Potential for energy recovery from internal combustion engines driving electrical generators in Iraq cities

ABSTRACT Distributed power generation may become an important segment in the energy sector in Iraq. The main objective of this paper is to estimate the potential of heat recovery from the Internal Combustion Engines (ICE) driving electric generators in Iraq. The heat recovery solution considered here is based on Organic Rankine Cycles (ORCs). A model has been developed for an ORC-based system recovering heat from a small/medium size ICE (37.7 kW), which is appropriate for large-scale implementation in Iraq. The model has been validated against results reported in the literature. The main steps of the procedure used to design an ORC-based system are presented, with proper illustrations. They include working fluid selection, performance analysis for each component of the system (evaporator, condenser, and expander) and sizing the main components of the system (evaporator and condenser). The heat recovery efficiency is higher in the North of Iraq and ranges between 8% and 11% in January and between 4% and 7% in July, depending on working fluid and geographical location. R134a provides the highest efficiency, while the second-best working fluid is R1234ze. We adopted the hypothesis that 20% of the power capacity to be installed in Iraq until 2020 is provided by electric generators driven by ICEs of medium power (37 kW). 125000 units should be installed and the investment is about 1.5 billion Euro while heat recovery units may cost about 500 million euro, if manufactured in dedicated factories. Heat recovery may save about 7.5% of the installed power. The government should prepare appropriate policies to stimulate distributed power generation and heat recovery.


Introduction
Iraq is a medium-size country, with about 40 million people. Most part of Iraq's electricity is generated by fossil fuel sources. Power is traditionally produced by thermal plants that burn crude oil and were built in the 1970s and 1980s (Al Jazeera 2018). The current thirst for electricity far outstrips the supply. The supply is highly dependent on location. From 1980 until now, the Iraqi government provided electricity to the population for 8-12 h as an average per day. The largest energy demand is in the summer when the air temperature may reach 55°C and air conditioning is necessary. A new segment appeared after 2003 on the energy market, when investors start installing large electric generators with a capacity of 1-2 MW to sell electricity to the population. In 2014, the number of electric generators was about 32000 units that produced 9216 MWh of electricity (Kamel 2012). As a result, the Iraqi government has enacted laws governing the management of these large generators. However, the large electric generators solved only in part the electricity crisis (Al-Khatteeb and Istepanian 2015;Istepanian 2014). Locals started to rely on small home or neighborhood diesel-powered electric generators to meet their needs (Rudaw 2018). This solution of distributed electricity generation is appropriate for Iraq, a country with large fossil fuel reserves. In 2014 the electricity generation mix consists of gas-turbine generation (around 48%), along with thermal plants relying on fuel oil, crude oil, refined gasoline (30%), and some limited hydroelectric capacity from the country's eight dams (14%), with remaining generation handled by small diesel generators (Ministry of Electricity 2014). However, in 2017 the installed power was about 8430 MW (Ministry of Electricity 2018a) while the Iraq System's need was about 13530 MW (Electricity 2018).
Small or medium-size electric generators are usually driven by Internal Combustion Engines (ICEs). It is known, however, that heat engines have large thermal wastes and heat recovery is important (Chinnapandian et al. 2015;Haşimoğlu 2012;Jana and De 2016). For large systems, more than 1 MW, recovery of waste heat from thermal engines has been already implemented in Europe (Turboden 2018). For small systems, several studies have been published (see, e.g., Fu, Lee, and Hsieh 2015;Guopeng et al. 2013) but further work is needed. Since distributed power generation increased significantly in the last decade in Iraq, heat recovery should be carefully considered.
In this paper, we deal with heat recovery systems from thermal engines operating under the climate, geographical and social conditions of Iraq. We focus on the design and performance analysis of heat recovery systems for heat engines of small/medium power (e.g., tens of kW), useful for private citizens or small communities. Since the temperatures involved are not large, the heat recovery solution proposed here is based on Organic Rankine Cycles (ORCs).
