Feasibility of Large-Scale Electric Vehicle Deployment in Islanded Grids: The Canary Islands Case

Abstract

The present integration of electric vehicles into everyday life has the potential to redefine current standards of urban mobility. However, the territorial impact of this deployment demands a multiscale effort to ensure both efficient and sustainable performance; this is even more necessary in a disconnected system like an island. This article addresses the possibility of transforming the existing fossil-fuel-based infrastructure within Europe’s outermost regions into an electric vehicle charging network, with particular emphasis on the Canary Islands’ strategic plans. Using official datasets from Red Eléctrica de España (REE), IDAE, and the Canary Islands’ Energy Transition Plan (PTECan), we develop three scenarios (2025 baseline, 2030, and 2040) to quantify the additional electricity demand, peak load requirements, charging infrastructure needs, and associated greenhouse gas emissions. The methodology combines EV fleet projections, the driving patterns of residents and tourists, and vehicle efficiency data to estimate yearly electricity demand and hourly charging loads. The carbon intensity profiles of each island’s grid are used to calculate well-to-wheel emissions of EVs, benchmarked against internal combustion engine vehicles. The results indicate that achieving 250,000 EVs by 2030 would increase electricity demand by 1.1–1.4 TWh/year (+8–12% of current consumption), requiring approximately 25,000–30,000 public charging points. EV emissions range from 90 to 150 gCO₂/km depending on charging time, compared to 160–190 gCO₂/km for ICE vehicles. Smart charging and vehicle-to-grid integration could mitigate 15–25% of peak load increases, reducing the curtailment of renewables and deferring grid investments. A comparative analysis with Zealand highlights policy synergies and differences in insular versus continental grids. The findings confirm that large-scale EV adoption in the Canary Islands is technically feasible, but quite difficult, as it requires the deep, coordinated planning of renewable expansion, storage, and a charging infrastructure. BEV WTW advantages become unequivocal once the average grid carbon intensity falls below ≈0.8–0.9 tCO₂/MWh, underscoring the primacy of accelerated renewable build-out and demand-side flexibility. Despite uncertainties in adoption and technology trajectories, the approach is transparent and reproducible with official datasets, providing a transferable planning tool for other islanded systems and mainland Europe. The proposed method demonstrates its usefulness in direct linking electrification scenarios with the real capacity of the electricity system, allowing the identification of very critical integration thresholds and guiding evidence-based planning decisions.

1. Introduction

Electric vehicles (EVs) represent a technological revolution compared to internal combustion engine (ICE) vehicles. Although EVs have appeared at various points throughout history, only the recent convergence of several factors has enabled the conditions for mass adoption. First, the development of high-energy-density lithium-ion batteries, initially driven by demand for portable electronics, has provided the autonomy required for EVs to become a viable option. At the same time, private sector leadership, particularly from companies such as Tesla and BYD, has generated social momentum towards cleaner mobility. The parallel expansion of renewable energy sources, which can generate electricity with zero direct CO₂ emissions, has allowed countries to increase their installed capacity and reduce the carbon intensity of their power systems. In this context, governments worldwide have implemented policies to curb emissions from private users, with a special emphasis on energy efficiency in both buildings and transport.

These dynamics present unique challenges in outermost and insular regions, such as the Canary Islands or Iceland. In such islanded power systems, the grid is often limited to the boundaries of the island, with no or very limited interconnections with continental systems. This structural isolation constrains their ability to balance supply and demand, even as electricity consumption continues to grow. For example, global electricity demand increased from just above 10,000 TWh in 1990 to nearly 30,000 TWh projected for 2025 [1], with Europe and the United States registering more than 60% growth in the same period (Figure 1).

Despite the increasing attention to electromobility in continental grids, there is a clear research gap regarding quantitative assessments of EV integration in insular and islanded systems. Existing studies often focus on technological potential [2,3], policy frameworks, or renewable integration at a general level, but very few provide a comprehensive quantitative analysis of electricity demand, charging infrastructure, grid emissions, and vehicle-to-grid (V2G) contributions specific to isolated island grids.

The main objective is to evaluate the feasibility of large-scale EV adoption in islanded systems (on the Canary Islands case), quantifying its impacts on electricity demand, charging infrastructure, carbon emissions, and the potential of V2G and stationary storage solutions. In addition, the Canary Islands are compared to Zealand (Denmark), a region with higher EV penetration, to draw lessons on policy design, infrastructure planning, and renewable integration. By addressing this gap, the study contributes novel insights on the transition towards sustainable electromobility in islanded power systems. The previous literature on electromobility has mainly focused on continental power systems [4], where interconnections and large-scale renewable integration mitigate grid stability issues. Studies on islanded systems remain limited, and most of them are descriptive, centred on policy or technical potential, rather than quantitative and reproducible analyses. Very few papers provide island-specific modelling of additional electricity demand, peak load impacts, charging infrastructure requirements, or well-to-wheel (WTW) emissions of EVs under realistic operating conditions.

The aim of this research is to evaluate the technical and environmental feasibility of a large-scale adoption of electric vehicles in island electricity systems, taking the Canary Islands archipelago as a case study. The work seeks to quantify the associated impacts in terms of electricity demand, charging infrastructure, emissions, and system stability, also integrating the role of storage and smart load management strategies. Unlike other existing approaches, which are generally focused on interconnected continental systems or descriptive analyses, this study develops a quantitative methodological framework based on reproducible scenarios, supported exclusively by official data. This approach allows us to explore critical thresholds for the integration of electromobility in isolated grids and provides a transferable tool for energy planning in island territories and European outermost regions.

This paper addresses this gap by applying a quantitative, scenario-based methodology tailored to the Canary Islands. The analysis integrates official datasets (Red Eléctrica de España, IDAE, PTECan, fleet statistics, EAFO) with international benchmarks to project the impacts of large-scale electric vehicle (EV) adoption. Three temporal scenarios are defined—baseline (2025), medium-term (2030), and long-term (2040)—to evaluate electricity demand induced by EVs, peak load increments, charging infrastructure requirements (slow and fast), and well-to-wheel (WTW) CO₂ emissions under distinct charging profiles. The grid-level analysis accounts for island-specific carbon intensity and assesses the mitigation potential of smart charging, vehicle-to-grid (V2G), and stationary storage. In addition, the methodology incorporates a comparative benchmark with Zealand (Denmark), a region with higher EV penetration and advanced renewable integration, to contextualize findings and derive policy-relevant insights. Overall, the framework provides a structured, reproducible basis to quantify the technical and environmental feasibility of electromobility in isolated island grids. We focus on Spanish islanded grids, as the outermost regions of Europe, where small isolated systems, weak meshing, and limited interconnection drive higher marginal emission factors and operational constraints, making EV deployment a distinct planning challenge. EU policy treats islands as specific clean-energy use cases. While existing work emphasizes policy and technology perspectives, this paper contributes a quantitative, island-specific assessment that links EV deployment to grid stability, emissions, and infrastructure planning. This methodological framework provides a structured basis to quantify the technical and environmental feasibility of implementing electromobility in isolated island grids.

