**1. Introduction**

Energy is known to be one of the most important elements in the development of any society. In recent years, many researchers have conducted many studies to discover ways to reduce energy consumption in different sections. Studies on industries have shown that a grea<sup>t</sup> amount of waste heat is generated during various processes that are placed in low-temperature ranges. This waste heat, which is released to the ambience directly, in many cases, causes a lot of problems for the environment, such as thermal pollution, ozone depletion, air pollution and so on [1]. There are some suggestions to use low-temperature waste heats, but recovering by organic Rankine cycles (ORCs) to produce power is offered as one of the best ways to increase process efficiency [2–4]. In the last two decades, different systems of ORCs have been studied widely by researchers, and their focus are more on working fluids of cycles and optimizing performance conditions [5–9]. Biomass, solar thermal energy and geothermal are some other heat sources for ORC applications to produce electricity [10]. The energy conservation law is not sufficient by itself, so the second low should be considered to have a wide view to design systems [11]. Huan et al. [12] selected a regenerative organic Rankine cycle (RORC) to analyze energy and exergy aspects of cycles with six different working fluids. In their study, they optimized the exergy efficiency of the cycles to find the best condition ranges for the inlet pressure and temperature of the turbines. R141b and R11 are suggested as better working fluids for systems, and the maximum exergy of 56.87% was obtained for ORC with double regeneration (DRORC). In another study by Roy et al. [13], inlet temperature in turbines and superheat in RORC were optimized. It was observed that R123, as working fluid of the system, showed its best performance at 2.5 MPa pressure at the evaporator compared with R123a. In 2011, Rashidi et al. [14] have investigated optimizing RORC using artificial bee colony-based neural network method. Results indicated that, for RORC, there is an optimum range for bleed pressure to reach the maximum thermal and exergy e fficiency with the highest power output. If the pressure goes above or below this range, the thermal performance of the system will ge<sup>t</sup> worse.

As it is seen, most studies consider a conventional exergy analysis for ORCs. A conventional exergy analysis can just evaluate the performance of system components separately to find the component with the highest exergy destruction. This method does not show the share of each component of a system on other components' exergy loss. An advanced analysis divides exergy loss into unavoidable and avoidable and exogenous and endogenous for each component. By this analysis, the potential of each component is observed and discussed to improve its e fficiency [15]. Conventional and advanced exergy analysis for gas turbines in di fferent systems has been applied by Fallah et al. [16]. Among those systems, gas turbines with evaporative inlet air cooling have the best potential to reduce their destruction. It was also concluded that, when using an advanced exergy analysis, working conditions obtained by optimization for inlet cooling components were di fferent from those obtained by a conventional exergy analysis. Galindo et al. [17] had discussed conventional and advanced exergy analysis in ORC as a bottoming cycle in an internal combustion (IC) engine in 2016. They indicated that boilers have the highest exergy destruction, but turbines have grea<sup>t</sup> potentials to improve their e fficiency. Additionally, they suggested that about 36.5% of exergy loss in a system can be reduced by only the avoidable part of exergy loss in each component. Nami et al. [18], in 2017, worked on a binary fluid organic Rankine cycle with conventional and advanced exergy analysis. In this system, the low-pressure vapor generator (LPVG) has the highest exergy destruction among the components. Additionally, the advanced exergy analysis results showed that 15% of the condenser exergy destruction is placed in avoidable parts, which consists of 7% of the whole avoidable exergy destruction rate of the system. In addition, their study shows that, from an advanced exergy analysis view, more than 70% of total exergy destruction of the system is placed in endogenous exergy destruction parts, and among all the parts of the system, the endogenous exergy destruction is higher than the exogenous exergy destruction.

By studying many papers, it was observed that RORC has a really grea<sup>t</sup> e fficiency and a potential to recover heat from low-temperature heat sources. RORC has been investigated by energy and exergy analysis, and the system was also studied from economics aspects [19–22]. To the best of the authors' knowledge, and by reviewing many papers, there is no study which has applied advanced exergy analysis to RORC for recovering low-temperature waste heat.

Therefore, the present study attempts to explain the system conditions, the first and the second law of thermodynamics and then to model our systems. Three cycles (BORC, single-regeneration ORC (SRORC) and DRORC) are selected to do the analysis. Then, the advanced exergy analysis aspects and their applications in the cycles are discussed. It is then followed by analyzing and discussing the results about the potential of each component to find and sugges<sup>t</sup> some ways of decreasing the total exergy destruction rate in order to have the best design.