The paper is tutorial in nature and several ways of recovering heat by using ORC-based systems are shortly analyzed. The ORC system design procedure consists of three steps. The first step is the selection of the working fluid, which is closely related to environmental aspects. For instance, three working fluids (namely, R11, Benzene, and R134a) have been analyzed in Iacopo and Agostino (2010). These fluids are not in the best position from the point of view of the Ozone Depletion Potential (ODP) and Global Warming Potential (GWP). One working fluid (R245fa) has been analyzed by Qiu (2012) while in (Shu et al. 2014) six fluids have been considered (R124, R134a, R245fa, R600, R600a, and R1234yf, respectively). Ten working fluids are considered here, some of them with very good thermal properties, others with excellent ODP and GWP features. This provides a better perspective on the thermal performance and environmental protection. The second step includes an irreversibility analysis and shows the components where a careful design is needed. The third step consists of sizing the main components. In distributed power generation the electricity is generated at consumer request. This means that there are periods of time when the heat generation systems (i.e., the ICEs) do not operate at full load. This case has been analyzed by Badescu et al. (2017) (where a solution has been proposed to optimize the ORC-based system operation through the variation of the working fluid mass flow rate) but is not considered here.
The paper is organized as follows: In Section 2, the model is shortly presented, while the ORC-based heat recovery system proposed for implementation in Iraq is described and analyzed in Section 3. Section 4 deals with the potential of heat recovery in Iraq. Section 5 contains the conclusions. Detailed information may be found in the Electronic Supplementary Material (ESM).

Model
The ICE considered in this work is a 4-stroke, 4-cylinder ICE that drives an electric generator for which the main technical data for full operation load are presented in Table 1. Full load means that the electric generator is operating at full capacity (the electricity demand is 36 kWe) that implies full load operation of the ICE (about 37.7 kW). This small/medium size ICE is appropriate for large-scale implementation in Iraq. The task is to recover heat from the flue gas released by this ICE.

Specific scheme of ORC-based system
Several schemes of ORC-based systems for heat recovery from ICEs are of interest and can be implemented in practice (Apostol et al. 2015). One of them is proposed here for possible implementation in Iraq. It involves only the recovery of heat from flue gas and requires a smaller amount of investments, which may be an important criterion when implemented in Iraq. This configuration has been analyzed by Badescu et al. (2017). For the interested reader, details are presented in Section S1 of the ESM.
The model of the ORC-based system has been developed in (Badescu et al. 2017) and is structured into several sub-models ( Figure 1). It is based on balance mass and energy equations for all system components (evaporator, expander, condenser, and pump). Appropriate heat transfer relationships are used for these components and performance indicators are defined. For the interested reader, some details about the model are presented in Sections S3 to S5 of the ESM. The assumptions adopted are as follows: (i) negligible heat loss in pipes and equipment; (ii) negligible pressure drops in pipes and equipment; (iii) flue gas is non-condensable; (iv) steady-state operation.
The thermodynamic cycle of the ORC-based system configuration of Figure 1 is presented in Figure 2 for an isentropic fluid.
The model is implemented in the Engineering Equation Solver (EES) environment according to the flow chart described in Figure 3 and it corresponds to the design of an ORC-based system for a given type of heat source.

Model validation
The results obtained by using the EES code have been validated against results obtained in (Iacopo et al. 2010) and (Hua et al. 2012). Those papers refer to waste heat recovery from ICE by means of ORC-based systems. The present code has been run by using input data corresponding to (Hua et al. 2012) and the results are presented in Table 2 for R245fa and R134a as working fluids of the ORC-based system. The input data used are: flue gas composition in terms of mass fractionsm CO2 ¼ 15:10 %, m H2O ¼ 5:37 %, m N2 ¼ 73:04 %, m O2 ¼ 6:49 %, temperature of the flue gas at the evaporator inlet T 5 ¼ 792:15 K, temperature of the flue gas at the evaporator outlet (under the condition of avoiding condensation) T 6 ¼ 393:15 K, flue gas mass flow rate _ m g ¼ 990:79 kg=h, temperature of the ORC-based system working fluid at the expander inlet T 3 ¼ 523:15 K, evaporating pressure p evap ¼ 3000 kPa, condensing temperature T con ¼ 308:15 K, expander efficiency η exp ¼ 0:7, pump efficiency η p ¼ 0:8. The quantities listed in Table 2 are: thermal efficiency of the ORC-based system η th;ORC À ½ , expansion ratio v 4r =v 3 À ½ and total heat transfer area (evaporator plus condenser) per net output power of the ORC-based system A tot P net;ORC m 2 =kW ½ . In (Hua et al. 2012), both evaporator and condenser are plate type heat exchangers while in the present work, a counter-flow double-pipe type of heat exchanger is considered. Details about the geometry of the heat exchangers considered in the present work can be found in (Badescu et al. 2017). In this situation, even if the equations that are used to compute the heat transfer coefficients are different, the value obtained for the total heat transfer area per net output power can be used to validate the results obtained in the present work for the heat transfer areas of evaporator and condenser. Table 2 shows good agreement between the results obtained in the present work and the results of (Hua et al. 2012) for both working fluids.