2. Current Constraints of the Canary Islands’ Power System for Electromobility

2.1. Regulatory Framework

The development of electromobility in the Canary Islands is determined by a multi-level regulatory framework, ranging from European Union legislation to regional strategies [5]. At the national level, legislation has laid down the fundamental principles for the deployment of charging infrastructure, whereas the Canary Islands have adapted these principles to the specific geographical and energy circumstances of the archipelago, with a view to promoting the integration of renewable energy sources and ensuring adequate coverage in both touristic and rural areas. The regulation of electromobility in the Canary Islands is embedded in the European Union’s strategy for the decarbonization of the transport sector. Of particular relevance is the Directive (EU) 2014/94 on the deployment of alternative fuels infrastructure, which sets minimum requirements concerning the installation of recharging points and their interoperability. This Directive has been instrumental in the planning of charging networks across the Member States. More recently, Regulation (EU) 2023/1804, adopted under the “Fit for 55” package, has introduced more stringent obligations for the rollout of publicly accessible recharging stations, thereby ensuring the establishment of a denser and more accessible network along the core road corridors of the European Union. Although the Canary Islands are not part of the Trans-European Transport Network (TEN-T), this regulation nonetheless provides the legislative basis for the development of recharging infrastructure across Spanish territories as a whole.

At a national level, the principal legal instrument governing the deployment of charging infrastructure is Law 7/2021 on climate change and energy transition, which imposes the obligation to install recharging points in non-residential buildings and in fuel stations exceeding a minimum sales threshold. Furthermore, Royal Decree 29/2021 has simplified the authorisation procedures for the installation of publicly accessible charging points, removing several administrative barriers. Royal Decree 1053/2014, which approved the Complementary Technical Instruction (ITC) BT-52, remains a cornerstone in regulating the installation of charging infrastructure for electric vehicles in buildings and parking facilities. In addition, incentive schemes such as the MOVES III Programme, managed by the Institute for Energy Diversification and Saving (IDAE), have played a decisive role in the expansion of charging networks in the Canary Islands, supporting the installation of both public and private charging points.

At a regional level, the region of the Canary Islands has enacted a specific regulatory framework tailored to the particularities of the archipelago. The Canary Islands Energy Transition Plan (PTECan) defines specific objectives for the electrification of transport and the expansion of charging infrastructure [6]. Law 11/2019 on climate change and energy transition in the Canary Islands introduces provisions relating to sustainable mobility, giving priority to the electrification of both public and private transport. Decree 5/2021 on the deployment of renewable energies further encourages the integration of charging points with renewable generation, which is of particular importance in a territory whose energy mix remains highly dependent on fossil fuels. With regard to infrastructure, the Canary Islands Sustainable Mobility Master Plan (PDMSC) establishes guidelines for the deployment of charging points, prioritizing strategic nodes such as airports, ports, and high-density urban areas [7].

Beyond binding legislation, a number of strategic initiatives and non-binding instruments also contribute to shaping the deployment of electromobility in the archipelago. The Sustainable Mobility Pact in the Canary Islands, for instance, constitutes a necessary agreement between public authorities and the private sector aimed at coordinating actions in support of electromobility [8]. As regards financial incentives, in addition to the MOVES III Programme, the Government of the Canary Islands has launched additional support schemes to foster the installation of charging points in tourist and rural areas, where the profitability of such investments is more limited. Likewise, the Island Council of Tenerife, under its “Tenerife 2030” strategy, has promoted initiatives such as the development of “fast-charging corridors” across the island, thereby facilitating the uptake of electric vehicles. Nevertheless, despite the progress achieved in regulatory terms and the availability of financial support, the widespread adoption of electric vehicles in the Canary Islands still faces a number of challenges, notably the need for a denser charging network and the integration of such infrastructure within a sustainable electricity system [9]. Continued progress will therefore depend on the evolution of public policies and on enhanced cooperation between public authorities and the private sector in the years ahead. Despite ambitious regulation, the lack of integration with TEN-T corridors and fragmented implementation limit its effectiveness for island systems.

2.2. Energy Sources

The Canary Islands, with a population of 2,238,754 inhabitants as of 1 January 2024, represent one of the most distinctive regions of Spain and a particularly attractive hub for both national and international tourism [10]. The population is distributed across seven islands, organized into two administrative provinces: Las Palmas and Tenerife. Cities with more than 50,000 inhabitants are mostly concentrated in coastal areas, favoured by trade, tourism, and port infrastructure. Overall, population distribution follows a coastal pattern, with higher densities along the shoreline, while interior areas—especially on mountainous islands such as La Palma and La Gomera—are more sparsely populated and predominantly rural. On smaller islands such as El Hierro and La Gomera, the population is scarce and clustered into small urban settlements (Figure 2).

Due to its insular nature and disconnection from the continental power system, the Autonomous Community of the Canary Islands faces a high degree of energy dependence. Its energy model relies predominantly on the importation of fossil fuels, resulting in elevated economic and environmental costs [11]. Despite recent advances in renewable energy, the energy transition remains a critical challenge for the sustainable development of the archipelago. The Canary Islands’ power system is composed of six independent electrical subsystems, one for each of the main islands, without interconnection between them or with the Iberian Peninsula. This structural isolation leads to reduced grid stability and higher generation costs, as electricity cannot be exchanged between islands or with other regions.

