HIGH-TEMPERATURE HEAT PUMPS FOR GEOTHERMAL APPLICATIONS IN AFRICA: THERMODYNAMIC, ECONOMIC AND ENVIRONMENTAL EVALUATION

Paper ID: 510, Page 1 37th INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS, 30 JUNE - 4 JULY, 2024, RHODES, GREECE HIGH-TEMPERATURE HEAT PUMPS FOR GEOTHERMAL APPLICATIONS IN AFRICA: THERMODYNAMIC, ECONOMIC AND ENVIRONMENTAL EVALUATION. Zuffi Claudio1*, Ramundi Filippo1, Fiaschi Daniele1 1University of Florence, Department of Industrial Engineering, Florence, Italy *Corresponding Author: [email protected] ABSTRACT Lowand high-enthalpy geothermal resources are ubiquitously distributed across the African continent, yet their utilization remains constrained. The Rift Valley region stands out as a focal point, showcasing myriad high-enthalpy manifestations of geothermal resources, and therefore for the production of electricity. Meanwhile, the mainland is characterized by an abundance of mediumand low-enthalpy resources and a thorough analysis of this potential is necessary for the sustainable development of the continent. Notably, geothermal resources harbor substantial energy potential that lends itself well to a diverse range of applications. The subject of investigation in this study revolves around the implementation of a high-temperature heat pump (HTHP) that exploits geothermal resources. Specifically, two distinct cases are evaluated: a one-level pressure system and a two-level pressure system. The primary objective of this research is to formulate a comprehensive model capable of predicting the thermodynamic efficiencies, economic costs, and environmental impacts associated with HTHPs. This endeavor entails the development of metamodels designed to forecast the dimensions of the HTHP, including its installed kilowatt capacity and its heat output. Additionally, the model assesses the levelized cost of heat (LCOH). Furthermore, the potential environmental footprint of the HTHP is estimated through the evaluation of its carbon dioxide equivalent emissions via a Life Cycle Assessment. This latter step is executed by employing a parametric Life Cycle Inventory (pLCI), establishing a link between the environmental impact of HTHP construction and the thermodynamic model. To validate the model and delineate potential applications, a series of case studies are examined, specifically focusing on various African regions. The central finding of this study underscores that the low-enthalpy geothermal resources available in Africa have the potential to yield substantial energy savings and significant environmental benefits. These findings are pivotal in fostering sustainable development within the region, marking geothermal energy as a fundamental contributor to the broader sustainability goals. 1 INTRODUCTION The African continent is endowed with significant geothermal potential, particularly concentrated in the eastern and southern regions, aligned with the East African Rift System (EARS) (Elbarbary et al. 2022). This geological phenomenon presents a promising avenue for the utilization of geothermal energy resources, due to the correlation between geothermal activity and Quaternary volcanism along the rift axis (Enerdata, 2013; ESY,2019). Moreover, Kenya's Rift Valley stands out as a hotspot for geothermal exploration and exploitation, boasting vast reserves estimated at 10,000 MW spread across 14 sites (Waruru, 2016; ERC, 2012; KME, 2018). While conventional geothermal power plants have historically focused on high enthalpy resources, recent advancements have shed light on the untapped potential of medium to low enthalpy resources (Stober & Bucher, 2013; Chandrasekharam & Bundschuh, 2008). Notably, the adoption of cascading approaches, leveraging different temperature levels of geothermal energy, emerges as a promising strategy to maximize resource utilization efficiency (Jin et al., 2007; Rubio-Maya et al., 2015; Budiarto et al., 2014). The direct utilization of geothermal energy is the oldest and most versatile way to harness geothermal energy of medium and low enthalpy. Current trending direct uses are mainly for heating systems working directly or through heat pumps, aquaculture, drying crops, growing plants and vegetables in greenhouses, processes of the 1599 1587 