The results obtained in the present work have been compared with results presented in (Hua et al. 2012) and (Iacopo et al. 2010) for benzene and R134a as working fluids (see Table 3). The input data are: flue gas composition in terms of mass fractionsm CO2 ¼ 9:1 %, m H2O ¼ 7:4 %, m N2 ¼ 74:2 %, m O2 ¼ 9:3 %, temperature of the flue gas at the evaporator inlet T 5 ¼ 743:15 K, temperature of the flue gas at the evaporator outlet (form the condition of avoiding condensation) T 6 ¼ 393:15 K, flue gas mass flow rate _ m g ¼ 15673 kg=h, temperature of the ORC-based system working fluid at the expander inlet has been considered T 3 ¼ 494:7 Kin case of benzene and T 3 ¼ 374:9 K in case of R134a, evaporating pressure p evap ¼ 2000 kPain case of benzene and p evap ¼ 3723:4 kPain case of R134a, as reported in (Iacopo et al. 2010), expander efficiency η exp ¼ 0:7, pump efficiency η p ¼ 0:8. The results presented in Table 3 for the present work have been obtained under the constraints of a minimum superheating increment ΔT sp ¼ 0:1 Kin case of benzene and ΔT sp ¼ 5 Kin case of R134a. These superheating increments have been imposed in order to ensure the operation of the code as described in Figure 3. The quantities listed in Table 3 are: net output power of the ORC-based system P net;ORC kW ½ , thermal efficiency of the ORC-based  system η th;ORC À ½ , condensing pressure p con kPa ½ , evaporating pressure p evap kPa ½ , evaporating temperature T evap K ½ , ORC-based system working fluid mass flow rate _ m ref kg=s ½ , ORC-based system working fluid flow rate (at the expander inlet) _ V ref m 3 =s ½ , expansion ratio v 4r =v 3 À ½ and Δh 3À4r kJ=kg ½ . Table 3 shows good agreement for both working fluids between the results obtained in the present work, on one hand, and those of (Hua et al. 2012) and (Iacopo and Agostino 2010), on the other hand. The differences between the two sets of results can be explained as follows: (i) In (Hua et al. 2012) the EES database of working fluid properties is used; also in (Iacopo and Agostino 2010) the REFPROP database of properties is used; in the present work, the EES database of properties is used.
(ii) In the present work, a minimum superheating increment has been considered, which enables the use of the computer code flow chart presented in Figure 3.

Uncertainty analysis
Most results presented in this paper refer to the efficiency η th;ORC . The uncertainty U η th;ORC of these results depends on the uncertainties U p i of the parameters p i upon which η th;ORC depend. U η th;ORC may be evaluated by the square root of the variance of the statistical distributions of each parameter (see, e.g., Coleman and Steele 1995): where n is the total number of parameters.