Nowadays, approximately 80% of electricity generation in the Canary Islands derives from fossil fuels, primarily diesel and fuel oil [12]. These fuels are imported, exposing the region to significant vulnerability from fluctuations in international markets and increasing the cost of electricity. In fact, the cost of energy production in the Canary Islands is among the highest in Spain, requiring the Spanish State to subsidize part of the electricity bill to align it with prices in mainland Spain. Although renewable energies have grown considerably in recent years, their contribution to the energy mix remains quite limited. In 2023, renewables accounted for around 20% of electricity production, led mainly by wind and solar photovoltaics. This figure falls short of the targets established by both the European Union and the Government of the Canary Islands for decarbonisation.

Electricity generation in the Canary Islands is thus characterized by a model highly dependent on fossil fuels, driven by its condition as an isolated archipelago. With no interconnections to continental grids or between islands, each of the six main islands operates an autonomous electrical system. Currently, electricity generation is based on two primary sources: conventional thermal power plants and renewable energy [13]. The majority of electricity (around 81% in 2023) is amazingly produced in thermal power plants using fossil fuels, mainly diesel and fuel oil. These plants are distributed across the main islands and operate under a decentralized generation scheme. The principal thermal plants are located in Tenerife (Granadilla and Candelaria), Gran Canaria (Jinámar and Barranco de Tirajana), Fuerteventura (Salinas), Lanzarote (Llanos Blancos), and La Palma (El Palmar). Since transporting fossil fuels to the Canary Islands increases electricity production costs, the Spanish Government subsidizes the excess costs to align final tariffs with those of the mainland. Data from “Mapas de Electricidad” show that the Canary Islands consistently rank among the highest globally in terms of carbon intensity, with emissions reaching up to 900 g of CO₂ per kWh generated. The grid is also highly fragmented, with no interconnections between islands, except for a link between Fuerteventura and Lanzarote.

An exception is the island of El Hierro, largely due to its relatively low consumption. This island, with installed wind power exceeding its average demand, can shift from the lower end of the emissions ranking (when relying on diesel generators in periods without wind) to the upper end, achieving as low as 13 g of CO₂ per kWh on windy days. This variability, dependent on uncontrollable weather conditions, represents both an achievement and a challenge in the pursuit of sustainable and carbon-neutral energy production [14]. When compared with mainland Spain, where 132 GWh of the installed capacity corresponds to an average consumption of 33 GWh (around 25%), the Canary Islands present higher average consumption levels, reaching up to 70% depending on the island. This structural constraint poses a significant challenge for the expansion of electromobility in the archipelago.

Renewable energies are slowly but gradually gaining ground in the Canary Islands’ energy mix, although their contribution remains modest relative to thermal generation. Currently, they represent approximately 20% of electricity production, with official targets of reaching 60% by 2030 and full decarbonisation by 2040.

Among renewable sources, wind energy is the most developed, with farms operating across all islands, particularly in Gran Canaria, Fuerteventura, and Tenerife. Despite high solar potential due to the region’s abundant sunshine hours, solar photovoltaic deployment has progressed at a slower pace compared to wind. In addition to these technologies, the Chira-Soria pumped hydroelectric storage project on Gran Canaria is a cornerstone initiative, designed to store surplus renewable energy during low-demand periods [15] and release it when required. Finally, emerging projects are beginning to explore the potential of wave and tidal energy as complementary sources within the islands’ energy transition pathway. The combination of fossil fuel dependence and lack of interconnections constrains the ability to accommodate additional EV demand without increasing emissions. Figure 3 compares the electricity generation mix in the Canary Islands, mainland Spain, and the EU-27. The Canary Islands remain heavily fossil-fuel-dependent, while the mainland and the EU exhibit significantly higher shares of renewables and nuclear generation.

2.3. Vehicle Fleet and Infrastructure

The central hypothesis underpinning this research posits the possibility of a complete transformation of the vehicle fleet and its associated infrastructure towards a system powered exclusively by electricity. In order to articulate a proposal grounded in current data, the research has obtained quantitative values for the fleet of fossil fuel vehicles (petrol and diesel), alternative fuel vehicles, and electric vehicles projected for the year 2030, by extrapolating future values based on the average growth rate calculated from historical records. According to the Canary Islands Energy Transition Plan (PTECan-2030), the target is for the number of electric vehicles in the Canary Islands’ fleet to reach 225,424 units by 2030 (a figure subject to revision upon the entry into force of new planning instruments) [6,15]. This projection is higher than the values calculated in

Table 1. Actual installed capacity and energy consumption in Canary Islands. Source: Authors.

Island	Installed Capacity	Average Power Consumed	% Use
Gran Canaria	1050 MW	442 MW	42%
Tenerife	999 MW	480 MW	48%
Fuerteventura	175 MW	104 MW	60%
Lanzarote	125 MW	86.7 MW	70%
La Palma	100 MW	22.8 MW	23%
La Gomera	40 MW	28.4 MW	70%
El Hierro	50 MW	9.9 MW	20%

and is therefore adopted as the baseline for this study.

The progressive increase in the number of electric vehicles in Tenerife will translate into a substantial rise in electricity demand (

Table 2. Inhabitants, vehicle fleet (February 2024) and accumulated electric cars (2023) in Canary Islands. Source https://www.fredica.org/es/informe-fredica-sobre-el-parque-movil-de-las-islas (accessed on 17 June 2025).

Island	Inhabitants	Vehicles	BEV
Gran Canaria	869,984	703,204	3500
Tenerife	959,189	798,041	4205
Lanzarote	163,230	141,936	600
Fuerteventura	126,676	101,755	500
La Palma	85,382	80,618	150
La Gomera	22,507	17,046	50
El Hierro	11,786	10,391	18

). Based on PTECan-2030 projections, and taking into account the estimated number of electric vehicles on the island by 2030, electricity demand is expected to increase by 607.08 GWh, representing an approximate growth of 58% compared to current levels of consumption.

The strategic location of charging stations is a decisive factor for the effective adoption of e-mobility, particularly in territories with spatial constraints or fragile power grids. In the case of island systems, spatial optimization models for the distribution of charging points are particularly relevant, as they make it possible to link their deployment with local renewable generation capacity and with the seasonality of tourist traffic [16], demonstrating its versatility by being able to be applied to different models such as battery energy storage systems [17] and its adaptability to articulate with geospatial analysis methodologies [18]. Therefore, to address the study of electric vehicle (EV) charging infrastructure, a mapping exercise has been carried out covering both existing fuel stations and current EV charging points. As shown in Figure 4 and Figure 5, the distribution of fuel service stations follows a pattern similar to population density [19], with greater concentration in urban and coastal areas of islands such as Tenerife and Gran Canaria, where the main cities and transport corridors are located. By contrast, in less populated islands such as El Hierro or La Gomera, fuel stations are fewer and strategically located in the principal urban centres and along major roads. In comparison, EV charging points, although increasing in number, present a less dense and less homogeneous distribution (Figure 4 and Figure 5). While several fast-charging stations have been installed in capital cities and tourist areas [16], rural zones and smaller islands still exhibit limited infrastructure, posing a challenge for widespread EV adoption in the region. This asymmetry in accessibility illustrates the uneven development of both infrastructures: fossil fuel networks remain predominant, whereas electrification is advancing progressively but still faces challenges regarding coverage and availability.

