Studies on Optimal Strategy to Adopt Nuclear Power Plants into Saudi Arabian Energy System Using MESSAGE Tool

An optimal long-term electric power strategy for Saudi Arabia to adopt nuclear power was evaluated using the MESSAGE tool. Saudi Arabia is predicted to experience an electricity shortage by 2025 with the present energy system. +is electricity shortage could be postponed until 2035 by rehabilitating the existing power plants. +e MESSAGE model predicts that adopting a combination of renewable (i.e., solar and wind), advanced traditional power (i.e., gas turbine, steam, and combined cycle), and nuclear technologies is the most competitive future strategy to supply 43.7%, 41.6%, and 3.8%, respectively, of Saudi Arabia’s electricity needs by 2050. +is paper proposes an optimal strategy for adopting nuclear power. +e nuclear capacity of three scenarios was evaluated: a single APR-1400 nuclear reactor, a single SMART-100 nuclear reactor, and a combination of these two reactors. +e results of this study indicate that the highest nuclear capacity was achieved by the combination of the APR-1400 and SMART-100 reactors followed by the single APR-1400 reactor and then the single SMART-100 reactor. However, the single G4ECONS nuclear reactor shows a higher capacity than the single APR-1400 reactor in other evaluated scenarios. +e combined reactor strategy may be the most feasible option if the capital cost of a first-of-a-kind SMART-100 reactor is reduced by 62.3%.+e cost reductions result from including factors like the time required to build the nuclear power plants in the MESSAGE tool calculation. Also, CO2 taxation will increase nuclear power’s feasibility in the Saudi Arabian energy system. However, the share of renewable energy is predicted to be more affected by the taxation of CO2. In this study, the proposed approach can provide more flexible strategic options for countries embarking on nuclear energy. +ese flexible strategic options can optimize their national energy mix for long-term planning.


