Abstract
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%.
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