By the end of 2023, the penetration rate of EVs in the Canary Islands stood at just 0.5% of the total vehicle fleet, compared to approximately 0.75% on the Spanish mainland (

Table 3. Evolution of the number of vehicles in the Canary Islands by type of energy, and expected numbers for 2030. Source: Authors, based on data collected by Instituto Canario de Estadística.

Year	Total Vehicles	Gasoline (Except Hybrids)	Diesel (Except Hybrids)	Alternative Energy	Electricity
2012	1,530,317	1,057,910	471,867	540	161
2013	1,520,930	1,042,390	477,481	1059	240
2014	1,534,171	1,042,776	489,766	1629	365
2015	1,566,038	1,059,295	504,453	2290	509
2016	1,613,731	1,084,341	524,027	5183	681
2017	1,673,226	1,122,064	544,598	6564	910
2018	1,726,969	1,157,299	560,358	9312	1346
2019	1,764,754	1,183,325	567,879	13,523	2132
2020	1,772,659	1,183,094	570,709	18,856	3383
2021	1,793,216	1,190,991	573,382	28,843	5276
2022	1,832,798	1,212,389	579,124	43,203	8024
2023	1,869,966	1,225,654	582,896	61,416	11,874
2024	1,900,791	1,240,717	592,987	66,960	12,932
2025	1,931,616	1,255,780	603,708	72,504	13,990
2026	1,962,441	1,270,843	613,169	78,048	15,048
2027	1,993,266	1,285,906	623,260	83,592	16,106
2028	2,024,091	1,300,969	632,391	89,136	17,164
2029	2,054,916	1,316,032	643,442	94,680	18,224
2030	2,085,741	1,331,095	653,533	100,224	19,280

). It should be noted that these figures refer to cumulative totals rather than annual registrations. The Canary Islands also register a particularly high vehicle density, with 828 vehicles per 1000 inhabitants—significantly above the mainland average of 627 vehicles per 1000 inhabitants. The average age of the vehicle fleet is likewise higher than on the mainland: 15.3 years in the Canary Islands compared to 14 years in continental Spain. This highlights the pressing need for a transition towards a newer, safer, and less polluting vehicle fleet. The complete substitution of the current fuel service station infrastructure with electric vehicle charging stations in the Canary Islands is a feasible process, but it requires strategic planning and the progressive adaptation of the islands’ power network. Given that the archipelago depends on a fragmented electrical grid with a high share of renewable energy, it is essential to ensure sufficient generation and storage capacity to meet the charging demand of a fully electric vehicle fleet [17]. This must be achieved while overcoming the structural obstacle of the lack of interconnection between islands, which constrains overall system efficiency and poses a challenge to the implementation of such a transition.

The transition must prioritize the installation of ultra-fast charging points in existing fuel service stations and at strategic nodes such as shopping centres, public parking facilities, and transport hubs. In addition, the distribution model must be adapted to both residential and tourism-related use, promoting the deployment of charging points in hotels and households. To achieve homogeneous coverage, a balanced approach will be required, combining fast charging along road corridors with semi-fast and slow charging solutions in urban and rural environments.

To materialize this transformation, it is essential to adopt a set of technical and regulatory measures. First, the electrical infrastructure must be reinforced through the installation of backup batteries and smart management systems to prevent grid overload. At the same time, it is crucial to establish incentives for private investments in charging stations and to simplify administrative procedures for their deployment (

Table 4. Gas stations and charging stations (March 2025).

	Gas Stations	Charging Stations	<11 kW	11 kW–50 kW	>50 kW
Gran Canaria	75	329	130	120	79
Tenerife	85	396	194	138	64
Lanzarote	25	65	32	18	15
Fuerteventura	20	73	36	16	21
La Palma	15	42	16	23	3
La Gomera	5	19	5	5	9
El Hierro	3	11	2	7	2

). The standardization of connectors and interoperability among operators will ensure a seamless user experience, while the integration of digital payment systems will facilitate access to charging. Furthermore, the development of vehicle-to-grid (V2G) technologies should be encouraged, enabling electric vehicles to return energy to the grid during peak demand periods [9]. Finally, awareness campaigns and training for industry professionals will accelerate the adoption of this new infrastructure, ensuring that the Canary Islands can position themselves as a leader in electromobility among island territories.

With regard to charging points, it can be observed that fast-charging stations account for approximately 20% of the overall network, ranging from 25% to 9% of total charging points depending on the island. On average, there is one charger (of any type) for every 10 vehicles, a ratio that lags slightly behind the Spanish national average of 7 vehicles per charger. The disparity between fossil fuel stations and EV charging infrastructure reveals a structural gap that complicates a rapid transition. Figure 6 projects the evolution of the Canary Islands’ vehicle fleet, highlighting the dramatic increase in BEVs expected by 2030, which will place unprecedented pressure on both electricity demand and charging infrastructure.

2.4. Obstacles to the Deployment of an Efficient Electric Vehicle Infrastructure

The first major obstacle faced in the Canary Islands is the level of CO₂ emissions associated with electricity generation, in addition to the non-regular demand [18]. The excessive dependence on a system based primarily on thermal power plants and diesel engines raises the average island-wide equivalent CO₂ emissions per kWh to levels exceeding 850 g CO₂/kWh during daily operating hours. This constitutes a significant barrier to the establishment of a carbon-neutral mobility network. As an illustrative example, emissions can be calculated for a vehicle model available in petrol, diesel, and electric versions: the BMW 1 Series. According to WLTP cycle values, the electric version has an average consumption of 15.5 kWh/100 km (or 0.155 kWh/km). Considering that electricity generation in the Canary Islands emits an average of over 850 g CO₂/kWh, the resulting calculation is:

0.155 kWh/km × 850 g/kWh = 131.75 g CO₂/km

This implies that, under the current conditions, the emissions associated with operating an electric vehicle may exceed those of a comparable diesel vehicle. Therefore, it is not sufficient to simply propose a charging network capable of servicing the islands’ vehicle fleet; parallel measures must also be implemented to support renewable energy integration, with the aim of reducing equivalent CO₂ emissions below the 850 g/kWh threshold. Only under such conditions can total island emissions be effectively reduced in line with sustainable mobility objectives. Figure 7 illustrates the sensitivity of EV well-to-wheel emissions to grid carbon intensity. Only when average intensity falls below ~850 gCO₂/kWh do EVs consistently outperform modern diesel vehicles.