Introduction
Energy, including electricity, plays a crucial role in the economic growth and social development of Saudi Arabia. Although Saudi Arabia has been the world's largest oil producer and exporter [1], previous studies predict that Saudi Arabia will be a net oil importer by 2030 or 2038. is will happen unless appropriate measures for the development of sustainable energy systems are immediately undertaken [2'3]. Currently, Saudi Arabia ranks 11 th in the world in electric power production and 13 th in the world in electricity consumption [4].
e Saudi Electric Company was the 14 th biggest electricity company in the world at the end of September 2017 [5].
In 2015, Saudi Arabia had more than 940 generator units in 46 power plants (PPs) distributed over four geographical regions (i.e., load areas) [6]. However, more PPs are needed to match its rapidly expanding electricity demand rate. is electricity demand rate is predicted to increase annually by 5%-8% [7][8][9]. It is reported that desalination of water significantly affects the energy Equation in the Middle East. Desalination of water is required more in the Middle East than in any other part of the world. us, energy and water are closely intertwined in the Middle East. In this region, any discussion about the outlook of electricity also becomes a discussion about water. e Middle East uses desalination to narrow the gap between freshwater withdrawals and a sustainable water supply [10].
Saudi Arabia uses 25%-50% of its oil and gas production to desalinate water. is means that the desalination sector uses a significant portion of Saudi Arabia's energy capacity [11][12][13][14][15]. In Saudi Arabia, the installed power capacity is expected to grow at an annual capacity growth rate of approximately 1.5% from 2020 to 2025. However, the energy demand is expected to increase by 8%-10% annually. Peak demand was 70 GW in 2020. is peak demand is expected to reach 120 GW by 2032, partially driven by increased water desalination. e region's unstable geopolitics are expected to act as a restraint on market growth in the power sector. In 2014, Saudi Arabia was estimated to increase its power generation capacity from 77 GW in 2014 to 156 GW in 2040 [8][9][10][11][12]. A recent study reports that desalination of water production has reached 2559 Mm 3 , with an annual growth rate of 5% in Saudi Arabia. Consequently, sustaining and improving the capacity of domestic PPs has become a major challenge in Saudi Arabia. Currently, approximately 60% of Saudi Arabia's total electricity supply is generated by burning oil in the planning and management of electric power generation systems [16].
Reduction in greenhouse gases (e.g., CO 2 ) produced by PPs is a strategic objective of Saudi Arabia. Currently, Saudi Arabia is the 10 th largest greenhouse gas-emitting country in the world [17].
is study evaluated possible electricity generation techniques to meet the future demand for clean energy in Saudi Arabia.
Previous studies on Saudi Arabia energy systems only evaluated short-term (e.g., 5 to 15 years) or medium-term (e.g., 20 to 30 years) electricity demands. e existing studies focused on the potential applications of new technologies, including wind and geothermal energy [18'19]. ese studies compared some renewable energy technologies with existing energy technologies [20'21]. However, these previous studies did not comprehensively evaluate the options for future energy systems in Saudi Arabia (e.g., utilization of existing PPs and strategic introduction of new technologies in the PPs, such as coal, waste, nuclear, and advanced traditional fuel).
A recent study showed planned nuclear power plants (NPPs) in the Middle East and North Africa region. is study identified Iran, UAE, Egypt, and Jordan as countries possibly adopting nuclear technology [22]. Although Saudi Arabia plans to introduce NPPs in the near future, this paper categorizes Saudi Arabia as a country expressing nuclear intention and does not directly address any specific nuclear power development plans. However, some technical or economic studies on Saudi Arabia energy policy have mentioned that nuclear power is one of the main options in the future power system by the Nuclear Energy Development Road Map (NEDRM). Saudi Arabia is included in the NEDRM timetable for the development of NPPs [7'23'24].
Based on the NEDRM, Saudi Arabia originally planned to construct 12 units of NPPs over the next three decades. e site selection process was set to begin in 2013. Construction of the NPPS was set to start in 2017. e first NPP was scheduled to start operating by 2022. Five NPPs were scheduled for construction by 2027. ese NPPs were expected to produce an accumulated total capacity of 9. 6 GWe.
An additional six NPPs were planned to be installed by 2032. By 2032, the total capacity of NPPs was projected to reach 17 or 17.6 GWe [7 '24].
A recent report mentioned that the nuclear target date has now been delayed until 2040 [25]. In 2019, the King Abdullah City for Atomic and Renewable Energy (KA-CARE) announced plans for a new renewable target. ese plans included a target of 2032 to produce 58.7 GWe by renewable technologies [26]. Some recent studies discussed that using electricity produced by solar and wind technologies in a grid may cause problems at high demand levels. ese problems occur because the supply of electricity produced by these technologies does not correspond to the demand [27,28]. In March 2015, the Korea Atomic Energy Research Institute (KAERI) signed a Memorandum of Understanding with the KA-CARE. Under this agreement, the two countries conducted a three-year preliminary study to review the feasibility of constructing SMART-100 reactors in Saudi Arabia. e agreement anticipated that the cost of building the first SMART-100 unit in Saudi Arabia was one billion USD. e contract to build four advanced power reactors (APRs) at Barakah with a nameplate capacity of 5,380 MWe had cost estimates ranging from 24.4 to 32 billion USD [9,[29][30][31][32]. Additionally, the SMART-100 supply chain and potential success were compared to projections for four Korean Electric Power Company APR-1400s currently being built in the United Arab Emirates (UAE) [31].
However, the NEDRM did not specify the available nuclear power development programs in Saudi Arabia. To date, there have not been any updated reports with additional detailed information (e.g., schedule of deployment of NPPs, time-dependent nuclear share, and type or capacity of NPPs to be built) or rationale to establish a nuclear power development program in Saudi Arabia. Additionally, the Saudi Electric Company has a plan to diversify fuel and reduce the direct burning of crude oil for electricity generation. is plan involves switching from conventional to nonconventional technologies to reduce greenhouse gas emissions from PPs [34]. e NEDRM did not address the strategic need to reduce greenhouse gas emissions from PPs [7]. Some investigators have studied the effect of controlling CO 2 emission from conventional and renewable PPs in Saudi Arabia. However, no specific studies have been conducted to evaluate the effect of CO 2 taxation on the relative competency of candidate technologies, including nuclear power in the Saudi Arabia energy system [35][36][37]. e objective of this study was to determine optimal long-term strategic options for introducing new technologies in Saudi Arabia. ese should consider the available options (i.e., traditional fuel, renewables, nuclear). e options should also include nuclear power system options based on the present situation of the Saudi Arabia energy system and the official plan in the NEDRM. In this study, a conceptual model of the Saudi Arabia energy system was developed and illustrated by a systematic diagram. Next, various scenarios were developed which simulate potential national energy systems with multiple nuclear power development options. ese scenarios consider the constraints on the cost of the overall energy system cost and other expenses (e.g., construction time of PPs). e Saudi Arabian energy system was simulated using the MESSAGE energyplanning tool [38' 39]. Additionally, this study included an analysis of the effect of taxation policy on greenhouse gas emissions from PPs in the Saudi Arabia energy system.
is study is a case study for a country intending to introduce nuclear power (i.e., Saudi Arabia) for optimizing its future national energy system through the use of the MES-SAGE tool. is study adopted a new approach for establishing scenarios by assuming possible deployment of a combined nuclear fleet consisting of two different types of NPPs. Furthermore, we applied the G4ECONS tool to calculate and compare the levelized costs for different types of nuclear generation. e levelized costs are not explicitly considered in the levelized Unit Energy Cost (LUEC) calculation incorporated in the objective function of the MESSAGE tool [40][41][42].

MESSAGE as an Energy-Planning Tool.
Various software tools for energy planning have been developed to evaluate future energy systems, including LEAP, POWERWORLD, WASP, PSSE, VULARAGUA, EMPS, and MESSAGE. e MESSAGE tool was developed by the International Atomic Energy Agency and has been widely used for long-term energy system planning. MESSAGE is based on a dynamic linear programming model to minimize the total system costs and discount all costs occurring at time points later than the base year [43][44][45].
In this study, the MESSAGE tool was used to evaluate the Saudi Arabia energy system. e MESSAGE tool has advantages due to the following features [39]: (i) Capability to combine technologies and fuels to construct so-called "energy chains" (see Section 2.3): this capability enables map energy to flow from resource extraction and energy conversion (supply side) to the distribution and provision of energy services (demand side) [38] (ii) Flexibility to introduce and simulate energy policy and technology choices: these factors may influence future energy demand and supply over time [39] (iii) Capability to ensure sufficient energy supply for generating technologies and resources based on the specified energy demand: this is accomplished by continuous simulation along the energy chain from supply to demand [45] (iv) Potential to define and introduce different types of PPs: these types of PPs include NPPs with detailed technical data for an extended time frame (i.e., over 50 years) [43] 2.2. e G4ECONS Tool. e G4ECONS tool was used to generate a more accurate calculation and analysis of the levelized costs of the various generation IV systems. G4ECONS is a Microsoft Excel-based tool that was developed for economic analyses. G4ECONS has four main requirements: simplicity, universality, transparency, and adaptability [40,42]. erefore, the G4ECONS tool can evaluate the relationship between construction lead time and levelized costs. In this study, G4ECONS was used to estimate the interest rate duration construction (IDC). It was also used to calculate the Total Capital Investment Cost (TCIC), LUEC, and levelized unit product cost (for nonelectricity applications) of different nuclear energy systems. G4ECONS was used to evaluate the effect of decommissioning costs and radioactive waste management from the nuclear generation processes [46][47][48][49][50][51][52][53][54][55][56][57][58].

