Energy-conversion systems are optimized in three stages: synthesis (structure, configuration), design (operating characteristics at the rated load), and operation. The performance of energy systems, including the thermal efficiency, can be improved by increasing the complexity of the cycle configuration. Therefore, when two thermodynamic cycles are compared, they must be evaluated at the same level of their complexity. The SYNTHSEP methodology, which presents a general procedure to derive a complex thermodynamic cycle configuration operating with a pure working fluid, has been proposed in the literature. In this methodology, a cycle configuration is represented as a superimposition of elementary thermodynamic cycles (ETC), consisting of four basic processes (compression, heating, expansion, and cooling). This methodology has been formulated and codified for the derivation of candidate configurations, which are then narrowed down to the effective candidates. The complexity of the cycle configuration can be expressed by the number of elementary thermodynamic cycles. In previous works, the authors expanded the methodology to cover the absorption refrigeration cycle, which is also represented by superimposing elementary thermodynamic cycles operating with different working fluids. The purpose of this paper is to propose a revised methodology for configuration optimization that can be applied to any absorption cycle, including absorption power cycles, such as the Kalina cycle. The cycle complexity defined using a cycle simplicity index based on the number of ETCs and the number of mixing and splitting points of the ETC. The authors have derived candidate configurations for the simplest absorption cycle, defined by this index. Then, the proposed methodology for configuration optimization is demonstrated by performing a case study on an absorption power cycle and refrigeration cycle. Thus, designers can compare the configurations of absorption power and cooling or heating cycles with certified simplicity. This study establishes a methodology for configuration optimization and maximizes an objective function for an arbitrary absorption cycle. In principle, this methodology can also be applied to the absorption power and cooling cycle.
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