Ultimately, the goal must be to ensure that energy generation systems in the Canary Islands minimize CO₂-equivalent output at all times (

Table 5. Example of emissions calculation for a car with gasoline, diesel, and electric versions. The model chosen is the BMW 1 Series, as this vehicle is offered with all three engines. Source: https://www.bmw.es (accessed on 24 April 2025). Please note that vehicle comparators were initially limited to a single compact model for cross-scenario consistency (pilot). This introduces selection bias; we therefore extend to three archetypes (B-hatch, C-compact, C-SUV) using official WLTP consumption ranges from IDAE. Results are reported per archetype and as a weighted average.

Source	Power	Energy Consumption WLTP	CO2 Emissions
Gas	136 hp	6.4 L/100 km	144 g/km
Diesel	150 hp	5 L/100 km	131 g/km
Electric	204 hp	15.5 kWh/100 km	0 g/km

)—not merely under optimal conditions, as described in the preceding section.

Therefore, the solution to be put forward, as mentioned at the beginning of this document, must come exclusively in the form of a low- or zero-carbon option. However, achieving a fully clean energy solution to unlock the full potential of electromobility in the Canary Islands presents an additional challenge. The islands benefit from between 3000 and 3200 h of sunlight per year (10–15% more than the best-performing regions of mainland Spain) and between 4000 and 5000 h of usable wind resources per year, out of a total of 8760 annual hours. This represents a significant potential advantage for solar and wind power solutions [5]. Nevertheless, more than 40% of the territory is designated as protected land, which makes it impossible to allocate sufficient space (onshore or offshore) for large-scale deployment of either technology. Even under the best-case scenario, renewable resources could cover only about 50% of annual electricity demand. Such a share would still represent a significant step forward, as it would reduce CO₂-equivalent emissions to just over 400 g/kWh.

Peaking plants would, however, continue to be necessary, not only during periods of high demand but also during hours of low wind and limited solar radiation. This dynamic is already observable today on the island of El Hierro, where installed renewable capacity exceeds demand when wind conditions are favourable, reducing CO₂-equivalent emissions to as low as 18 g/kWh. Yet, when the wind ceases, diesel generators become the sole energy source, driving emissions up to 950 g/kWh. Without drastic reductions in grid carbon intensity, EV adoption risks delivering marginal or even negative environmental benefits. These constraints highlight the central research question of this paper: Is large-scale EV adoption in the Canary Islands by 2030 feasible without compromising grid stability or undermining emission reduction goals?

3. Methodological Framework for the Transition to Electromobility in Insular Systems

The development of sustainable urban mobility systems constitutes a strategic pillar in the fight against climate change and in the improvement of quality of life in urban environments. Among the available technological pathways, the electrification of transport through battery electric vehicles (BEVs) has consolidated itself as one of the most promising solutions. This transition is particularly relevant for insular regions such as the Canary Islands, where high external energy dependence, ecological sensitivity, and concentrated urban settlements demand integrated mobility and energy strategies with a strong sustainability component [5].

The geographical and demographic configuration of the archipelago offers favourable conditions for the progressive adoption of petrol-alternative technologies [19], due to the short average distance of daily trips, the presence of multiple compact urban areas, and an expanding installed capacity of renewable energy resources—mainly solar and wind. These create an enabling environment for the deployment of battery-powered electric vehicles. Methodological framework adopted to evaluate the transition toward electromobility in the Canary Islands, rather than following a laboratory-based or experimental design, the study relies on a multi-layered analytical approach that combines the strategic role of batteries as the backbone of electromobility and their integration with the power system is discussed (Section 3.1). Second, the case of Zealand (Denmark) is presented as a comparative benchmark, given its similarities in population and land area with the Canary Islands, in addition to its more advanced trajectory in electromobility and renewable integration (Section 3.2). Third, a transformation strategy tailored to the Canary Islands’ conditions is introduced (Section 3.3). Finally, the analytical framework of the study is defined (Section 3.3.3, Section 3.3.4 and Section 3.3.5), including the quantitative methods employed to estimate EV electricity demand, peak load impacts, charging infrastructure requirements, and well-to-wheel (WTW) emissions under different scenarios.

The scenario-based approach adopted in this paper provides an original contribution to the study of the regional energy transition, by integrating in a quantitative and reproducible way the relationships between electrification of transport, decarbonization of the electricity system, and territorial planning in island contexts. Unlike previous analyses, which focused mainly on technological assessment or regulatory frameworks, this model articulates projections of fleet, electricity demand, emissions and infrastructure needs under different degrees of renewable penetration. This approach allows us to identify critical thresholds of technical and environmental feasibility, providing a dynamic perspective on the interaction between electromobility and sustainability of the energy system. Consequently, the methodological framework developed transcends existing descriptive studies and offers a prospective planning tool applicable to other island territories or those disconnected from the continental network.

3.1. Batteries as the Structural Backbone of the New Electromobility System

Historically, energy storage has been one of the main barriers to the large-scale integration of non-dispatchable renewable energy sources [20] such as solar photovoltaics and wind power. The intermittency of these sources generates imbalances in the grid that can only be mitigated by efficient storage technologies. In this regard, lithium-ion batteries—and their anticipated technological evolutions—enable the coupling of generation and demand in near real time, maximizing the utilization of renewable generation and reducing systemic losses.