Collection of Basic Information and Input Data.
A set of data for Saudi Arabia were collected and rearranged for input into the MESSAGE tool to simulate the national energy system. A wide range of national statistical data, technical reports, and other previous studies on the Saudi Arabia energy system were reviewed. Technical and economic data with detailed information about existing and candidate PPs in Saudi Arabia were adopted from official reports and recent studies. is information included capacity, type of fuel, lifetime, efficiency, capacity factor, investment cost, variable or fixed operation, maintenance cost, electric power production, and demand [6'8]. Information on the available national resources of crude oil and natural gas was obtained from official statistics issued by the Saudi Arabia government [59].

Modeling the Saudi Arabian Energy System and Definition of Base
Year. A well-organized flow diagram of the energy system is helpful when developing energy-planning studies for a country. e flow diagram shows the energy levels (ranging from resource to demand) and their interconnected chains. It is useful for understanding the whole energy system. However, no specific energy system flow diagram of the Saudi Arabian energy system has not been reported in the public domain literature. is study modeled the energy system of Saudi Arabia by using a systematically conceptualized energy system flow diagram based on the abovementioned information and data collected with the MESSAGE methodology [60]. e national energy system of Saudi Arabia was structured in a supply of energy network (i.e., physical flow model), which included energy resources (i.e., crude oil, natural gas, and their derivatives, and other imported energy resources), primary, secondary, and final energy levels. e simplified Saudi Arabian energy system flow diagram is shown in Figure 1.
2015 was selected to be the base year for the MESSAGE calculation. 2015 was chosen because it was the most recent year with available background information on the economy and energy status of Saudi Arabia. e MESSAGE calculations were performed for 2015 to 2050, with a five-year time step for each calculation and an assumed annual discount rate of 2.1%.

Resource Level.
In this study, "resource" is defined as a raw resource such as coal, oil, natural gas in the ground, or biomass in a field [60]. As of 2015, the primary energy system resources in Saudi Arabia were crude oil (63%) and natural Science and Technology of Nuclear Installations gas (37%). e amount of strategic reserve of crude oil reached 266 billion barrels with a daily production of greater than 10.5 million barrels [61]. e natural gas reserve was reported to be approximately 303.251 billion cubic feet [60].
ese resources (i.e., crude oil and natural gas) are transferred to refineries or gas treatment facilities after extraction. Next, these resources are processed to produce the derivatives used in the primary energy level. is type of primary energy level is identified as "1" in Figure 1.

Primary Energy
Level. In this study, "primary energy" is defined as a raw product at a generation site (e.g., crude oil input to the refinery) [45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60]. Based on this definition, the Saudi Arabian energy system's primary energy level was defined as extracted crude oil and natural gas for transfer to refinery and treatment facilities, respectively. is type of primary energy level is identified as "7" in Figure 1. Imported derivatives or fuel (e.g., nuclear fuel for NPPs) and waste from PPs were categorized as the primary energy levels [62]. is type of primary energy level is identified as "2" in Figure 1.

Secondary Energy Level
. "Secondary energy level" is defined as a finalized product on a generation site (e.g., gasoline or diesel fuel output from the refinery) [59]. erefore, the Saudi Arabia energy system's secondary energy level was defined as the following energy forms: oil derivatives, including LPG, gasoline, kerosene, diesel, heavy fuel oil (HFO), petroleum coke, and natural gas derivatives, including treated natural gas [61]. e secondary energy level was identified as "3" Figure 1. In this study, the future production of derivatives of crude oil in Saudi Arabia refineries was predicted by assuming the annual average growth rate for the period 2007 to 2015 (i.e., 5.3% for LPG, 14.2% for gasoline, 2.3% for kerosene, 5.7% for diesel, 18% for HFO, and 2.1% for petroleum coke) and the actual production of the 2015 base year [59'62]. e secondary energy level also includes the main electricity transmission lines to four regions (i.e., east, west, center, and south), all existing PPs (identified as "9" in Figure 1), all desalination units (including Cog-SMART, which was identified as "13" in Figure 1), and candidate PPs (identified as "10" in Figure 1). e imported items (identified as "8" in Figure 1) include the imported electrical power from the Gulf Cooperation Council (GCC) countries' grid interconnections between the six Arab states of Kuwait, Saudi Arabia, Bahrain, Qatar, UAE, and Oman. e imported power is expected to drive the market in the future.
is plan aims to supply both Kuwait and Saudi Arabia with a 1200 MW of power capacity (along with 900 MW for UAE, 750 MW for Qatar, 600 MW for Bahrain, and 400 MW for Oman) [8]. is project was overseen by the board of directors of the GCC Interconnection Authority (GCCIA). Other imported items (e.g., oil fuels), nuclear fuel for the NPPs, and waste from the PPs were also represented in the energy system flow diagram. However, some of the oil derivatives (e.g., asphalt) were not considered in Figure 1 because they do not fit an energy form specified in Table 1.
e average values of the characteristic parameters for the existing PPs available in Saudi Arabia are shown in Table 2. In this study, the characteristic parameters for the assumed candidate PPs (i.e., nonnuclear PPs and NPPs) are listed in Tables 3 and 4. However, all of the described costs in Table 4 refer to 2020. is study was normalized to the 2015 base by assuming that Saudi Arabia and South Korea have the same economic parameters as the US [64][65][66]. We assumed that the nominal discount rate value from the revised Appendix C of Circular A-94 approximated the current economic factors in 2015 for both APR-1400 and SMART-100 reactors during the operation time. We considered the US economic factors, such as the inflation rate and the incremental escalation (i.e., the base of the nuclear projects experience) in our calculation, as shown in Table 10 [64]. We also considered other US economic factors, including inflation rate and incremental escalation (i.e., the base of the nuclear projects experience) in our calculation. e capital cost was set to 1.7% to represent the general inflation rate per year. Additionally, the incremental escalation rate was set to 3%, and the nominal discount rate was set to 2.1% [65]. e normalized costs in Table 4 were calculated for all units using the net present value (NPV), and the reference year for cost assessment was set to 2015. e normalized costs were based on the following equation [66]: where I inf is the general inflation rate, I ins esc is the incremental escalated rate, I d is the nominal discount rate, and n is the number of years after the base year. e characteristic parameter values for the desalination systems representing an integrated nuclear desalination system (i.e., cogeneration (Cog-SMART)) are shown in Table 5 [11].

