Demands on the electrical grid.

One challenge of a rapid transition to EVs in that the transportation sector places significantly more demands on the electrical grid. If the system is not prepared for distribution and demand, implementation might have negative impacts, including overloaded systems. Of the articles covered in the systematic review of the literature, two papers focused on the load that would be applied during charging events for EVs and the problems that this might pose on the grid system [14, 26]. One paper [14] discusses the impact that EVCS have on the grids, offering specific technical recommendations to handle demands as per Qatar Energy & Water Company standards [14]. The main concern of the authors in this paper is the heightened harmonic distortion caused by increased energy demand as charging stations increase the peak current of the electrical grid. Such harmonic distortion can create higher operating temperatures and lead to more frequent equipment failure. To address this potential issue, the authors recommend connecting high capacity EVCS to dedicated feeder stations, while smaller capacity charging stations are capable of being integrated into the existing power grid [14]. Conversely, the second paper [26] discusses the issue of the potential power strain caused by plug-in electric vehicles (PEVs), looking to answer the question of whether Qatar’s power grid can meet the demands required of a 10% PEV penetration rate. Based on normal operations, where peak energy demand occurs in the afternoon and where EV charging takes place at night, the research finds there is plenty of capacity available for both summer and winter months. However, under a worst-case-scenario where all vehicle charging takes place at 2 p.m., the aggregate PEV load exceeds the generation limit and increases the peak demand by 19.2%. However, the article notes that this is only when considering the current grid operations as of 2019 and does not factor in any power generation from the new 800 MW PV solar farm. If this source of electricity is taken into consideration, peak electricity generation will be misaligned with peak electricity demand and therefore to best make use of this energy surplus they recommend charging vehicles between 5 am and 11 am. This would reduce the peak demand induced by EVs, flatten the demand curve, and reduce the requirements of natural gas generators as an auxiliary power source. The author further investigated the energy cost of transitioning Qatar’s consumer vehicle fleet to all electric. When considering the 2019 power generation peak capacity of 8.5 GW, the daily spare capacity would be 0.035 TWh during peak consumption events, which would allow PEV penetration of up to 85% if energy usage was optimized. This suggested optimization would be in the form of smart charging algorithms designed to equalize power consumption throughout the day. The simulations did not, however, model different vehicle segments. It also did not consider driving habits and parking statistics. As a result, the energy demand of PEVs could increase or decrease depending on these factors (e.g. synced daily driving habits spurred by commuting may lead to high demand in the morning while spaced out driving and parking may better spread the load, larger vehicles may require more energy during a charging event). To address these gaps, the researcher recommends experimental studies of surveys. Four different strategies for solving the aforementioned issue were found within the literature. These were (a) development of off-grid charging systems to avoid increased strain on the current grid [16–20], (b) diversification of energy production systems to include photovoltaic power generation with the existing grid [10], (c) development of smart charging schedules to temporally spread out the load to be more manageable throughout the day [21], and (d) modeling the spatial arrangement of charging networks to better distribute the load during charging events [4, 11, 12, 28].

