Designing an optimal energy recovery system has become a hot spot for energy management researches. The rapid expansion of growing industries and their high demand for green energy have made energy recovery of paramount importance to today’s companies. Recovering the wasted heat, which usually has a low temperature, by optimally converting it into other forms of energy like electrical energy is a subject of ongoing debates. The Organic Rankine Cycle (ORC) has been known as one of the most effective methods for the recovering process. When using an ORC for recovering wasted energy, an evaporator supplants the boiler and heats the working fluid. In the ORC an organic fluid used as the working fluid, which made the cycle capable of operating with low-temperature sources like biomass, geothermal, and solar energy. The cycle can be operated with industries’ wasted energy and converts it into mechanical work.
Demands for energy optimization have been urged since the early 1970s. It consists of three essential aspects, including energy, economic, and environmental efficiency. Industrial countries have made a vast fortune using energy optimization while preserving and improving environmental standards in the last decades. Nowadays, energy management and optimization perceive as a new source of energy. To optimize a system, its parameters and components should be optimally selected.
Many efforts have been made to optimize the ORC for different situations. Li et al., 2012 [
1] conducted an exergo-economic analysis along with condenser performance optimization for a binary mixture of vapors in the ORC system. They showed that with increasing the difference of the temperature ratios, the optimal number of transfer units decreases, leading to the heat capacity ratio rise [
1]. El-Emam and Dincer, 2013 [
2] optimized a geothermal ORC based on the heat exchanger’s total surface area parameter and performed an exergo-economic analysis of the system with the heat source temperature of 165◦ Celsius. They used Isobutane as the working fluid and reached the energy and exergy efficiency of 16.37% and 48.8, respectively [
2]. Khaljani et al., 2015 [
3] carried out an exergo-economic analysis of a combined gas turbine and an ORC. They found that an increase in the condenser temperature and Pinch point temperature difference can significantly decrease the first and second law efficiencies while increasing the total cost [
3]. Yari et al., 2015 [
4] performed an Exergo-economic comparison of trilateral power cycle (TPW), the Kalina cycle, and the ORC. They found Butane to be the most economically efficient gas when using the working fluid of both ORC and TPW. Yang et al., 2015 [
5] thermo-economically optimized a diesel engine waste heat recovery ORC system. They have found R245fa- also known as Pentafluoropropane- the most efficient working fluid used in a waste heat recovery ORC system [
5]. The same result was found in other researches [
6,
7]. Scardigno et al., 2016 [
8] examined the thermo-economic performances for an ORC fed by solar energy. They introduced heat exchangers as the most inefficient components of the system [
8]. Wang et al. 2016 [
9] conducted a geothermal ORC Multi-objective optimization along with grey relational analysis. They found the Pareto frontier as an effective way of comprehensively comparing ORCs [
9]. Nazari et al., 2016 [
10] carried out an exergo-economic multi-objective optimization of a combined steam-organic Rankine cycle. They revealed that the combined cycle with R152a has the best performance among R124, R152a, and R134a fluids [
10]. Zou et al., 2016 [
11] analyzed the performance of the partial evaporating ORC with zeotropic mixtures. They proposed a partial evaporating ORC with R245fa/R227ea, which can outperform the traditional subcritical ORC with R227ea by generating 24.7% more power [
11]. Wang et al., 2017 [
12] enhanced the performance of ORC with two-stage evaporation based on energy and exergy analysis. They have found that even though the two-stage evaporation improved the evaporation procedure, it deteriorated the condensation, pressurization, and expansion processes [
12]. Bufi et al., 2017 [
13] optimized ORC using both the single-objective genetic algorithm and the multi-objective Non-dominated sorting genetic algorithm II (NSGA-II). They found Toluene as a compelling choice for heat exchanger efficiency [
13]. Scardigno et al., 2015 [
14] used the multi-objective NSGAII optimization algorithm to find the hybrid organic Rankine plant for solar and lowgrade energy sources with the highest first and second law efficiencies and the lowest levelized energy cost. They found Cyclopropane as the most efficient working fluids, with a power output greater than 100 kW [
14].
In this research, we performed a thermo-economic optimization of ORC for the heat recovery of a sample power plant. As a mixture, working fluid is used, four possible thermodynamic models were considered. They were defined based on where the condenser and evaporator temperatures are located. Exergy efficiency and levelized energy cost values were calculated for every component of the system to investigate their relative role in system performance. To optimize the exergy and economic aspects of the system, a multi-objective Strength Pareto Evolutionary Algorithm II (SPEA II) [
15] was used, and Pareto frontier answers were ordered and chose by Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) [
16]. Four main thermal parameters, evaporator temperature, condenser temperature, degree of superheating and pinch point temperature difference, were taken as critical parameters. This paper is organized in the following order; first, detail explanations of the system are discussed. Then, the optimization algorithm is introduced, and after that, the results are analyzed.