Final Energy Level.
In this study, "final energy" is defined as a finalized product at its consumption point (e.g., gasoline in a car's tank or electricity leaving a socket) [56]. e final energy level of the Saudi Arabia energy system was defined as electricity and other energy forms (e.g., diesel, gasoline, kerosene, HFO, and LPG) produced by the secondary level (e.g., PPs or refineries) and then transferred to the final level (i.e., consumption point) [44]. e final energy level is identified as "4" in Figure 1.

Demand Level.
In this study, "demand" or "useful energy" in the Saudi Arabia energy system was defined as the final products satisfying the demand for services, such as heating by heat fuel, lighting by electricity, and moving people and freight by transportation. Demand is identified as "5" in Figure 1 [59]. e only electricity demand level was considered in this study was identified as "12" in Figure 1.
In this study, the electricity peak demand (EPD) after the 2015 base year was calculated by adopting the annual growth rate of the EPD for each region assumed in an official report.
e EPDs were assumed to be 6%, 5%, 5%, and 9% for the East region, West region, Central region, and South region, respectively [6,8,75,76]. e forecasted EPDs were further adjusted by considering a feasible future demand reduction of 8% in Saudi Arabia. Previous studies report future demand reduction due to the possible decrease in electricity consumption from the use of high-efficiency electrical appliances, which have lower losses (e.g., cooling system, water heating, lighting, and smart loads) in Saudi Arabia identified in past studies [75,76]. e total projected EPDs for Saudi Arabia were estimated using an Equation from the manual of the Model for Analysis of Energy Demand (MAED). e total projected EPDs for Saudi Arabia are detailed in Table 6 [6,8,77]. e EPDs projected in this study (i.e., 68.7 GWe in 2020 and 135.5 GWe in 2032) compared well the predictions reported by the World Nuclear Association (i.e., 70 GWe in 2020 and 120 GWe in 2032).
Forecasts in another study estimated that Saudi Arabia's energy demand will grow annually by 8%-10%. e peak demand was expected to be 70 GWe in 2020 and reach 120 GWe by 2032, driven partially by the increase in desalination. Desalination represented about 41% of the other consumption sectors in Saudi Arabia. However, Saudi Arabia was estimated to increase its power generation capacity from 77 GWe in 2014 to 156 GWe by 2040 to meet the projected electricity demand [6,[8][9][10][11][12][13][14][15][16].
In this study, the capital cost assumptions were demonstrated by previous category classification, including direct construction costs, indirect services costs, preconstruction costs, owner costs, supplementary costs, and financing during construction. ese values were summarized in Table 7.

Main Scenarios with Assumptions.
To determine the optimal options for Saudi Arabia to supply its EPD sustainably in the long-term, the following four different energy system scenarios were assumed.

Scenario I (Reference Energy Supply).
Scenario I is a "do nothing" scenario, in which all of the existing PPs are assumed to be in operation up to their intended design lifetimes and then subsequently dismantled and out of the grid without either rehabilitation of existing PPs or introduction of any new PPs.

