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    基于MOGWO算法的有机朗肯循环多目标优化

    Multi-objective Optimization of an Organic Rankine Cycle Based on MOGWO Algorithm

    • 摘要: 为提高有机朗肯循环的综合性能,从热经济学和经济学出发,以单位输出功率的系统总投资成本和系统产品单价为目标函数构建多目标优化模型。针对423.15 K低温烟气热源,选取R245fa、R123、R114、R245ca、R601、环己烷、丁烷和R236ea为待选工质。引入MOGWO对多目标模型进行求解,采用一维向心透平效率预测模型分析了透平效率随蒸发温度和冷凝温度的变化。结果表明:各工质的透平效率随蒸发温度升高而降低,随冷凝温度升高而提高;所选工质中R601是最优工质。

       

      Abstract: To improve the overall performance of an organic Rankine cycle, a multi-objective optimization model was established from the perspectives of thermoeconomics and exergoeconomics by taking the total investment per unit power output and the cost per unit exergy of the system as the performance indicators. For the 423.15 K low temperature flue gas waste heat source, the R245fa, R123, R114, R245ca, R601, cyclohexane, butane, and R236ea were chosen as the candidate working fluids. The model established was solved using the multi-objective gray wolf algorithm (MOGWO), while the effects of evaporation temperature and condensation temperature on the turbine efficiency were analyzed with a one-dimensional radial-inflow turbine efficiency prediction model. Results show that, for all the working fluids, the turbine efficiency reduces with the rise of evaporation temperature, but increases with the rise of condensation temperature. Among the working mediums selected, R601 is the optimal working fluid.

       

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