https://doi.org/10.52202/077185-0136 Paper ID: 510, Page 2 37th INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS, 30 JUNE - 4 JULY, 2024, RHODES, GREECE paper and the cement industry, food processing, brewing, dyeing of fabrics, snow melting, cooling spaces and balneology, among others (Lund et al. 2011-2016). In this context, Africa stands at the forefront of harnessing geothermal energy for sustainable development, (Waruru, 2016). This underscores the continent's commitment to transitioning towards cleaner and more reliable energy sources to meet growing energy demands while mitigating environmental impacts (Rubio-Maya et al. 2015). Integration of High Temperature Heat Pump (HTHP) with geothermal systems offers potential energy consumption benefits (Arpagaus et al. 2018). Despite being underutilized, geothermal energy presents challenges due to the need for specific extraction locations (Arpagaus et al. 2018) The economic and Environmental feasibility of these methods is a key consideration for future studies. The objective of this paper is to provide a comprehensive model for the sustainability assessment of HTHP applied for geothermal energy and apply it to a case study of the Malawi geothermal resource. This work was carried out as part of the European Long-Term Joint European Union-African Union Research and Innovation Partnership on Renewable Energy, Geothermal Atlas for Africa (LEAP-RE GAA 2020) project. 2 METHODOLOGIES The methodology section of this study delineates the comparative analysis of two distinct system configurations of High-Temperature Heat Pumps (HTHP) as illustrated in Figure 1. Cycle A operates at a singular pressure level, incorporating an evaporator, a compressor, a condenser, and an expansion valve. Conversely, Cycle B is characterized by a dual pressure level system, in which a separator is integrated. This separator works at an intermediate pressure, situated between the cycle's minimum and maximum pressures. Its role is crucial in recovering some of the heat from the working fluid after condensation, as well as decreasing the compressor workload, thus increasing the system's coefficient of performance (COP). The systems configurations for both cycles are derived from existing literature (Cao et al., 2014) employing R152 as working fluid. Initial model validations were conducted using the same fluid; however, This investigation, however, broadens its scope to include environmental considerations by selecting alternative low Global Warming Potential (GWP) fluids, specifically R1233zd(E) and R1234ze(Z) (HFO fluids). The adoption of HFO fluids allows to increase the condenser's temperature compared to R152, thereby raising the user temperature while maintaining the cycle's subcritical condition. The objective of these models is to evaluate the performance of the two cycles, focusing on variables such as the thermal power of the evaporator (Qevap), the heat absorbed by the evaporator from geothermal fluid, the condenser's heat output (Qcond) indicating the system's useful power, the compressor's work requirement (Wcomp), the COP, the system's working fluid flow rate (mcycle), the generated hot water flow rate (mw_out), and temperature (Tw_out). Figure 1: Plant layout of the two cycles: A on the left, B on the right. 1600 1588 https://doi.org/10.52202/077185-0136 Paper ID: 510, Page 3 37th INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS, 30 JUNE - 4 JULY, 2024, RHODES, GREECE After identifying and optimizing these cycle parameters, the study aims to transform the thermodynamic model into a metamodel or surrogate model. This involves defining the inputs, namely the geothermal resource's temperature (Tgeo) and mass flow rate (mgeo), along with their respective variation ranges. Tgeo is specified to range from 50-100°C, and mgeo varies from 1-50 kg/s. To ensure a uniform input distribution, a fixed number of intervals (np), set at 25, is established, resulting in an npx npmatrix. The validated models are then assessed across npx npinput points to generate an output matrix encompassing mechanical component sizes (kW), basic cycle parameters (pressure, temperature, flow rate, etc.), component costs ($), thermo-economic efficiency ($/kWh), and environmental indicators (kg CO2 eq/kWh). Through