Scenario II (Rehabilitation of Existing PPs).
In Scenario II, it was assumed that old PPs would be rehabilitated. e efficiency of the existing PPs would be upgraded once at the end of their design lifetimes as follows: 38% to 40% for ST-PP [79], 45% to 49% for GT-PP [80], 40% to 45% for CC-PP, and 25% to 30% for DG-PP [81].      [33,[48][49][50][51][52][53][54][55][56][57][58].    [9]. Furthermore, Saudi Arabia has tremendous wind and sun, and these technologies are considered among the best in the world [69][70][71][72][73][74][75]. Nevertheless, Saudi WD-PP and SL-PP prices will be at the low end of the global price range. Some studies reported by WNA, REI, and WNISR provide a potential decline of energy prices from renewals, such as wind and solar, which may improve the competitiveness of such technologies in the energy mix. Due to the limitation of availability of specific discounted cost and the technology development of renewables and reproduction of PPs in the future, the reported values in existing studies were assumed in this study [80][81][82]. Furthermore, the locations of other candidate technologies have been assumed based upon available energy resources therein. WD-PP is assumed to be introduced in West and East regions, and SL-PP in West, East, and Center regions, reflecting the abundance of wind resources and solar radiation [21] and GH-PP in South region considering the availability of geothermal resources therein [19]. PSH-PP was assumed to be adopted in the West region due to the potential of pumped storage hydro to be built in this region [74]. WT-PP is also assumed to be adopted in the West region due to the availability of waste fuel either from industrial regions or from agricultural bio-waste materials in the West region [84]. CL-PP is assumed to be in the East region due to coal fuel will be imported through the Persian Gulf seaport, and it is better to reduce the coal transportation cost [37]; A-CC-PP is to be in East and West regions to energize the local industrial sector [86], whereas A-GT-PP being assumed to be in South region as shown in Table 3 [85,87].
ere are two families of desalination technologies, such as thermal technology and membrane technology. However, in this study, three desalination units are assumed based on General Electric (GE) suggests that Saudi Arabia requires 300000 barrels of oil per day for the desalination plants on the country's eastern and western coasts with two types of seawater desalination technologies, such as Seawater Reverse Osmosis (SWRO) as membrane technology, while multistage flash (MSF) and multiple effect distillation (MED) as thermal technology as shown in Table 5 [11].
To implement the NEDRM, Saudi Arabia has signed various bilateral cooperation agreements with several nuclear vendor countries. Recently, five countries such as China, France, Korea, Russia, and the USA who submitted letters of intent were designated as preferred bidders for its first NPP project [82]. All of the above five countries have experience constructing large capacity commercial NPPs, such as CNP-1000, P4 REP 1300, OPR-1000, APR-1400, VVER V-491, and WH 4LP (DRYAMB) [83].
e Saudi Arabian government has signed a few agreements with other countries for the development of small-capacity nuclear reactors, including CAREM-25 (27 MWe) of Argentine and SMART-100 (100 MWe) of Korea [9]. More specifically, KEPCO, which has been shortlisted to bid on nuclear power projects in Saudi Arabia, has an experience in constructing and operating large capacity NPPs such as APR-1400 and OPR-1000 [82]. Furthermore, Korea has signed an agreement with the KA-CARE to assess the potential for building at least two small size reactors such as SMART-100 developed by KAERI [9]. erefore, both large and small NPPs (i.e., APR-1400 and SMART-100) from Korea have been considered as candidate nuclear power reactors in this study. With a view of observing differences in various nuclear power development options possibly introduced into Saudi Arabia, Scenario III was further divided into four subscenarios: It is noted that NPPs are assumed to be excluded from the region "Center" due to the limited availability of surface water resources for reactor cooling in the area compared to the other three regions [48][49][50][51][52][53][54][55][56][57][58].

Scenario IV (Consideration of Carbon Dioxide Emission).
It was reported that Saudi Arabia's government showed an interest in applying taxes to carbon dioxide (CO 2 ) emission from PPs, though the time for enforcement has not been specified [83]. Subscenarios III-1 to III-3 were expanded to Subscenarios IV-1 to IV-3 by applying an additional constraint of the greenhouse gas emission cost into the MESSAGE tool to compare the relative impact of CO 2 taxation to alternative nuclear energy development programs.
In this study, we assumed that the taxation for CO 2 emission results in when all types of new candidate PPs were predicted to be introduced to Saudi Arabia (see Section 3.3). As such, operators of PPs should pay CO 2 emission tax for the electricity produced thereafter, which may affect any type of technology's economic feasibility depending upon the CO 2 emission rate from a specific type of PP. e CO 2 emission tax for technology can be calculated by the following equation [88]: where T C,k is the CO 2 emission tax for technology k (U$/ MWh), EF k is the emission factor for technology k (ton of CO 2 /MWh), and carbon is the carbon cost (U$/ton of CO 2 ) for which the average value of forecasted carbon cost in 2030, 37.5 U$/ton of emitted CO 2 , was assumed for simplification in this study [88][89][90][91][92].

Levelized Unit Energy Cost.
A LUEC was calculated by the G4-ECONS tool for each possible option in the nuclear power fleet (i.e., APR-1400, SMART-100, or a combination of APR-1400 and SMART-100). e LUEC was compared to the results from the MESSAGE simulation. is was performed to verify the results from the MESSAGE tool, which provides an optimal option by minimizing a complicated objective function. In this study, a LUEC of a type of nuclear reactor, R, for the whole lifetime was discounted to the 2015 base year and was calculated using (2). In (2), the NPP was assumed to be constructed at the initial time of the project, and the interest during construction was taken into account. e interest during construction (IDC) with nominal discount rates for the capital cost was 2.1% and 2.5% for the decontamination and decommissioning (D&D), respectively, using the following equation [41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58]: where C AC is the annual capital repayment cost, C O&M is the annual operation and maintenance cost, C F is the annual fuel cost, C D&D is the annual decontamination and decommissioning cost sinking fund contribution, P net is the net electrical capacity (MWe) or the total useful energy for a cogeneration plant, including the thermal energy expressed in MWe, and L F is the load factor: where IDC is the interest accrued during construction, m is the monthly interest rate, and it is the number of months to construct.

Overall Approach and Procedure of is Study.
e major steps taken in this study were (i) data collection, (ii) preparation of input data based on the protocol of MES-SAGE tool, (iii) establishment of long-term electric power development scenarios encompassing a variety of possible options in Saudi Arabia, (iv) simulation with the MESSAGE tool, (v) analysis of the results from the MESSAGE tool combined with a manual calculation of the LUEC, and (vi) derivation of the main findings and insights. e overall approach and procedure employed in this study are depicted in Figure 2.

Results and Discussion
Scenarios I, II, III (III-1, III-2, and III-3), and IV were simulated using the MESSAGE tool. e simulations included relevant assumptions and input parameters detailed in Tables 1 to 7. ese simulations were performed to formulate an optimal long-term energy supply strategy, which could meet the electricity demand of Saudi Arabia from 2015 to 2050.

