Thermal hybrid power systems using multiple heat sources of different temperature: Thermodynamic analysis for Brayton cycles

Past studies on hybrid power cycles using multiple heat sources of different temperatures focused mainly on case studies and almost no general theory about this type of systems was developed. This paper is a study of their general thermodynamic performance, with comparison to their corresponding single temperature heat source reference system, focusing on the Brayton cycles: simple Brayton cycle, and Brayton cycle with intercooling, reheat and heat regeneration. The generalized expressions for the energy and exergy efficiency difference between the hybrid and the corresponding single heat source reference systems were developed, which allow easy determination of the extent of relative desirability of the hybrid systems in that respect. The design and operating conditions under which the hybrid systems become more efficient than the non-hybrid reference ones were found. A number of case studies were simulated (after validation) to help basic understanding and confirm the thermodynamic generalization of the results. One of the results showed that the largest exergy destruction occurs in the combustors (67% to total exergy destruction) and can be reduced by using additional heat sources (AHS) that are of lower temperature difference between the heating and heated streams, and/or renewable energy. The sensitivity analysis results further suggested that efforts should be made to increase the energy conversion efficiency of the AHS. The effects of AHS input and temperature on energy efficiency, fuel depletion and emissions were studied and compared with the conventional Brayton cycles. It was found that addition of the AHS, i.e. cycle hybridization, reduces emissions and fuel depletion and thus has an advantage over conventional non-hybrid Brayton cycles. A thermodynamic foundation of such hybrid systems was laid, and some easy guidance was provided for use in their preliminary design, before their highly time-consuming and expensive detailed analysis, simulation, and experiments.