基于改进运行参数的双效蒸汽吸收式制冷(VAR)循环中不同流体对性能系数(COP)预测的层相关性

M. Khan, Sambhaji T. Kadam, A. Kyriakides, Ibrahim Hassan, A. Papadopoulos, M. A. Rahman, P. Seferlis
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摘要

蒸汽吸收制冷(VAR)是传统蒸汽压缩制冷(VCR)循环的可持续替代方案,因为它对不可再生能源的需求较低,并且具有开发可再生能源的潜力。传统上,传统单效VAR周期的绩效系数(COP)远低于VCR周期。这提供了改进的空间,可以通过提供相对更高性能的双效VAR循环来实现。双效无功循环的COP是由于从冷凝器或吸收器到二次发电机的废热/废热利用而提高的。双效VAR周期的COP与运行参数相关的模型在公开文献中是不可用的,只有Iyer的相关性是唯一的例外。这项工作应用这种COP相关性使用文献数据的双效VAR与各种制冷剂和吸收剂对操作。对各种流体对的2028多个数据点进行了全面的平均绝对百分比误差(MAPE)分析。结果显示,MAPE(86.6-839%)值对于报告的相关性似乎相当高。此外,利用提出的数据集对模型进行了优化,极大地降低了MAPE,最高可达36.03%。结果还表明,由于缺乏流体特异性参数,这种相关性的应用可能不支持新的双效应VAR周期的发展。因此,建立基于性能的相关性至关重要,该相关性考虑了操作参数和流体参数,以评估新的高效双效应VAR循环的性能。
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Modified Operating Parameter-Based Iyer Correlation for the Coefficient of Performance (COP) Prediction of Different Fluid Pairs in Double-Effect Vapor Absorption Refrigeration (VAR) Cycles
Vapor absorption refrigeration (VAR) is a sustainable alternative to the conventional vapor compression refrigeration (VCR) cycle, owing to its lower non-renewable energy requirements and potentially for exploitation of renewable energy sources. Traditionally, the coefficient of performance (COP) of the conventional single effect VAR cycle is considerably lower than VCR cycles. This provides room for improvement which can be attained through double effect VAR cycles that provide relatively higher performance. The COP of the dual effect VAR cycle is enhanced due to the waste/rejected heat energy utilization from the condenser or the absorber into a secondary generator. Models that correlate the COP of the double effect VAR cycle with operating parameters are not available in the open literature, with Iyer’s correlation being the only exception. This work applies this COP correlation using literature data for double effect VAR that operate with a variety of refrigerant and absorbent pairs. A comprehensive Mean Absolute Percentage Error (MAPE) analysis is performed for more than 2028 data points of various fluid pairs. Results reveal that MAPE (86.6–839%) values appear to be quite high for the reported correlation. Furthermore, the model is optimized using the proposed data set, considerably reducing the MAPE up to 36.03%. The results also indicate that due to the lack of fluid-specific parameters, the application of this correlation may not support the development of new double effect VAR cycles. Therefore, it is crucial to establish a performance-based correlation that considers both operational parameters and fluid parameters to assess the performance of new and efficient dual effect VAR cycles.
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