Scenario I (Reference Energy Supply). Scenario I was simulated by the MESSAGE tool.
e calculated optimal electricity capacity (vertical bar) of each technology and the peak demand (pointed solid line) for every five years starting in 2015 are shown in Figure 3. ese results indicated that the electricity shortage would begin to occur in 2025 and continue to the end of the simulation (i.e., 2050). e electricity shortage rate was defined as the electricity gap (i.e., the electricity demand and the actual electricity supply divided by the electricity demand) [94]. e electricity shortage rate was estimated as a percentage. e electricity shortage rate started at 27.1% in 2025 and increased to 96.2% in 2050, as shown in Figure 4. e total installed capacity of 73.3 GWe in 2015 is predicted to decrease to 15.1 GWe at the end of 2050. e decrease in the total installed capacity was due to the gradual retirement of existing PPs, which were Science and Technology of Nuclear Installations assumed not to be refurbished in Scenario I (see Section 2.4.1). Scenario I was determined not to be a sustainable long-term energy option for Saudi Arabia.
Moreover, Scenario I predicted that gas turbine (GT) PPs would be the major energy technology in Saudi Arabia until 2035. Steam turbine (ST) PPs became the majority thereafter, and diesel generator (DG) PPs showed the smallest share of the capacity throughout the timeframe.
is finding was attributed to more GT-PP units reaching the design lifetime earlier than the ST-PPs from 2015 to 2035. e highest share of the GT-PPs was attributed to the highest number of available GT-PPs (i.e., 653 units as of  2015) among the total number of existing PPs (i.e., 947 units as of 2015) [5]. e lowest share of DG-PPs was attributed to the comparatively high fixed and variable operation and maintenance costs of DG-PPs compared to the other existing technologies, as shown in Table 2. Figure 5 shows the MESSAGE tool calculation results from Scenario II. Scenario II assumed that the existing PPs were maintained and upgraded to higher efficiency and continued to operate until they reached the original design lifetime (see Section 2.4.2). e installed electricity capacity as of 2050 (i.e., the end of the timeframe of this study) for Scenario II was predicted to reach the maximum 244.6 GWe, whereas a much smaller capacity of 15 GWe was predicted in Scenario I. e future electricity shortage predicted in Scenario I was solved and/or mitigated to some extent in Scenario II. Scenario II predicted that the estimated EPD could be covered until 2035, as shown in Figure 5. For Scenario I, the electricity shortage was expected to begin in 2020, as shown in Figure 3. In Scenario II, the electricity shortage rate was estimated to be 6.8% in 2040 and reach 33.8% by the end of 2050, as shown in Figure 4. us, Scenario II showed a reduction in the shortage rate (i.e., mitigated) of 81.2%, 90%, and 94.2% for 2040, 2045, and 2050, respectively, compared to Scenario I.

Scenario II (Rehabilitation of Existing PPs).
is study calculated 371 units of PPs (262 units of GT-PPs, 59 units of ST-PPs, 43 units of DG-PPs, and 7 units of the combined cycle (CC) PPs would be rehabilitated and upgraded during the timeframe of this study) [6]. e incremental capacity of Scenario II incremental capacity is compared to the incremental capacity of Scenario I in Figure 6. It was predicted that both GT-PPs and ST-PPs would be two major technologies, and the capacity of the ST-PPs would increase continuously within the timeframe of this study. As shown in Figure 5, the capacity of the GT-PPs would be higher than other available technologies from 2015 to 2045 and then decrease to the capacity of the ST-PPs. is indicated that GT-PP was the major existing technology in 2015. e number of GT-PP units needing rehabilitation by 2050 (i.e., 262 units) is higher than any other types of PPs considered in this study. Moreover, the highest share of the ST-PPs in 2050 was attributed to the longer lifetime of ST-PPs compared to the lifetime of GT-PPs (see Table 3).

Scenario III (Introduction of New Energy Technologies, including NPPs).
e MESSAGE tool calculation results for the three Subscenarios III-1, III-2, and III-3 (see Section 2.4.3) are discussed in this section.    e share of new technologies was forecasted to increase gradually. SL-PP, A-GT-PP, A-CC-PP, WD-PP, and A-ST-PP were predicted to be the top five major technologies in the future energy system of Saudi Arabia. In Subscenario III-1, the first NPP unit (i.e., APR-1400) would be introduced around 2030. Its capacity and share would increase from 4.2GWe and 2.8% in 2030 to 16.8GWe and 3.8% in 2050, as shown in Figure 8. Moreover, nuclear power would be the sixth-largest capacity by the end of the study, as shown in Figure 9. e share of two conventional technologies (i.e., CC-PP and DG-PP) was predicted to decrease throughout this timeframe of the study.

Subscenario III-2 (New Energy Technologies including SMART-100 as the Only Type of Nuclear Power).
In Subscenario III-2, the nuclear power (i.e., SMART-100) would contribute a capacity of 0.8GWe and 0.5% share in 2030 and reach 6.2GWe and 1.4% share by 2050, as shown in Figures 10  and 11. In Subscenario III-2, the SMART-100 reactor ranked eleventh in 2050 as shown in Figure 12 in Subscenario III-2. e reduced competitiveness of the SMART-100 reactor over the other candidate technologies in Subscenario III-2 compared to Subscenario III-1 was attributed to the high capital cost of the SMART-100 reactor compared to the APR-1400 reactor. e uncertainties and implications of the high capital cost of the SMART-100 reactor are detailed in Table 4 and were thoroughly reviewed and discussed in Section 3.3.4. Moreover, the water desalinated by a Cog-SMART-100 would be able to cover 123.7 Mm 3 .
is is approximately 4% of the desalinated water demand per unit. All of the Cog-SMART-100 units would be able to cover 9151.8 Mm 3 , which is approximately 80% of the amount of desalinated water demand by 2050, as shown in Figures 13  and 14.