Selection of working fluid
Selection of the working fluid in the ORC-base system is an important step. Optimization must be performed for each ORC configuration since the optimal working conditions are closely linked to the working fluid. For the present study the following working fluids have been considered: R134a, R236fa, R245fa from the hydrofluorocarbons (HFCs) group (Jacopo, Manente, and Lazzaretto 2015;Zhang et al. 2016), R1234yf and R1234ze (R1234ze[E] in the EES database) from the hydrofluoroolefines (HFOs) group (Jacopo, Manente, and Lazzaretto 2015), R290 (propane), R600 (butane), R600a (isobutane), pentane, hexane, benzene and toluene from the hydrocarbons (HCs) group (Jacopo, Manente, and Lazzaretto 2015;Zhang et al. 2016), RC318 from the perfluorocarbons (PFCs) group (Jacopo, Manente, and Lazzaretto 2015) and HFE7100 and HFE7500 from the hydrofluoroethers (HFEs) group (Jacopo, Manente, and Lazzaretto 2015). Four selection criteria have been used: environmental, safety, technical and economical. The most suitable fluids are R134a (wet fluid), R1234ze and R1234yf (isentropic fluids). Further details about the working fluid selection are presented in Section S5.9 of the ESM.

Design details
The design of the ORC-based system is related to the geometry of the evaporator and condenser in correlation with the maximum net output power for a given type of heat source, which in this case is  the flue gas from an ICE that drives an electric generator. The selection of the proper pump and expander is also important but it is not under discussion in the present work. The design of the ORC-based system corresponds to the full load operation of the electric generator, which in turn involves full load operation of the ICE. The design of the ORC-based system is performed by using the computer code developed in EES software (see Figure 3) and obeys the following conditions: • steady-state operation of the electric generator and ORC-based system; • ambient temperature is 293 K; • the pinch point temperature in the condenser is 15 K; • the pressure losses and the heat rejected to surroundings at the evaporator and condenser level are not taken into consideration; • the water inlet temperature in the condenser of the ORC-based system (state 7 in Figure 2) is 293 K; • the water outlet temperature in the condenser of the ORC-based system (state 8 in Figure 2) is 300 K; • the temperature of the exhaust gas at the outlet of the evaporator of the ORC-based system is limited to 413 K in order to avoid acid corrosion; • the flue gas composition in term of mass fractions is considered to be m CO2 ¼ 9:1 %, For full load operation of the electric generator, the temperature of the flue gas at the inlet of the ORC-based system evaporator is T 5 ¼ 743 K and the flue gas mass flow rate is _ m g ¼ 192 kg=h. These values are obtained experimentally in Badescu et al. (2017).
Before designing the evaporator and condenser of the ORC system, in terms of computing the heat transfer areas, the optimum operation conditions must be determined for the specified heat source. To do so, an analysis regarding the influence of the superheating degree and evaporating temperature on the net output power of the ORC-based system and on the exergy destruction is needed. To save space, results are shown in Section 5.8 of the ESM.
The design of the ORC-based system is performed according to the optimum operation conditions. The design mainly involves computation of the heat transfer areas for the evaporator and condenser, as well as their corresponding lengths. These values are presented in Table 4. Nevertheless, other important operation parameters are of interest as presented in Tables 5 and 6.  Table 4 shows the main operation parameters of the ORC-based system for the three working fluids considering the optimum operation conditions determined previously. For the same evaporating temperature, the highest evaporating pressure of the ORC-based system is obtained in case of R134a, followed by R1234yf and R1234ze. The highest optimum value of the superheating increment corresponds to R134a, followed by R1234yf and R1234ze. Also, for the same heat flux transferred in the evaporator, the highest value of the mass flow rate is obtained in case of R1234yf, followed by R1234ze and R134a. The highest thermal efficiency of the ORC-based system is obtained when it operates with R134a, followed by R1234ze and R1234yf. For all three working fluids, the heat flux released in the condenser has similar values, which in turn lead to very close values for the cooling fluid (water) mass flow rate.