Beyond their passive role as storage devices, batteries are increasingly being configured as active nodes within the power system. They can contribute to grid management, frequency stabilization, fast-response services, and direct support to electric vehicle (EV) charging infrastructure; however, they are not the only solution [21]. Through strategies such as vehicle-to-grid (V2G) and battery energy storage systems (BESSs), the traditional centralized energy paradigm can evolve into a distributed, digitalized, and dynamic model. The electrification of transport is among the most robust pillars of global decarbonization strategies, yet its impact extends far beyond the mere substitution of combustion engines with electric motors. Each EV carries a battery that, in addition to its primary role of mobility, can act as a flexible, mobile storage unit capable of interacting with the grid and delivering energy services. The exponential growth of the EV fleet implies an unprecedented increase in distributed storage capacity. If appropriately managed, this mobile battery network could provide multiple services, including the following:

• Energy storage for self-consumption: EV batteries can be used to store surplus photovoltaic (PV) generation during periods of high solar irradiation (e.g., midday) and release it during evening or nighttime hours when demand peaks and renewable production is lower. This functionality not only maximizes local renewable utilization but also reduces dependence on fossil-fuel backup plants. In insular systems such as the Canary Islands, where solar potential is exceptionally high, but grid flexibility is limited, this service can contribute significantly to balancing diurnal load curves.
• Load balancing through smart charging: Intelligent charging strategies (smart charging) allow EVs to avoid creating new demand peaks by scheduling charging sessions during off-peak hours or when renewable generation is abundant. Aggregated across thousands of vehicles, this mechanism can flatten the daily demand profile, reduce stress on distribution networks, and minimize the need for costly grid reinforcements. Advanced control algorithms can further enable dynamic adaptation to real-time grid conditions.
• Ancillary services for the power system: EV batteries, when connected via V2G-enabled chargers, can deliver ancillary services traditionally provided by conventional power plants. These include frequency regulation (rapid injection or absorption of small amounts of power to stabilize system frequency), voltage control (supporting local voltage profiles in distribution networks), and reserve capacity to mitigate sudden fluctuations in demand or renewable generation. In fragile island grids with limited inertia, these services are particularly valuable for maintaining system reliability.
• Emergency response and critical infrastructure support: In the event of grid outages, EV batteries can act as mobile backup sources, supplying electricity to essential facilities such as hospitals, telecommunications infrastructure, or emergency services. Vehicle-to-home (V2H) and vehicle-to-building (V2B) applications enable EVs to provide localized resilience, while larger coordinated fleets could potentially serve as mobile microgrids during extended blackouts. For insular regions vulnerable to climatic and geological risks, this capability enhances energy security and disaster preparedness.

The utilization of electric batteries for vehicle propulsion therefore represents a paradigm shift in the relationship between mobility, energy consumption, and pollutant emissions. The main advantages include the following:

• Reduction in local pollutant emissions. Battery electric vehicles (BEVs) produce no direct CO₂ emissions or other atmospheric pollutants in urban environments, thereby contributing to improved air quality and mitigating adverse impacts on public health.
• Integration with renewable energy sources. Batteries enable the storage of electricity generated from intermittent renewable resources such as solar and wind, facilitating deferred use and maximizing local utilization of these resources. In the Canary Islands, where renewable potential is high and regulatory frameworks actively promote self-consumption, this represents a unique opportunity to progress toward a more self-sufficient and decentralized energy model.
• Energy efficiency: Electric propulsion systems exhibit a significantly higher efficiency than conventional internal combustion engines, resulting in lower overall energy consumption per kilometre travelled.
• Reduction in urban noise: Electric vehicles generate substantially lower levels of noise pollution compared to combustion vehicles, a factor of growing relevance in sustainable urban planning, particularly in densely populated or tourism-sensitive areas.
• Synergies with advanced energy management systems: The integration of electric vehicles with smart grids and bidirectional charging technologies (V2G, vehicle-to-grid) enables more dynamic and resilient management of electricity demand, strengthening system flexibility and supporting higher levels of renewable penetration.

These benefits can only be fully realized through digitalization and interoperability across the energy system, ensuring seamless communication between EVs, charging infrastructures, and grid operators. While both technologies can provide critical services, their systemic contribution differs. EV batteries, due to their scale and mobility, represent a massive potential for distributed storage activated through V2G and smart charging. Stationary BESS, in contrast, offer greater controllability and centralized dispatch. Both are complementary, enabling resilient and low-carbon power systems in isolated island grids, as shown in

Table 6. Comparative services provided by EV batteries and stationary BESSs. Source: Authors.

Service	EV Batteries	Stationary BESS
Energy storage (load shifting)	Yes (through smart charging/V2G)	Yes (direct control, centralized dispatch)
Frequency regulation	Yes (aggregated fleets, V2G)	Yes (fast-response capability)
Voltage support	Yes (localized V2G)	Yes (large-scale voltage regulation)
Black-start/Emergency supply	Yes (vehicle-to-home/critical loads)	Yes (dedicated backup systems)
Mobility support	Yes (primary function of EVs)	No (non-mobile)
Distributed storage potential	Very high (millions of units possible)	Limited (site-specific installations)
Grid integration with renewables	High (when coordinated with smart grids)	High (direct coupling with PV/wind farms)

.

In insular environments such as the Canary Islands, these synergies can play a decisive role in stabilizing fragile power systems with high renewable penetration. By reducing local pollutant emissions, enhancing energy efficiency, and lowering noise pollution, electric vehicles directly improve the urban living environment. More importantly, their capacity to integrate with renewable energy sources and to interact dynamically with the grid through smart charging and V2G technologies enables them to support system reliability under conditions of intermittency. However, these benefits can only be fully materialized through adequate digitalization of the energy system and the establishment of interoperability standards among vehicles, charging infrastructure, and system operators. This requires not only technological innovation but also coordinated governance frameworks that ensure seamless communication across all actors in the electromobility ecosystem. For the Canary Islands, where power grids are small, isolated, and vulnerable to fluctuations, such digital and institutional integration is a prerequisite for achieving a resilient, low-carbon, and scalable model of electromobility

3.2. Case Study: Zealand as Reference for EV Adaptation

The central Islands of Denmark, where Copenhagen is located, have a similar land area as the Canary Islands, and a similar population (

Table 7. Comparative data between Zealand and Canary Islands. Source: Authors.

	Zealand	Canary Islands
Country	Denmark	Spain
Area	7.031 km2	7.493 km2
Population	2.6 million	2.2 million
Population density	370 people/km2	294 people/km2
Number of islands	1 large island and smaller islands	3 main islands and 5 smaller islands

).