Subscenario III-3 (New Energy Technologies including a Combination of APR-1400 and SMART-100 as the Nuclear Power Reactors).
e calculation results from Subscenario III-3 are shown in Figure 15. In Subscenario III-3, the combined nuclear fleet of APR-1400 and SMART-100 reactors was assumed to be available starting in 2030. e highest capacity and share of nuclear power as of 2050 was predicted for Subscenario III-3 compared to Subscenario III-1 and Subscenario III-2, as shown in Figure 15.
Afterward, the relative capacity and share of the combined nuclear fleet increased continuously to ranking sixth with an installed capacity of 18.9 GWe and a 4.3% share by the end of 2050, as shown in Figures 16 and 17. e share of two conventional technologies (i.e., CC-PP and DG-PP) was predicted to decrease throughout the timeframe of the study (i.e., 13th and 14th ranked). e majority of the nuclear capacity was supplied by the large NPPs (i.e., APR-1400). e total capacity contribution of the APR-1400 reactor in the combined nuclear fleet was calculated as 2.6% and 4.2% for 2030 and 2050, respectively. e total capacity contribution of the SMART-100 reactor in the combined nuclear fleet was calculated as 0.19% and 0.16% for 2030 and 2050, respectively.

Further Discussions on the Relative Competitiveness of Nuclear Power in Subscenarios III-1 to III-3.
e installed capacity of the nuclear power in the Saudi Arabian energy system from 2025 to 2050 calculated for Subscenarios III-1,   2050, the MESSAGE tool's predicted capacity of the combined fleet was higher and later reduced to the capacity of only using the APR-1400 reactor. is was attributed to the differences in total costs and other nonmonetary terms between the two options considered by the MESSAGE tool. e predicted composition (or ratio) of the reactor design in Subscenario III-3 by the number of units of NPPs is shown in Figure 19. e predicted capacity of the combined fleet predicted was only higher than the capacity of the APR-1400 reactor. is was attributed to the differences in total costs and other nonmonetary terms between the two options considered by the MESSAGE tool.
In this study, the calculated LUEC for the APR-1400 reactor (42.3 U$/MWh) was slightly higher than the reported values (22.1 to 34.1 U$/MWh) [50,94]. However, the calculated LUEC for the SMART-100 reactor (44.3 U$/MWh) was within the range of the reported values (42 to 78 U$/MWh) [94][95][96][97][98][99]. In general, the calculated LUECs for the nuclear energy technologies calculated in this study were comparable to those reported in previous studies. e gaps, including overestimation of the LUEC for the APR-1400 reactor, were attributed to different parameter values, including cost elements and assumed conditions [51]. Furthermore, the increasing

18
Science and Technology of Nuclear Installations   calculated LUEC for the combined nuclear fleet of APR-1400 and SMART-100 reactors (65.1 U$/MWh) was 35% higher than the calculated LUEC of only using the APR-1400 reactor (42.3 U$/MWh). Additionally, the IDC showed little effect on the LUEC (i.e., increasing the IDC percentage). e IDC caused a slight reduction in the LUEC, as shown in Figure 21.
However, this reduction did not affect the LUEC for all types of reactors. Even if the reason for the discrepancy could not be specified, it was attributed to additional factors. For example, the region-by-region data used in the MES-SAGE tool (see Table 2) may have induced discrepancies in the simplified LUEC calculations that would not have occurred if a national level calculation was performed. In contrast, it might have been necessary to differentiate already commercialized NPPs (e.g., the APR-1400 reactor from the SMART-100 reactor) which has not yet been constructed compared to the relative feasibilities of the nuclear fleet. e potential reduction in the capacity of the SMART-100 first-of-a-kind nuclear reactor was assumed to occur after commercialization [48,50,51,91,93]. Capital costs and the operation and maintenance costs of the APR-1400 reactor can be confidently constrained in a range based on previous construction and operation experiences. us, the LUECs for the combined nuclear fleet were further estimated by varying the capital cost of the SMART-100 reactor, while other cost factors were kept fixed, as detailed in Table 4. e composition of the reactor designs is shown in Figure 22. e LUEC of the combined nuclear fleet slightly decreased with a reduction in the capital cost of the SMART-100 reactor. e slope of the LUEC was slightly steeper for a higher number of APR-1400 units than SMART-100 units (i.e., they appear as the same line). e economic feasibility of the combined nuclear fleet and the single APR-1400 reactor in terms of LUEC were reversed in the ranged from 2487.3 to 2822.7 U$/MWe of the capital cost of the SMART-100 reactor (i.e., 71.8%-75.1% lower than the reference value listed in Table 4). Below 2822.7, the combined nuclear fleet became more feasible, at least in terms of economics (i.e., LUEC). e capital cost reductions were higher than the reported expectation of capital cost reduction for the SMART-100 reactor (i.e., 15%-55%) [51][52][53][54][55][56][96][97][98][99]. For reference, the MESSAGE tool predicted that a higher installed nuclear capacity in Subscenario III-3 than in Subscenario III-1.
is prediction would change if the capital cost of the SMART-100 reactor exceeded 10000 U$/MWe (i.e., 9.3% higher than the reference value in Table 4). If that occurred, additional factors would have been taken into consideration.