multidimensional interpolation, the input matrix is associated with the output matrix to estimate a correlation. This process leads to the creation of a metamodel, which is essentially a function that calculates the HTHP system without requiring direct use of the equations of the underlying model. Furthermore, the application scope of this methodology scenarios involving either surface geothermal water or resource extraction from shallow wells. It's critical to note that the thermodynamic metamodel's efficacy is independent of well depth. However, the model's thermo-economic and environmental impact are significantly influenced by the presence and depth of geothermal wells, as evidenced in recent studies (Shamoushaki et al., 2021; Zuffi et al., 2022). Accordingly, this study engages on a comprehensive thermo-economic and environmental analysis across three scenarios: surface geothermal water extraction (well00), extraction from a 500 m well coupled with reinjection into a 300 m well (well500), and extraction from a 1000 m well with reinjection into a 600 m well (well1000). 2.1 Thermodynamic modeling In the simplest plant configuration, denoted as Cycle A operating at a single pressure level, the geothermal fluid is introduced into the evaporator. Here, it transfers heat to the working fluid, which flows in counter current. The temperature of the geothermal fluid exiting the evaporator (Tgeo,out) and the specifications of two temperature differentials in the heat exchanger inlet (ΔTevap,in) and outlet (ΔTevap,out) are fixed. Consequently, the temperature of the working fluid at the evaporator inlet is Tgeo,out -ΔTevap,in, and Tgeo,in + ΔTevap,out at the outlet. This dependency on the geothermal well is evident. The working fluid, existing either as saturated steam (x=1) or superheated steam, enters the compressor, tasked with elevating the fluid pressure to match that of the condenser. The condenser's outlet pressure (x=0) and temperature (Tcond) are directly determined. Two distinct conditions are examined for the working fluids: the first with Low Temperature (LT) Tcond set at 105°C, and the second at High Temperature (HT), evaluating higher temperatures for the two HFO fluids with Tcond set at 140°C. Assuming water is drawn at 50°C (Tw,in) from various sources such as residential, commercial, or industrial applications, it is raised to Tcond-ΔTcond,out . Utilizing the heat output provided by the condenser, the flow rate of hot water producible at this temperature is computed. Finally, the expansion valve serves to revert the fluid to evaporator pressure, thereby completing the cycle. In configuration (B), a separator is integrated into the cycle. Following the initial expansion undergone by the fluid in the high-pressure expansion valve, the separator segregates saturated liquid from saturated vapor. The former undergoes further expansion in a second expansion valve until it reaches the evaporator pressure. Meanwhile, the latter is blended with the fluid exiting the low-pressure compressor. This mixture is subsequently pressurized to match the condenser pressure by the high-pressure compressor. Table 1 reports the main parameter for both cycles. Table 1: Main thermodynamic parameter for the cycles PARAMETERS Value Unit GEOTHERMAL FLUID OUTLET TEMPERATURE OF Tgeo,out 45 °C Evaporator inlet temperature difference 'Tevap,in 5 °C Evaporator outlet temperature difference 'Tevap,out 9 °C Compressor isentropic efficiency Kcomp 0.8 Inlet temperature of the supplied water Tw,in 50 °C Temperature difference between critical point and condenser 'Tcond 10 °C Subcooled temperature in the condenser 'Tsub 5 °C Condenser outlet temperature difference 'Tcond,out 5 °C 1601 1589 https://doi.org/10.52202/077185-0136 Paper ID: 510, Page 4 37th INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS, 30 JUNE - 4 JULY, 2024, RHODES, GREECE Separator pressure difference 'Psep 2 bar The final output of the metamodel is a surface which depends on the two inputs (Tgeo, mgeo) and expresses a thermodynamic parameter of the cycle. For better understanding, the metamodel derived from linear multidimensional interpolation is illustrated in Figure 2, with Cycle A featuring fluid R1233zd(E) as an example. Figure 2: Cycle_a fluid