Significantly further north in Europe than the Canary Islands, Zealand has experimented with a big transformation within the last decade. Not only they have adopted EVs quickly, they have also changed their energy source. This case study is a good reference for the path that the Canary Islands will walk sooner or later, in addition to showing that this change is perfectly possible, with potential for organic growth. With comparative conditions, the system that has been set up in Zealand could serve as a reference for the Canary Islands in their transformation towards clean mobility and towards a cleaner way of producing energy more generally. Zealand has benefited from a long-term national strategy since the 1990s, establishing clear objectives for the electrification of transport and the expansion of renewable energy generation. Zealand went from 15% renewable energy production in the 90s to over 82% in 2023. This increase follows the general trend worldwide, but the rates achieved are higher than those achieved by their neighbours. The Canary Islands would benefit from a similarly stable political and institutional framework, capable of sustaining long-term decarbonization goals beyond electoral cycles.

The early adoption of renewable energy facilitated the adoption of electric cars during the last decade; Zealand went from under 4500 EVs in 2015 to over 300,000 EVs in 2024 (11.5% of the total), with a total of EVs higher than all the previous 9 years together. One of Zealand’s key strengths lies in its robust investment in charging infrastructure. The region has managed to balance electric vehicle adoption with a proportional rollout of charging stations, including fast and ultra-fast chargers. The infrastructure increased 386% from 2020 to 2023, going from 1 public charger per 20 cars in 2021 to 1 public charger per 12 cars. To compare, right now in the Canary Islands there is 1 public charger per 20 cars, while the current EV fleet represents 1.5% of the total. If the Canary Islands wants to follow Zealand’s numbers, that would mean a fleet of 153,075 EVs (11.5% of the current fleet) and 12,756 public chargers (1/12 cars). Currently, there are 935 chargers in the Canary Islands, so the current network would need to be multiplied by a factor of 13.6. Given the insular and fragmented geography of the Canary Islands, there is an opportunity to deploy an intelligent, well-distributed charging network tailored to urban, rural, and touristic contexts.

In terms of EV penetration (Figure 8), the key indicators of integration were laid out according to an ETL workflow: (i) attain raw data tables from each source; (ii) standardize geography (NUTS/region–island crosswalk), units, and time (calendar year); (iii) remove duplicate points and filter for ‘publicly accessible’ per AFIR; (iv) construct indicators (EV stock share; EVs/point; installed points per 1000 EVs); and (v) run consistency checks (year-to-year deltas, outlier flags, and reconciliation against operator totals).

Another relevant aspect is Zealand’s community-driven approach. In Denmark, local cooperatives often manage renewable energy assets, fostering both citizen engagement and energy ownership. The Canary Islands could replicate this by promoting neighbourhood or municipal energy communities, particularly in residential areas, hotels, and rural towns. Furthermore, Zealand has successfully integrated electric vehicles into its broader energy system [22], leveraging smart charging to align demand with renewable generation. The Canary Islands could go even further by utilizing EV batteries as distributed storage, reinforcing local grids on islands with limited interconnectivity. But this is not so easy: unlike Zealand, the Canary Islands are not connected to a continental grid. This electrical isolation limits their ability to import or export power, demanding a higher level of local energy resilience [23]. Managing the intermittency of solar and wind resources without external support is a critical challenge. Additionally, the insular dispersion of the archipelago presents an infrastructural challenge. While Zealand operates under a single, integrated energy system, the Canary Islands comprise eight major islands, each with distinct energy demands and grid capabilities. This necessitates the development of eight tailored energy transitions, coordinated under a unified regional vision. Tourism plays a major role in the Canary Islands’ economy, causing seasonal and geographic variability in energy consumption and transport needs [24]. Planning for touristic electromobility—such as electric car rentals, hotel charging stations, and zero-emission taxis—must ensure that local grids are not overstressed.

Finally, while Zealand benefits from vast onshore and offshore wind potential, the Canary Islands face geographical constraints. Steep terrain and land-use pressure limit wind turbine deployment, and solar installations must compete with agricultural, touristic, and protected areas (like natural parks), in addition to residential land-uses [25]. While simply copying the system in Zealand would not work for the Canary Islands, we can learn a lot from them. Moreover, if the Canary Islands did try to copy Zealand’s system, they would surpass what Zealand achieved, since the Canary Islands would have to replicate a working model in a much harder environment and maintain energy independence. In this comparison, we see evidence of the structural gap that the Canary Islands must overcome to achieve comparable levels of electromobility. The comparison also allows us to underscore the necessity of parallel strategies: increasing renewable generation to decarbonize EV use, scaling up charging infrastructure proportionally with fleet growth, and fostering policy stability to replicate the long-term trajectory seen in Zealand.

3.3. Calculation of Total Energy Needs

The quantitative estimation of electricity demand for electromobility in the Canary Islands requires a structured, methodological framework combining diverse datasets, scenario building, and analytical modelling. This section defines the approach used to calculate the incremental electricity demand generated by the progressive penetration of battery electric vehicles (BEVs), as well as the implications for peak load, grid stability, emissions, and infrastructure deployment. Data sources are drawn from a combination of national and European institutions (e.g., REE for hourly demand and carbon intensity; IDAE and EAFO for EV performance benchmarks; DGT and ISTAC for vehicle fleet statistics; and manufacturer data for vehicle consumption), complemented by the Canary Islands’ own Energy Transition Plan (PTECan 2030–2040), which sets the regional targets for EV adoption and renewable integration. Based on these inputs, three scenarios are developed: a baseline (2025) reflecting current fleet characteristics and charging infrastructure; a medium-term (2030) scenario incorporating the deployment of approximately 225,000 EVs, a renewable penetration of 60%, and reduced carbon intensity of electricity; and a long-term (2040) scenario, in which BEVs represent the vast majority of the fleet, vehicle-to-grid (V2G) technologies are widespread, and renewable penetration approaches 100%.

For each scenario, the methodology estimates the electricity demand associated with EVs (based on vehicle numbers, annual mileage, and average consumption rates), the peak load impact under unmanaged and smart charging conditions, and the technical potential of V2G to provide grid services. In addition, a well-to-wheel (WTW) analysis is conducted to quantify the emissions intensity of EV usage, accounting for variability in the carbon intensity of the electricity mix (300–900 g CO₂/kWh) and the comparison with internal combustion engine (ICE) benchmarks. The infrastructural implications are also assessed, using EU charging density benchmarks (7–10 EVs per charging point) to estimate the number and typology of charging stations required (AC ≤ 22 kW, DC ≥ 50 kW). Finally, the scenarios are benchmarked against the case study in Zealand (Denmark), which offers a relevant point of comparison due to its similar demographic size, higher EV penetration, and advanced renewable integration. Scenario building follows public-sector foresight guidance: scanning drivers, defining critical uncertainties, constructing three–four internally consistent narratives, and stress-testing strategies across them. We draw on OECD, European Commission/JRC, and UNDP methodological guides.