Scenario IV (Consideration of Carbon Dioxide Emission).
e CO 2 emission tax for a power plant was calculated using (2). e CO 2 emission tax was additionally reflected in the Subscenarios III-1, III-2, and III-3. Subscenarios IV-1, IV-2, and IV-3 were established. However, SL-PP, WD-PP, and NPP turned out to be positively affected by the CO 2 emission tax policy and decreased during the years 2030 to 2050. Specifically, SL-PP increased from 2.2 to 16.7 GWe, WD-PP increased from 1.8 to 7.9 GWe, PSH-PP increased from 0.3 to 1.9 GWe, and NPP increased from 1.7 to 14 GWe. However, the shares of ST-PP, DG-PP, CL-PP, GT-PP, and CC-PP decreased with CO 2 taxation. e CO 2 taxation for Other studies [91] Other studies [93] [ is study] Other studies [47] Other studies [91] [ is study] Other studies [68] SMART-100  each nuclear power option's installed capacity was simulated using the MESSAGE tool.
e results are displayed in Figure 23.
As shown in Figure 23, the CO 2 taxation policy increased the capacity of all nuclear power options from 2025 to 2050 in Subscenarios IV-1, IV-2, and IV-3 in the range of 8% to 74%. For example, the CO 2 taxation caused expansion of the installed capacity by 67.8% of the single APR-1400 in Subscenario III-1 and 74.1% of the combined nuclear fleet in Subscenario III-3.

Conclusions
A simplified energy system diagram for Saudi Arabia was established and implemented by collecting the national energy resources distribution system and the energy policy, including the NEDRM and other analyses. In Saudi Arabia, the 2015 EPD of 56.7 GWe as of 2015 was estimated to gradually expanded to 392.4 GWe in 2050. e following scenarios were modeled using a well-known MESSAGE tool to investigate the optimal electricity supply options for Saudi Arabia: (1) reference supply scenario, (2) rehabilitation scenario, and (3) adoption of new energy technologies after 2020 and introduction of nuclear power after 2030 scenario. It was shown that the present Saudi Arabian energy system could cover the predicted electricity demand through 2025 but would experience blackouts thereafter. e rehabilitation of existing PPs could postpone the possible electricity shortage by approximately ten years. However, simply rehabilitating the existing PPS cannot meet the future EPD in Saudi Arabia. e EPD in Saudi Arabia was predicted to continuously expand until the end of 2050 (i.e., the end of this study's timeframe). It was also shown that introducing various candidate new energy technologies, including nuclear power, was needed to generate a sustainable electricity supply in the future for Saudi Arabia. It was predicted that solar, advanced gas, wind, advanced steam, and advanced combined cycle would be the top five major energy technologies in the future. In this study, nuclear power ranked eleventh, and the installed capacity ranked sixth by the end of 2050. Four subscenarios that assumed a single reactor design (i.e., APR-1400 only or SMART-100 only) and a combined nuclear fleet of APR-1400 and SMART-100 were simulated using the MESSAGE tool to investigate a more strategic nuclear program for Saudi Arabia. e simulation predicted that the combined nuclear fleet would show the highest installed capacity, followed by APR-1400 only and SMART-100 only. e decreasing order of capacity for APR-1400 only and SMART-100 only results were partially verified by calculated LUEC for each reactor design generated by the G4ECONS tool. However, the approximately 35% difference between the capacity of the combined nuclear fleet and the single APR-1400 reactor could not be interpreted only in terms of the LUEC. e calculated LUEC for the combined nuclear power option exceeded the LUEC for the APR-1400 only scenario by approximately 35%. However, the exact reason for the approach feasibility of the combined nuclear fleet could not be interpreted. However, it was proposed that the approach feasibility of the combined nuclear fleet's installed capacity could be partially demonstrated in terms of LUEC if the capital cost of the SMART-100 reactor was within the range of (2487.3 to 2822.7 U$/MWe).
is finding is consistent with reported studies on the potential reduction in capital cost of a SMART-100 first-of-akind power plant, after commercialization. Investigation into the potential impact of greenhouse gas taxation policy on each candidate energy technology determined that the capacities of new technologies (e.g., solar) would be the most positively affected by the CO 2 taxation. Nuclear power ranked as the second most positively affected technology by CO 2 taxation. During this study's timeframe, nuclear power showed an 8 to 74% increase in the installed capacity due to CO 2 taxation. e main findings and implications from this study were (1) the determination of a potentially higher preference for combined nuclear fleet over single reactor design and (2) the possible impact of greenhouse gas taxation policy could be referenced when proposing optimal strategic options for embarking nuclear countries. However, in this study, each energy technology's relative feasibility, including nuclear power, was based on assumed cost-related parameters. ese assumed cost-related parameters are subject to change associated with the uncertainty of the parameter values.

A-CC:
Advanced combined cycle A-GT: Advanced gas turbine A-ST: Advanced steam APR: Advanced power reactor CC: Combined cycle CL: Coal Cr: Crude oil CSP: Concentrated solar power D: Diesel DG: Diesel generator EPD: Electricity peak demand FOM: Fuel, operation, and maintenance GT: Gas turbine GH: Geothermal HFO: Heavy fuel oil LUEC: Levelized unit energy cost LPG: Liquefied petroleum gas MESSAGE: Model for energy supply strategy alternatives and their general environmental impact NEDRM: Nuclear energy development road map NPPs: Nuclear power plants O&M: Operation and maintenance OPR: Optimal power reactor PPs: Power plants PV: Photo voltage PSH: Pump storage hydro REI: Renewable Energy Institute SL: Solar SMART: System-integrated modular advanced reactor ST: Steam turbine WNISR: World nuclear industry status report WNA: World Nuclear Association WD: Wind WT: Waste.

Data Availability
e data used to support the findings of this study are included within the article.

Conflicts of Interest
e authors declare there are no conflicts of interest regarding this article's publication.