The above-noted study [26] mentioned the addition of solar energy inputs to the electrical grid (using 500 MW as an example). Although it is yet to be reported in the academic literature, in 2022, an 800 MW solar power project came online in Qatar, which will cover 10% of peak energy demand in the country [37]. In addition to this, the government has announced that two additional solar power projects will be launched within two years, adding another 880 MW, which will surpass 20% of peak energy demand provided by solar energy [38]. Before the launch of the first major project, researchers had been calling for the development of Qatar’s solar capacity (2). In addition to centralized, large-scale solar power projects, five papers discussed the solution of off-grid EVCS [16–20]. All papers conclude that an off-grid EVCS should include two to three main power sources–solar (PV), wind turbines, and optionally bio-generators–along with some form of energy storage system either in the form of batteries or in the form of chemical storage [16–20]. Four of these papers focus on developing an EVCS that can support 50 vehicles per day [16–20]. This system would require 250 kW of wind turbine produced energy, 450–468 kW of CPV/T, and 10–100 kW of biodiesel [16–20] (see Table 3 for paper by paper breakdown). Additionally, to support charging throughout the night and during unfavorable climactic conditions, some form of energy storage system is recommended. This was frequently a mix of lithium-ion batteries (304–595 kWh) along with electrolysis and storage of hydrogen and natural gas which could be consumed at a later time [16–20]. Two of these four papers explored the cost of one of these systems which placed a system within the range of $2.38 million and $2.92 million with the cost of electricity being between 0.284 and 0.329 $/kWh [19, 20]. A fifth paper explored the development of a EVCS to support 80 vehicles per day [18]. They recommend for the CPV/T of 1,728 kWh/day. They also recommended 250 kW of wind and 654 kWh lithium-ion battery [18]. The assumption of the daily charging demand of each EV in all studies was 35 kWh/day [16–20]. All studies also assumed that 1,500 m2 of space would be required for the EVCS [16–20]. The [19] paper also conducted a life cycle cost analysis, which determined the upkeep cost of each system component over the course of its lifetime.

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Table 3. A comparison of proposed off-grid EVCS.

https://doi.org/10.1371/journal.pclm.0000271.t003

On the other hand, only one paper discussed the solution of diversifying Qatar’s existing energy production systems to include photovoltaic (PV), concentrated photovoltaic (CPV), and wind turbine power generation in order to maximize the benefits received from electrifying the consumer vehicle fleet [10]. Due to Qatar’s geography, solar and wind energy have been identified as the most feasible RES, although the authors also discuss the potential to produce energy by converting waste to natural gas [10]. Two cases of hybrid RES are explored. The first is comprised of wind (1900 MW), CPV (3,180 MW), and a solar thermal storage unit (60 GWh), which would produce 16.89 TWh of energy, 34.9% of total electricity production (TEP) and would result in a CO₂ emission reduction of 31% compared to current power generation [10]. The second scenario involves PV (3,003 MW) and wind (3,392 MW), which would yield 15.42 TWh annually, 31.8% of TEP and a 17.5 MT reduction in CO₂ emissions [10]. This paper also mentions several challenges and limitations to RES development in Qatar, the first being related to the energy storage associated with CSP [10]. While a thermal storage system can double the utilization of CSP, the supply only lasts for a period of 6 to 9 hours, at best [10]. The authors mention that a pump hydro storage system has greater capacity but requires a geographically suitable location [10]. An alternative for long-term storage is liquid fuel (ex. hydrogen) [10]. However, cost and low State-level motivation as a result of energy security remain a challenge [10]. Thus, while a near 100% renewable energy scenario is possible the biggest challenge is energy storage [10]. The authors mention that to achieve the State of Qatar’s target of 20% renewable energy by 2030, no matter which methods are employed, it will cost on average about USD $7 billion over a 10 year period, as of 2021 [10]. The authors suggest that to reach the 2030 targets there needs to be favorable market and political conditions such as low interest loans and research grants [10].

Only one paper discussed the solution of smart charging schedules to temporally spread out the load to be more manageable throughout the day [21]. Using an optimization approach that aims to identify the least cost options, the model was tested on a cluster of six-buildings at Qatar University and was able to strategically reduce the operation cost by 21.04%. They did so by thermally mapping each building to determine strategic locations to deploy HVAC as required as well as to redirect cool air from lower occupancy areas to ones of higher occupancy. They also modelled the management of a flexible load system involving both the buildings aggregate flexible loads as well as EV loads to avoid peak price spikes and huge demand charges. By managing both the time of use of electricity as well as the location of cooling within buildings, the latter being a major electrical demand in the country, operations can distribute demand and increase overall energy efficiency.

Spatial distribution of EVCS.