The results reported by Seyedali, Saeed, and Krishna (2017) are obtained for an ICE that operates with natural gas. Even if the fuel is different from the one considered in the present work and the operation conditions are different, the values of the exhaust gas temperature are similar to those obtained in the present paper. Those authors show that when using R134a as working fluid the thermal efficiency of the ORC-based system is 8.7%, as indicated in Table 7. The thermal efficiency obtained in the present work, for the same working fluid, is 8.6% (see Table 4). Therefore, the results obtained in the two papers are in very good agreement. Table 5 shows the heat fluxes absorbed at the evaporator and released at the condenser, for the three working fluids. In the case of the evaporator, the heat fluxes absorbed in the preheating, boiling and superheating processes, respectively, are different for the three working fluids. In case of R134a, the distribution of the absorbed heat flux is 37% in the superheating process, 30% in the boiling process and 33% in the preheating process. In case of R1234ze, 25% of the heat flux is absorbed in the superheating process, 39% in the boiling process and 36% in the preheating process. For R1234yf, 33% of the heat flux is absorbed in the superheating process, 24% in the boiling process and 43% in the preheating process. In the case of the condenser, for all three fluids, the heat flux released in the condensation process is considerably higher than the heat flux released in the desuperheating process. In case of R134a, 66% of the total heat flux is released in the condensation process and 0.34% in the desuperheating process. For R1234ze, 73% of the total heat flux is released in the condensation process and 0.27% in the desuperheating process. In case of R1234yf, 69% of the total heat flux is released in the condensation process and 0.31% in the desuperheating process. Table 6 shows the overall heat transfer coefficients, heat transfer areas and lengths for the evaporator and condenser. For all three fluids, the overall heat transfer coefficient in the boiler zone is higher than the overall heat transfer coefficient in the superheating zone, which is higher than the overall heat transfer coefficient in the preheater zone. Also, for all three fluids, the values of the corresponding overall heat transfer coefficient are close to each other. At the condenser level, for all three fluids, the value of overall heat transfer coefficient in the desuperheater zone is roughly 50% smaller than the overall heat transfer coefficient in the condensation zone. Also, there is a noticeable difference between the corresponding overall heat transfer coefficients for the three fluids. The preheater heat transfer area has the highest value for all three fluids and it covers 51% in case of R134a, 56% in case of R1234ze and 62% in case of R1234yf, of the corresponding total heat transfer area of the evaporator. The heat transfer area of the boiling zone in case of R134a and R1234yf is smaller than the heat transfer area of the superheating zone, while in case of R1234ze it is higher. For R134a, the heat transfer area of the boiling zone represents 24%, in case of R1234ze 29%, and in case of R1234yf 18%, of the total heat transfer area of the evaporator. Regarding the heat transfer area of the superheating zone, it represents 25% in case of R134a, 15% for R1234ze and 20% in case of R1234yf, from the total heat transfer area of the evaporator. At the condenser level, for all three fluids, the heat transfer area of the desuperheater zone is considerably smaller than the heat transfer area of the condensation zone.
In case of R134a, the desuperheating zone represents 27%, 26% in case of R1234ze and 35% in case of R1234yf, from the total heat transfer area of the condenser. Also, for all three fluids, the evaporator length is considerably smaller than the length of the condenser. The model developed in the present work has been used under the conditions presented in (Shan et al. 2019). Those authors used R245fa as the working fluid. The heat transfer area of the evaporator obtained with the present model is 4.637 m 2 . This has to be compared with 2.38 m 2 from Table 7 of Shan et al. (2019). The heat transfer area of the condenser obtained with the present model is 4.732 m 2 , compared with 6.48 m 2 from Table 7 of Shan et al. (2019). Therefore, the heat transfer areas of the evaporator and condenser obtained by Shan et al. (2019) and by us are comparable in size. The difference between the two sets of values comes from the fact that the diameters of the counter-flow double-pipe type of heat exchangers are different in the two works (for the values used in the present work see Section 3).

Potential for heat recovery from ICE driving electric generators in Iraq cities
Because of power shortage in Iraq, private small and medium-size diesel generator sets are now used to supply houses with power. There is a good potential for this distributed power generation solution since the expected power demand is largely exceeding the power supplied by the government. Usage of ICEs for driving electric generators is expected to increase and heat recovery from these thermal engines may become an important issue in the next years.
