区域回热的基础上突破瓶颈,进一步实现了在超临界区域的回热,是循环回热优化的进一步发展.

Regeneration is significant in improving the thermal efficiency of the Rankine cycle. However, current research on regeneration islimited to the subcritical region, and the supercritical region has not been deeply explored yet. In this study, the supercriticalregenerative method is proposed for the first time, the supercritical regenerative cycle is constructed, and the advantages of theregeneration process are reflected by its high power generation efficiency. Considering a double-reheating unit as an example, thisstudy performs a theoretical calculation and a comparative analysis with BEST turbine generation based on the first and second lawsof thermodynamics. The analysis results show that supercritical regeneration can effectively improve power generation efficiency. Inthis paper, for the main vapor parameters of 32 MPa and 610/625/622°C, the two supercritical regenerative technologies can improvethe power generation efficiency by 0.96% and 1.02%, respectively, on the basis of 47.57% power generation efficiency. Moreover,BEST turbine regeneration can increase the power generation efficiency by 0.1%. Meanwhile, BEST turbine can effectively reduceexergy loss during regeneration, while supercritical regeneration can greatly reduce boiler exergy loss. Further efficiency gains can beachieved (48.7% and 48.76%) by coupling the two methods. The supercritical regeneration process proposed in this paper breaks thebottleneck and realizes regeneration in the supercritical region. The proposed method is the next step in the further development ofcycle regeneration optimization.