As alluded to in the above-mentioned studies, the distribution of EVCS has an impact not only on accessibility and uptake of EVs, but also on electrical demand. Four articles discussed the solution of modeling the spatial arrangement of charging networks to better distribute the load during EV charging [4, 11, 12, 28]. In order to determine the optimal locations for EVCSs, Zafar et al [4] tracked the driving habits of 7 vehicles (6 ICV, one BEV) to understand driving habits and energy consumption in Qatar. Regardless of workweek or weekend scenarios, charging at home was deemed to be the most convenient, which implies that capacity in the private sector needs to be sufficient to meet the demand of EVCS at homes. As the driving habits of both vehicle types (ICV and BEV) involved extended periods of parking, the authors suggest that a level 2 charger would be sufficient, although they also recommend investigating the installation of fast chargers at shopping malls as these parking events are much shorter [4]. The intensity and/or frequency of driving patterns impacts how dense the EVCS network needs to be, and thus Zafar et al also assessed the daily driving distances of drivers and found that nearly 80% of all ICV daily trips are less than 100 km and only 3% of trips are higher than 200 km [4]. These averages, however, were much lower for the EV, which they posit was likely due to range anxiety [4]. The daily trip is about 19 km and 80% of the trips are less than 26 km even though the vehicle in question has an advertised range of 299 km [4]. Due to these low mileage trips the researchers inferred that the owner used a separate petrol car to complete other longer trips [4], however the short trips are also due to the concentrated nature of the State of Qatar, with the vast majority of population and economic activity occurring around the capital city. The authors were also able to compare the fuel efficiency of an ICV and determined a decline of 24% due to AC usage [4]. This range reduction is likely higher for EVs although it should be investigated further to better understand [4]. The results of this study suggest that EVCS distribution could be optimized at locations where people are parked for longer durations, at homes (which would require charger installation) and at public locations (e.g., malls) and work places (where EVCSs could be installed by the government and private sector). These two approaches require different types of capacities (individual home installation and public providers), both of which may require support in the initial stages of EV expansion.

Abdullah et al [11] developed a framework for determining the best locations for chargers, using a case study of Qatar University. To successfully determine the best spot for charger placement the author recommends following these steps: (1) “define the project goals and objectives,” (2) “define the potential sites (alternatives) and associated attributes,” (3) “identify which criterion is more important than another with the help of experts and decision-makers,” (4) “solve for the EV placement,” and (5) “sensitivity analysis” [11]. The authors also recommend revaluating the best spots for EV placement following each installation as the attributes will change. A second paper by Abdullah et al [12] also focused on the implementation of EVCS at Qatar University, it forecasts the average number of EVs on campus, recommend the optimum number of chargers each year, solar power plant sizes, and required policy. To do this, the model applies a system dynamic approach initially developed by Forest and colleagues at MIT in the 1950s where variables are classified as either as either belong to reinforcing (positive feedback) look or balancing (negative feedback) loops. The specific case study is informative for the State of Qatar, however additional studies are needed that examine EVCSs at a broader scale. Finally, Sultana et al. [28] used a particle swarm optimization algorithm to determine where on an IEEE-37 bus system EVCS can be placed with minimal energy loss. They determined the best location is bus 19. Additionally, adding a solar PV system to the grid can reduce the cost of lost energy by 29% and actual power loss by 70%.

Life cycle assessments.