The procedure developed in Section 2 has been used to estimate the potential of heat recovery from ICE units in Iraq. The performance of the heat recovery systems depends on the cold reservoir temperature. Since the cooling water of the ICEs is commonly cooled by using radiators transferring heat toward the ambient, here we assume that the cold reservoir temperature is the atmospheric temperature. Three major cities of Iraq have been selected to cover the territory of the country: Mosul (North of Iraq), Baghdad (center of Iraq) and Basra (South of Iraq), respectively. Tables S13,  S14, and S15 in the ESM provide information about the multi-year averages of mean, minimum and maximum air temperature in the three cities. ORC-based systems have been designed to operate in the three selected cities. The optimization procedure proposed in (Badescu et al. 2017) (also, see Section S2 of the ESM) has been used and three refrigerants have been considered: R1234yf, R1234ze and R134a. The operation of the heat recovery systems has been analyzed for all months of the year in the three cities. Table 7 shows the results concerning the heat recovery efficiency of the ORCbased system in Mosul. Similar tables may be found in Section S6 of the ESM for Baghdad (Table S16) and Basra (Table S17).
The efficiency η th,ORC is higher in the winter months, as expected, since the air temperature is lower in those months. In January, the efficiency ranges between about 8% and 11%, depending on working fluid and air temperature. July is the month with the smaller value of η th,ORC . This applies for all working fluids. In this month, the efficiency ranges between about 4% and 7%, as a function of air temperature and working fluid. R134a is the working fluid associated with the highest efficiency, in all months of the year, followed by R1234ze. Depending on the air temperature, the efficiency η th,ORC may change by about two percent, in a given month. This can be seen by comparing the values of η th,ORC for the minimum and maximum air temperature in Table 7.
It is convenient to use as a first performance indicator the value of the efficiency η th;ORC associated with the mean ambient temperature. The uncertainty U η th;ORC of this value is estimated by using the results of Table 7. Since just the influence of the air ambient temperature is considered in Equation (1), n = 1 and p i ¼ T amb . The procedure is as follows: First the difference Δη th;ORC between the η th;ORC values for the minimum ambient temperature T min and the maximum ambient temperature T max , respectively, is computed for every month in Table 7. Also, the difference ΔT amb ¼ T min T max is evaluated for every month. Next, the ratio Δη th;ORC =ΔT amb is evaluated, as an approximation for the derivative in Equation (1). The uncertainties in the values of T amb to be used in Equation (1) are simply approximated by T mean T min (for overestimation) and T mean T max (for underestimation). The uncertainty U η th;ORC is shown in Table 8 for three working fluids in Mosul city. Both underestimation and overestimation values are shown.
Generally, Table 8 shows the underestimation of η th;ORC is larger in the summer months, for all fluids while the overestimation of η th;ORC has a smoother variation during the year, with larger values in the summer and autumn.
The yearly average values of the efficiency η th,ORC of the ORC-based heat recovery systems are shown in Table 9, for three working fluids. Daily mean, minimum and maximum values of air temperature have been considered as input. These input values have been computed as averages of the monthly values in Table 7, S16 and S17.
The model developed in the present work has been run under the conditions described in Iacopo and Agostino (2010). Special care has been granted to the value of the condensing pressure, which has been adapted to match the situation presented in Table 7 for the month of March. For this particular case, the thermal efficiency of the ORC-based system obtained with the present model is 0.0856, which has to be compared with 0.0852 shown in Table 2 of (Iacopo and Agostino 2010). The two results are in very good agreement.
The yearly average values of the efficiency η th,ORC is generally the highest at Mosul, which is located in the North of the country, and the lowest in the Southern city of Basra. Generally, the yearly averaged efficiency ranges between about 6% and 9%, for all cities, all temperatures and all working fluids. R134a is the working fluid providing the highest efficiency in all cities. The second best working fluid is R1234ze. The difference in efficiency between the three working fluids is less than 1%, in all cities and for all temperatures. This shows that any of the three working fluids may be used in practice. Choosing among these fluids depends on the design or economical aspects.
The values in Table 9 are affected by uncertainties when used during different months. It is conservative to consider the extreme values of the underestimation and overestimation of η th,ORC in Table 8 . For instance, the results in the first row of Table 9 for Mosul city may be lower or larger, as follows: by -1.33% to 1.33% for R1234yf, by -1.40% to 1.38% for R1234ze and by -1.45% to 1.43% for R134a.