R1233zd(E) 2.2 Thermo-Economic modeling The economic evaluation comprises two stages. Firstly, the cost analysis of individual plant components is conducted using thermo-economic correlations established by Turton (2008). Secondly, the initial investment cost and the total operating and maintenance cost are assessed to determine the Levelized Cost of Heating (LCOH). The thermodynamic analysis provides fundamental parameters required for thermo-economic correlations, including the surface area needed for heat transfer in the condenser and evaporator, compressor and valve handling flow rates, and separator volume flow rate. For the separator, present in the Cycle B only, the thermo-economic correlation referenced from Mosaffa et al. (2017) is adopted. Table 2 outlines the component types and equations used for each one. Various economic equations exist for geothermal wells, often following linear correlations. In this study, the correlation proposed by Shamoushaki et al., (2021) is adopted. LCOH is a techno-economic parameter crucial for feasibility assessment, enabling the comparison of thermal systems. It quantifies the cost of thermal energy produced per kilowatt-hour ($/kWh), as discussed by de Simón-Martín et al. (2022). ܮܥܱܪ ൌ ܥ்஼ூ ൅σܥைƬெ ሺͳ൅ݎሻ௜ ௡ ௜ୀଵ σܧ௜ ሺͳ൅ݎሻ௜ ௡ ௜ୀଵ (1) The parameters in equation (1) are: CTCI is the total capital investment cost, CO&M is the annual operating and maintenance cost, Eiis the annual thermal energy produced, r is the discount rate and n is the lifetime of the energy system. For the calculation of CTCI, the method and parameters used in this work 1602 1590 https://doi.org/10.52202/077185-0136 Paper ID: 510, Page 5 37th INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS, 30 JUNE - 4 JULY, 2024, RHODES, GREECE were taken from Karimi & Mansouri, (2018) and Shamoushaki et al., (2022) and readapted to the case of HTHP, as shown in Table 2. On the other hand, the yearly O&M cost was taken from Beckers et al., (2021) for the general part. On the other hand, the cost of electricity, set at $0.15/kWh and the total energy consumed by the compressors are taken from the above discussed thermodynamic metamodels . Furthermore, a 7% discount rate and a useful life of 25 years were assumed. Table 2: Main equations for the thermo-economic model Cost Correlation Evaporator, Condenser, Compressor ܥܲ଴ൌͳͲ௄భା௄మכ௟௢௚భబௌା௄యכ௟௢௚భబௌమ ܨ௉ൌͳͲ஼భା஼మכ௟௢௚భబ௉ା஼యכ௟௢௚భబ௉మ ܥ஻ெ ൌܥܲ ଴כሺܤଵ൅ܤଶכܨ ெכܨ ௉ሻ All variables are indicated in the tables of Turton 2008 Valve ܥ௩௔௟௩௘ ൌͳͳͶǤͷכ݉௖௬௖௟௘ᇹ Mossafa et al. 2016 Separator ܥ௦௘௣ ൌ ʹͺͲǤ͵כ݉௖௬௖௟௘଴Ǥ଺଻ Mossafa et al. 2016 Wells ܥ௪௘௟௟ ൌʹͷͲͲכ݉ௗ௥௜௟௟௘ௗᇹ Shamoushaki et al. 2021 Total Cost of equipment and wells ܶாௐ ൌ෍ܥ ௜ ௡௖ ௜൅ܥ௪௘௟௟ Cicost of single component Cwell cost of the wells Total Direct Permanent Investment ܥ஽௉ூ ൌܶாௐ ൅ܥ௦௜௧௘ ൅ܥ௦௘௥௩ Csite cost of site preparation Cserv cost of service facilities Total Depreciable Capital ܥ்஽஼ ൌܥ஽௉ூ ൅ܥ௖௢௡௧ Ccont cost of contingencies Cost Total Permanent Investment ܥ்௉ூ ൌܥ்஽஼ ൅ܥ௟௔௡ௗ ൅ܥ௥௢௬௔௟൅ܥ௦௧௔௥௧௨௣ Croyal cost of royalties Cland cost of land Cstartup cost of plant startup Total Capital Investment ܥ்஼ூ ൌܥ்௉ூ ൅ܥௐ஼ C WC cost of working capital 2.3 Environmental modeling The environmental modeling approach adhered to the Life Cycle Assessment (LCA) methodology outlined by ISO 14040 and ISO 14044 standards (ISO, 2021a; ISO, 2021b). The approach used is cradle-to-gate, so the system boundaries include the production and reinjection geothermal wells (if present), the piping system, the surface plant, and the utilization phase. The functional unit for the analysis is the thermal kWh produced by the system. Specifically, to facilitate assessment across numerous scenarios, emphasis was placed on developing a Parametric Life Cycle Inventory (pLCI). pLCI links material and energy consumption throughout the production, operation, maintenance of the HTHP system with its size, as determined by the thermodynamic metamodel. For the construction phase of the system, primary data was collected from commercially available HTHP models sourced from TRANE (2022). A correlation was established between system thermal power (kW) and total weight, as depicted in Figure 3, based on the collected data. Subsequently, the production process for process - heat pump