The other major subset of articles in the systematic review were life cycle sustainability assessments of various vehicle types (ICV, HEV, PHEV, BEV) and models (SUV versus sedan) [1, 3, 13, 24, 25]. All the papers concluded that EVs are better in all environmental impact categories asides from water withdrawal and water consumption [1, 3, 13, 24, 25]. However, this is only due to Qatar’s reliance on natural gas as the primary source of electricity generation. If Qatar were to transition towards solar water withdrawal and consumption that factor would be reduced and/or be negligible. The studies also concluded that economic benefits, which are very closely tied at the moment to fossil fuel production, result in ICVs being favored within this category as only the current economic landscape of Qatar is taken into account, not any future diversification that would occur due to electrification [1, 3, 13, 24, 25]. The same can be said for the social indicators considered, which includes total tax, employment compensation, employment, and human health impacts [1, 3, 13, 24, 25]. As the first three indicators are directly tied to fossil fuel production, the reduction in fossil fuel consumption associated with EV uptake will have a direct negative effect on these categories. The articles again do not mention or take into account any future opportunities electrification would create, a limitation of the studies. Human health impacts, however, were positively correlated with the adoption of EVs as they reduce emissions [1, 3, 13, 24, 25]. As a result, in the short term the main recommendations were that a mix of HEVs and BEVs be used while Qatar’s electricity is generated by natural gas [1, 3, 13, 24, 25]. As this changes in the long term from natural gas to solar, however, a complete conversion to BEVs is optimal [1, 3, 13, 24, 25]. An important caveat to these findings, however, is that these studies results were likely found prior to Qatar’s large solar projects being connected to the grid. The assumption that natural gas would continue to provide 99% of the power to Qatar’s grid was one that was considered long-term but, Qatar is now quickly moving away from natural gas as a power source for their grid. 10% of the electrical grid is now powered by solar and this number is expected to increase to 20% in the next two years.

Al Mamun et al. [15] discuss the benefits and drawbacks of electric, hybrid, or conventional ICV taxis as well as the public acceptance of electric buses which will not be focused on as it is outside the scope of this study. In regards to taxis, Al Mamun et al. [15] states that after 10 years of use or 150,000 km, HEVs become cheaper than both ICVs and BEVs. It was also found that HEVs can reduce emissions by 37.85% compared to ICVs no matter the electricity generation scenario of the country. As a result, HEV taxis have several advantages over the use of ICVs as taxis, namely fuel efficiency, decreased costs, reduced emissions, as well as extended range having to be fueled less frequently due to regenerative breaking. The authors also highlight that this switch to HEV taxis can occur in the short-term given that taxis on average only last 3–6 years before needing to be replace at which time they could be replaced by HEVs.

Knowledge, attitudes, and behaviors.

The dimensions of EVs, EVCS, and load capacity of the electricity grid have been largely technical assessments. However, the transportation transformation in Qatar also requires shifts in knowledge, attitudes, and behaviors. Only two articles [6, 23] discusses the social side of EV adoption. Al-Buenain et al [6] interviewed consumers and found that the majority preferred ICVs for their commute. Furthermore, it was found that these same consumers would require convincing to purchase an EV despite believing EVs could compete with ICVs. Current government incentives were also not sufficient to encourage adoption. Khandakar et al [23], on the other hand, conducted a survey and categorizes respondents into two groups, non-technical and technical. They defined technical respondents as those who worked in part of the EV industry either directly or indirectly while non-technical respondents did not [23]. The study ultimately found that compared to non-technical audiences, technical respondents were more aware of climate change, more willing to work toward a solution, and were more willing to buy EVs despite the higher purchasing cost and lower range, and instead being more swayed by the long-term savings of EVs through reduced maintenance and charging costs. Additionally, technical respondents were more persuaded by possible government incentives such as free charging, subsidized replacement parts, and purchasing bonuses. Overall, non-technical respondents had more neutral responses, likely due to a lack of understanding of climate change as well as the potential of EVs as a solution. Therefore, in order to increase uptake the researchers recommend enhancing public awareness through the development of a mobile app which disseminates information regarding EVs and their benefits, give information on nearby EVCS and allow users to reserve spots to increase convenience [23]. The authors also recommend the implementation of government incentives such as those outlined above along with allowing EV users to feed any unused power back into the grid for profit [23]. Finally, they also mention that having sufficient EVCS is pertinent in achieving greater adoption by the general public [23].