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On the suitable superstructure thermoeconomic optimization of a waste heat recovery system for a Brazilian diesel engine power plant

机译：关于巴西柴油机发电厂废热回收系统的合适超结构热经济优化

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摘要

Brazilian thermal power plants were designed to operate as peaking plants. The diesel engine power plants in Brazil eliminate copious amounts of residual heat through cooling water and exhaust gases. The current scenario has led to an increase in the operational times of the plants. An attractive solution for increasing power and efficiency in this situation is waste heat recovery (WHR). A variety of technologies and configurations can be used for WHR. The selection of the best WHR system is not a simple task, and the solution should not be generalized for different applications. In this work, a superstructure method is used for structural and parametric thermoeconomic optimization, selecting the best WHR for a Brazilian diesel engine power plant operating scenario. Three technologies are considered: the conventional Rankine cycle (CRC), the organic Rankine cycle (ORC), and the Kalina cycle (KC). The thermoeconomic models were developed using Engineering Equation Solver software, and the optimizations were carried out using the genetic algorithm toolbox. Due to the specificity of the Brazilian scenario, the maximization of the gross profit rate function was the selected objective, allowing for the evaluation of 16 combinations of annual dispatch hours and variable unit cost of electricity. The results showed that, although different optimal structures and parameters can be obtained through optimizations, depending on the combinations of annual dispatch and unit cost of electricity, ORC has the highest gross profit rate and is always the best alternative. For an optimistic scenario of dispatch and variable unit cost of electricity, ORC produces up to 14.3 MW of net power, increasing the installed capacity of the 20 generator sets up to 8.2%.
机译：巴西热电厂设计为峰值植物。巴西的柴油发动机电厂通过冷却水和废气消除了大量的残留热量。目前的情景导致植物的操作时间增加。在这种情况下增加功率和效率的有吸引力的解决方案是浪费热回收（WHR）。可以使用各种技术和配置。选择最佳WHR系统不是一个简单的任务，并且解决方案不应推广不同的应用程序。在这项工作中，超大结构方法用于结构和参数热经济优化，选择最佳WHR用于巴西柴油发动机电厂操作场景。考虑了三种技术：传统的兰氏素循环（CRC），有机兰氨酸循环（ORC）和Kalina循环（KC）。使用工程方程求解器软件开发了热经济模型，并且使用遗传算法工具箱进行了优化。由于巴西情景的特殊性，毛利率函数的最大化是选定的目标，允许评估16个年度派遣时间和可变单位电力成本的16种组合。结果表明，尽管可以通过优化获得不同的最佳结构和参数，但根据年度派遣的组合和电力单位成本，ORC具有最高的毛利率，并且始终是最佳选择。对于乐观的调度和可变单元的电力成本，ORC产生高达14.3兆瓦的净功率，增加20个发电机的装机容量高达8.2％。

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