production, brine-water, 10kW (heat pump, brine-water, 10kW - from the Ecoinvent database was selected as a reference model. Inputs and outputs of this process were categorized into materials and energy utilized during construction. Percentages for each material and energy consumption were determined, with energy normalized to the total mass of the element. This allows the creation of a new environmental model for the HTHP, incorporating adjusted input and output values multiplied by the correlation obtained in Figure 3. The modeling of geothermal wells was approached linearly, utilizing a shallow well drilling process as described by Karlsdottir et al. (2015). The operation phase accounted for electricity consumption using a reference process for electricity production (market for electricity, medium voltage | electricity, medium voltage, KE) while maintenance was evaluated as a 20% material replenishment throughout the life cycle. For analysis, the Ecoinvent 3.7.1 library and the Brightway software, integrated with activity-browser software via Python, were employed. The environmental impact assessed primarily focused on the Climate Change (CC) indicator, expressed through the Environmental Footprint 3.1 methodology. 1603 1591 https://doi.org/10.52202/077185-0136 Paper ID: 510, Page 6 37th INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS, 30 JUNE - 4 JULY, 2024, RHODES, GREECE Figure 3: Development of correlation between total system weight and heating capacity 3 CASE STUDIES: MALAWI HOT SPRINGS The case study evaluated in this paper is the Malawi hot springs. Davalos et al., 2021 performed an extensive study on the geochemical characteristics of 27 hot springs in Malawi, distributed along north to south of the Malawi Rift Zone. In addition to characteristics related to the chemistry of the geothermal resource, the surface temperature assessment is carried out by reporting the temperature of all 27 sites. The surface temperature ranges between 35-80°C, but only hot springs with a temperature above 50°C are taken into consideration in this work, as reported in Table 3. Unfortunately, the required mass flow rate are not available, for this reason, three flow rate scenarios are defined - High 50 kg/s (Hm), Medium 20 kg/s (Mm), Low 8 kg/s (Lm). Table 3: Hot spring geothermal sites in Malawai (Davalos et al. 2021) Hot spring Surface Hot spring Surface T°C T°C Ngala 54.90 Chombo 66.84 Chiweta 79.70 Madzimawira 63.73 Mphizi Stream 78.70 Ling’ona 58.08 Mtondolo 64.77 Chikwizi 52.17 Mtondolo 2 72.90 July Borehole 51.35 Chiwe 74.90 Final applications have been defined for possible users of the heat produced at the respective temperatures. In particular, 2 possible uses were chosen: xCooking station (CS) supplying steam at 140 °C (HT condition) for cooking food, which requires about 2.89 GWh/year heat load for a group of 5’000 people, (CS5k); 5.79 GWh/year for 10’000 people (CS10k); 29.00 MWh/year for 50’000 people (CS50k) (Kajumba et al. 2022). xCassava drying (CD) supplying steam at 100°C (LT condition) for drying vegetables. This process requires about 306 kWh/(ton), so three scenarios are assumed in which a company produces about 10 k tonnes/year CD10, 50 k tonnes/year CD50, and 100 k tonnes/year CD100 (Nwakuba et al. 2016). 4RESULTS 4.1 Parametric analysis From the analysis conducted on the performance of the system depicted in Figure 4, the COP in all scenarios within Cycle A and Cycle B are compared with previously mentioned fluids. COP is not dependent of mgeo and is solely reliant on Tgeo,as the m cycle increases and decreases at the same rate as y = 4.1389x + 1130 R² = 0.8995 0 2000 4000 6000 8000 10000 0 200 400 600 800 1000 1200 1400 1600 1800 2000 Weight [kg] Heating capacity [kW] 1604 1592 https://doi.org/10.52202/077185-0136 Paper ID: 510, Page 7 37th INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS, 30 JUNE - 4 JULY, 2024, RHODES, GREECE mgeo, thus the COP value does not change at variable mgeo. The general trend is increasing because, as Tgeo increases, the difference between highand low-pressure decreases, so the compressor work is reduced and the COP increases. Focusing on the case of LT, the comparison between Cycle A and Cycle B, the COP for HFO fluids ranges between 3.67 and 4.14 for Cycle