The yearly averaged heat recovery efficiency η th,ORC in Table 9 is higher than 7% for all working fluids and towns. This is not a negligible amount and a perspective is obtained when looking at the level of the whole country. Table S18 in the ESM shows the values of the yearly averaged values of the heat recovery efficiency η th,ORC in major cities of Iraq. Since the heat recovery efficiency depends on the climate conditions, the following procedure has been adopted when preparing Table S18. For the Northern towns Mosul, Sulaymaniyah, Arbil, Dahuk and Kirkuk, the heat recovery efficiency values obtained for Mosul have been used. The values η th,ORC obtained at Baghdad have been used for the following cities in the middle of the country: Baghdad, Karbala, Najaf, Ar -Ramadi, Baquba, Kut, Al-Hillah, Samawah, Tikrit, and Al-Diwaniya, while for the Southern cities Basra, Nasiriyah, and Amarah, we used the values  Table S18 and three working fluids have been considered. Note that the year 2018 population in Table S18 is a rough estimation since in some cases it corresponds to the governorate rather than the capital city (World Population Review 2018). Figure 4 shows the distribution of the heat recovery efficiency η th,ORC over the territory of the country, for working fluid R134a. The mean yearly average air temperature has been considered. In this case, the differences between the efficiency values in the Iraq cities are less than 1%. There is a slight increase in the efficiency values when going from the South to the North of the country, as expected. Figures S62 to S69 in the ESM show the heat recovery efficiency η th,ORC in major towns of Iraq, for working fluid R134a, R1234yf, and R1234ze and yearly averaged values of mean, minimum, and maximum air temperature used as input.
The values in Figure 4 are affected by uncertainties when used during different months. In the first approximation, one may use for all towns in Figure 4 the results obtained for Mosul city for refrigerant R134a (see Table 8). Therefore, the values in Figure 4 may be lower or larger by -1.45% to 1.43%.
Table S19 in the ESM shows the necessary installed power in 2020 for the Iraq governorates (Ministry of Electricity 2018b). Assume that 20% of the necessary installed power is covered by distributed power generation by using electric generators (EGs) driven by ICEs. Table S19 shows the estimated installed power by using EGs in this quite reasonable scenario. Figure 5 shows the distribution over the Iraq territory of the necessary installed power which is to be covered by distributed power generation by using electric generators (EGs) driven by ICEs. The necessary number of ICE units is easy computed taking into account the power of one ICE unit (37 kW). Distributed power generation may constitute a good solution since the major towns are relatively uniformly distributed over the country. This may ensure a more uniform coverage of the electricity demand, taking into account the fact that the structure of high voltage electric grid is quite rigid, being dependent on the place of the major power plants in the country.
Table S18 in the ESM shows the population of the major Iraq towns. The number of families in each town is obtained by taking into account that the average family in Iraq consists of five persons. For instance, the necessary number of ICE units to be implemented in Baghdad (40076) (see Figure 5) and the population of that city is 7,216,000. Hence, the number of families in Baghdad is about 1,443,200. If each newly installed ICE unit will be own by one family, the percentage of families owning newly installed ICE units in Baghdad is 2.78% and similar values are expected to apply for the other towns. This is a reasonably small percentage, showing that an appropriate government policy favoring the implementation of ICE units may find a good response among the category of wealthy people.
Previous experience of the authors shows that an estimated cost of the unit consisting of an Internal Combustion Engine and Electric Generator is about 12000 Euro, while the cost of a factory-manufactured ORC-based system may range about 4000 Euro (for details see Section S1 in the ESM). The total Installed Power Provided by newly installed ICE units is 4631.2 MW and the total number of ICE units is 125168 (see Table S19 in ESM). Therefore, at the level of the whole country, the investments in the generators and ICE units are about 1.5 billion Euro while the cost of the attached heat recovery systems based on ORC may be about 500 million Euro. Part of these investments may be covered by the government through direct methods or dedicated regulations. The heat recovery efficiency η th,ORC is higher than 7.5% for all working fluids and towns (see Figure 4). This is not a negligible amount and a perspective is obtained when looking at the level of the whole country. The total Installed Power Provided by ICE units of 4631.2 MW is decreased if ORC-based heat recovery systems are used. The saved ICE installed power may be evaluated by multiplying the installed power provided by the heat recovery efficiency η th,ORC (7.5%, say) and this gives the amount of saved installed power: 347.3 MW, which is the equivalent of 9387 ICE units operating without heat recovery. This exceeds the number of ICE units to be installed in most major cities of Iraq, except Baghdad, Mosul, and Basra (see Figure 5). Heat recovery is indeed effective in terms of economic and social consequences.