A and between 3.53 and 4.13 for Cycle B. Despite the difference in pressure levels for this case, there is no remarkable difference between the two cycles at the thermodynamic level. Conversely, the notable performance difference of fluid R152, exhibiting consistently lower COP across all Tgeo values, is highlighted. Considering that HFO's environmental performance is better than R152 due to its lower GWP and the better thermodynamic performance of the cycle, the selection of HFO fluids is advised. In addition, with HFO fluids it is possible to maintain the subcritical cycle by increasing the output temperature, in the case of HT. The comparative analysis between Cycle A and Cycle B unveils a notable downturn in COP for both cycles when juxtaposed with the LT scenario. Comparing LT and HP, the cycle A COP experiences a precipitous decline from 1.90 to 2.47, whereas in Cycle B, albeit exhibiting a decrease compared to the preceding scenario, COP ranges between 2.59 and 2.89. The rise of Tcond precipitates a growth of pressure consequently augmenting the workload for the compressor. While this yields steam of higher temperature for the end user, it concurrently diminishes the COP of the cycle. This behavior is enhanced in Cycle A, exerting a lower impact on Cycle B due to the presence of two compression levels, which mitigates the overall work required during the compression stage. For the following analyses, Cycle A for the LT scenario and Cycle B for the HT scenario are taken as references. Figure 4: Graphs of the coefficient of performance (COP) of the different cycle cases: Top left Cycle A - Low temperature (LT) Tcond = 105°C, Top right Cycle B - LT, Bottom left Cycle A - High temperature (HT) Tcond = 140°C, Bottom right Cycle B - HT 1.5 2.0 2.5 3.0 3.5 4.0 4.5 50 70 90 COP Tgeo Cycle A - LT R1233zd(E) R1234ze(Z) R152 1.5 2.0 2.5 3.0 3.5 4.0 4.5 50 70 90 COP Tgeo Cycle B - LT R1233zd(E) R1234ze(Z) R152 1.5 2.0 2.5 3.0 3.5 4.0 4.5 50 70 90 COP Tgeo Cycle A - HT R1233zd(E) R1234ze(Z) 1.5 2.0 2.5 3.0 3.5 4.0 4.5 50 70 90 COP Tgeo Cycle B - HT R1233zd(E) R1234ze(Z) 1605 1593 https://doi.org/10.52202/077185-0136 Paper ID: 510, Page 8 37th INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS, 30 JUNE - 4 JULY, 2024, RHODES, GREECE 4.2 General results of Metamodels: Economic, Environmental The thermo-economic evaluation reveals significant variability in the Levelized Cost of Heat (LCOH) depending on resource conditions and well characteristics. Figure 5 shows LCOH, with 5a representing well1000, 5b representing well500, and 5c representing well00. Additionally, the red dashed line represents the reference LCOH value provided by IEA 2021 for heat generated from natural gas-fired boilers, hovering around 17 c$/kWh, while the cost obtained for High-Temperature Heat Pumps (HTHP) is indicated as 22 c$/kWh (Jeßberger, J et al. 2023). It is evident that there is a substantial decrease in LCOH from 5a to 5c, highlighting the significant influence of drilling costs on this parameter. In 5a, it is observed that LCOH is exceedingly high for low value of Tgeo and mgeo, reaching a maximum of 155 c$/kWh, with economic feasibility only apparent at higher temperatures or increased mass flow rates. In 5b, where the well depth is shallower, the maximum LCOH reduces to 100 c$/kWh, and more combinations of Tgeo and mgeo surpass the red dashed line. Finally, in 5c, only a narrow range fails to yield an economic advantage, in fact, for all combinations of Tgeo-mgeo above 62° C or above 17 kg/s, an LCOH below the boiler heat output is obtained. This underlines the dependence of LCOH on the cost of wells, which strongly affects the parameter. Therefore, for HTHP applications, cases where the geothermal reservoir is superficial, hot waste fluids from geothermal power plants or other situations without drilling wells would offer significant economic benefits. However, if a greater number of wells or deeper drilling is necessary, the conditions for LCOH advantage diminish considerably. Therefore, a careful evaluation is needed for each specific case according to the depth of the resource. The same areas assessed for the LT case are not displayed due to the consistent trend, with LCOH range variation being minimal, around 1-2 c$/kWh. Figure 5: Techno-economic metamodel of the LCOH parameter for the three well depth scenarios: 5a well1000, 5b well500, 5c well00 Figure 6 shows the metamodel of CC, equivalently for Figure 5. The environmental impact from geothermal HTHP has been much less studied in the literature so the limits are shown, a red one representing the CC indicator for a kWh produced by a natural gas modulating condensing boiler 264.16 g CO2 eq/kWh and the blue line for a kWh from a borehole heat exchanger brine-water 223.88 g CO2 eq/kWh evaluated by Ecoinvent providers. As can be seen, the trend is similar to the LCOH, where CC has a higher impact for case 6a whereas for low mgeo and Tgeo 278 gCO2 eq/kWh which compared to normal boiler emissions is very similar. For this reason, temperatures above 60°C or mgeo above 15 kg/s are preferred to have a low environmental impact compared to other low-impact systems. It should be considered that, even in this case, the impact from drilling has a major contribution even if it is less incidental compared to the effect in LCOH, this is because CC also has a strong contribution from electricity production. As shown in both figures 6b and 6c, the potential for achieving low environmental impact is even greater, confirmed by a decrease in equivalent emissions. The borehole heat exchanger brine-water limits given in figure 6b only cover a small range for temperatures below 55° C. On the other hand, from figure 6c all cases are environmentally advantageous. Combining the information derived from both LCOH and CC, it appears that the limiting factor prevailing is the economic aspect rather than the environmental one. Therefore, for a comprehensive assessment of HTHP installation, priority should be given to economic viability over environmental considerations. The optimal conditions, as defined by economic metamodels, should guide decision-making processes in ensuring the most advantageous outcomes. g 1606 1594 https://doi.org/10.52202/077185-0136 Paper ID: 510, Page 9 37th INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS, 30 JUNE - 4 JULY, 2024, RHODES, GREECE Figure 6: Figure 5: Environmental metamodel of the CC parameter for the three well depth scenarios: 5a well1000, 5b well500, 5c well00 4.3 Results of Malawi case studies Figure 7 shows the thermal energy produced by cycle B with R1234ze(Z) fluid, the corresponding LCOH and CC. The dashed red lines represent the heat demand for the three scenarios CS5k, CS10k, CS50k. The graph shows that in the case where mgeo is Lm for all wells, it is possible to satisfy the heat demand for a community of 5 thousand people CS5k. A community of 10 thousand people CS10k can be satisfied for some wells even in the case of Lm (Mtondolo 2, Chiwe, Mphizi stream). For all other wells, it is possible to satisfy this demand only in the case of Mm. The heat load of the CS50k scenario is only reached for some sites in the Hm case (Chombo, Chiwe, Motombolo, Motombolo2 and Mphizi stream). It can also be noted that the two Madzimawira and Chiweta sites where the flow rates are known can meet the CS10k and CS50k heat loads respectively. All scenarios have an LCOH that varies between 11.2 c$/kWh and 12.5 c$/kWh and are therefore very cost-effective. It is mainly due to the surface heat source, which allows for an extremely low LCOH. As far as CC is concerned, a larger variation is found, ranging between 197-186 gCO2/kWh. It is found that for wells with low Tgeo, CC increases, and this is the result of the cycle behavior. In fact, the lower Tgeo implies a larger difference between the low and high pressure of the cycle, which is reflected in a higher consumption of electricity by the compressor and thus a greater environmental impact. Figure 7: heat produced by cycle B with R1234ze(Z) fluid and corresponding LCOH and CC, for cooking station 0.0 10.0 20.0 30.0 40.0 50.0 Ngala Chiweta Mphizi Stream Mtondolo 2 Mtondolo Chiwe Chombo Madzimawira Ling'ona Chikwizi July Borehole Heat [GWh/year] Real Low Medium High 185 187 189 191 193 195 197 199 201 203 205 0 2 4 6 8 10 12 14 Ngala Chiweta Mphizi Stream Mtondolo 2 Mtondolo Chiwe Chombo Madzimawira Ling'ona Chikwizi July Borehole CC [g CO2 eq/kWh] LCOH [c$/kWh] LCOH CC 1607 1595 https://doi.org/10.52202/077185-0136