Conclusions
The power plants in Iraq provide about a half of the power need. There is a growing tendency by citizens and communities to rely on electric generators driven by Internal Combustion Engines (ICEs). Therefore, distributed power generation may become an important segment in the energy sector in Iraq in the next years. Heat engines operation is associated with significant thermal losses and heat recovery is a necessary tool in modern energy policy. The main objective here is to give perspectives for the potential of heat recovery from the ICEs driving electric generators in Iraq. The focus is on heat engines of small and medium power, which are appropriate to operate for private owners and small communities. The heat recovery solution considered here is based on Organic Rankine Cycles (ORCs), which became very popular in the last years.
The number of electric generators installed in Iraq is of the order of tens of thousands. The heat released by the ICEs driving these generators is huge. The main novelty of this work is that it provides a first estimate of the amount of potential heat recovered from these ICEs at the level of the whole country. Also, how this recovered heat is used to generate work, and which is the effectiveness of the process of work production, is shown here for the first time.
A model has been developed for the ORC-based system operation. The model has been applied to a small size ICE (37.7 kW), which is appropriate for large-scale implementation in Iraq. Good agreement with results reported in the literature has been found. The main steps of the procedure used to design an ORC-based system are presented, with proper exemplification for easy practical implementation. The first step is the selection of working fluid. Several criteria have been used and 3 of the 10 fluids on the initial list have been selected for further consideration: R1234yf, R1234ze, and R134a. The performance evaluation and irreversibility analysis are performed in the second step. This includes the evaluation of the exergy destruction for each component of the system (evaporator, condenser, expander). The third step consists of sizing the main components of the system, which are the evaporator and the condenser.
The model developed here provides results in good agreement with previous findings in the literature. For instance, for a specific case, the thermal efficiency of the ORC-based system, η th,ORC , considered by Seyedali, Saeed, and Krishna (2017) is 8.7% while the result obtained here for the same case is 8.6%. Also, the value of η th,ORC obtained here is 8.56%, which is invery good concordance with the value 8.52% obtained by Iacopo and Agostino (2010) in a similar situation. Finally, the heat transfer areas of the evaporator and condenser obtained by Shan et al. (2019) are rather similar in size with those obtained in this paper. The difference may be explained by the different diameters of the counter-flow double-pipe type of heat exchangers used in the two works (see Section 3.2).
Heat recovery systems based on ORC have been designed to operate in three cities (Mosul, Baghdad, and Basra) selected to cover all latitudes of Iraq. The heat recovery efficiency η th,ORC is higher in the North of Iraq. It ranges between 8% and 11% in January and between 4% and 7% in July, depending on working fluid and geographical location. η th,ORC may change by about two percent, in a given month. R134a provides the highest efficiency while the second-best working fluid is R1234ze, but differences in efficiency are less than 1 %. In first approximation, the values of η th,ORC obtained here by using as input the mean air temperature may be underestimated/ overestimated by -1.33/1.33% for R1234yf, by -1.40%/1.38% for R1234ze, and by -1.45%/1.43% for R134a, respectively.
A scenario has been studied, assuming that 20% of the newly installed power capacity is provided by distributed power generation by using electric generators driven by ICEs of medium power (37 kW). The total number of needed units in Baghdad is about 40000 while at the level of Iraq it is about 125000. This means that less than 3% of families should own such newly installed units. The investment in the electric generators and ICE units is about 1.5 billion Euro at the level of the country. Heat recovery units may cost about 500 million euro, if manufactured in dedicated factories. Heat recovery may save about 7.5% of the installed power. The government should be involved in direct investments and in developing appropriate policies to stimulate distributed power generation and heat recovery.