The consumption range applied in this study (0.155–0.20 kWh/km) reflects the realistic real-world operational conditions for the Canary Islands and incorporates the main sources of variability observed in EV efficiency. Consumption differs significantly depending on vehicle size and mass (compact vs. SUV), battery capacity, drivetrain efficiency, and auxiliary loads. Driving style and trip characteristics also play a major role: the archipelago shows a predominance of short-distance urban trips with frequent acceleration–braking cycles and limited use of high-speed highways. Furthermore, the islands’ topography—characterized by steep gradients, especially in Tenerife, La Palma, Gran Canaria, and El Hierro—can substantially increase energy demand during ascents while favouring partial recovery through regenerative braking during descents. The selected interval aligns with empirical data from EAFO, IDAE, and major EV manufacturers with presence in the islands (Volkswagen, KIA, Tesla), which report typical real-world consumption values of 0.14–0.21 kWh/km for compact and midsize EVs under mixed driving conditions. These categories represent more than 85% of EV registrations in the Canary Islands, as indicated by DGT statistics. Choosing this range therefore captures both the lower bound of efficient small EVs commonly used in urban environments (≈0.155 kWh/km) and the upper bound associated with heavier models or operation in mountainous terrain (≈0.20 kWh/km) (Figure 9). This ensures that the demand scenarios realistically reflect regional driving conditions, climatic patterns, and fleet composition.

3.3.1. Data Sources

The analysis relies on a combination of official statistical sources, institutional databases, and manufacturer specifications, each providing critical inputs for the modelling framework. Data from Red Eléctrica de España (REE) (https://www.ree.es, accessed on 15 May 2025) is employed to characterize the insular power system, including hourly electricity demand profiles, the carbon intensity values of the grid, and the composition of the generation mix. These datasets allow for the quantification of baseline demand, the identification of peak load hours, and the calculation of well-to-wheel (WTW) emissions associated with EV charging. Information from the Institute for Energy Diversification and Saving (IDAE) (https://www.idae.es, accessed on 23 July 2025) and the European Alternative Fuels Observatory (EAFO) (https://alternative-fuels-observatory.ec.europa.eu), accessed on 16 April 2025) provides benchmarks for EV energy consumption, charging efficiency, and infrastructure deployment density. These sources are essential for estimating the average energy use per vehicle, the efficiency of charging processes, and the required ratio of EVs per charging point, in line with European standards.

At the regional level, the Canary Islands Energy Transition Plan (PTECan 2030–2040) (https://www.gobiernodecanarias.org/energia, accessed on 29 June 2025) defines policy targets for EV fleet size, renewable energy penetration, and CO₂ reduction objectives. This document offers the reference values against which the scenarios for 2030 and 2040 are constructed. Data from the Directorate-General for Traffic (DGT) (https://www.dgt.es, accessed on 2 August 2025) and the Canary Islands Statistics Institute (ISTAC) (https://www.gobiernodecanarias.org/istac, accessed on 18 July 2025) provide island-level details of the existing vehicle fleet, annual registrations, and demographic context. These statistics form the foundation for the baseline fleet composition and for disaggregating demand projections across the archipelago. Finally, manufacturer data from brands such as BMW (https://www.bmw.com, accessed on 24 April 2025), Nissan (https://www.nissan-global.com, accessed on 24 April 2025), and Tesla (https://www.tesla.com, accessed on 24 April 2025) are used to establish real-world consumption benchmarks for representative EV models (ranging between 0.155 and 0.20 kWh/km). These values ensure the accuracy of consumption estimates and serve as a cross-check against institutional averages. Collectively, these sources create a robust and multiscalar database that enables the construction of realistic scenarios for EV adoption, electricity demand, infrastructure requirements, and emissions pathways in the Canary Islands.

3.3.2. Scenario Definition

To evaluate the prospective evolution of electromobility in the Canary Islands, three scenarios have been defined for the time horizons of 2025 (baseline), 2030 (medium-term), and 2040 (long-term). These scenarios are constructed based on official planning documents such as the Canary Islands Energy Transition Plan (PTECan 2030–2040), complemented by institutional benchmarks from IDAE, EAFO, and REE, as well as regional fleet statistics from ISTAC and DGT.

This baseline scenario (2025) represents current conditions, including the existing number of battery electric vehicles (BEVs), the present charging infrastructure, and the prevailing carbon intensity of the electricity mix (

Table 8. Summary of the key variables across the three scenarios, including the number of EVs, their share of the fleet, the share of renewable energy (RES) in the generation mix, the average grid carbon intensity, and the density of charging infrastructure expressed as the number of EVs per charging point (CP). Source: authors.

Variable	Baseline (2025)	Medium-Term (2030)	Long-Term (2040)
Number of BEVs	~35,000	~225,000	>600,000 (majority fleet)
EV share of fleet	~1.5%	~10–12%	>70%
Renewable share (RES)	~20%	~60%	~95–100%
Grid CO2 intensity (g/kWh)	850	400–500	<100
CP density (EVs/CP)	~20	7–10	≤7

). The medium-term scenario (2030) integrates policy targets, with an estimated EV fleet of approximately 225,000 units, a renewable energy penetration of 60%, and a significant reduction in grid carbon intensity due to the progressive substitution of fossil-fuel generation. Finally, the long-term scenario (2040) envisions the consolidation of electromobility, where BEVs constitute the majority of the fleet, vehicle-to-grid (V2G) technologies are widely deployed, and renewable penetration approaches 100%, thereby enabling near-zero carbon intensity levels. Table 8 is a summary table of the scenario parameters (BEV numbers, EV share, renewable share, grid carbon intensity, and charging point density), providing a concise overview of the analytical framework.

Related to these scenarios, the trajectory of electromobility and energy transition variables between 2025 and 2040 depends on the number of BEVs increases almost twentyfold, reflecting both policy ambition and consumer uptake. This growth—now in an impasse scenario due to the legal imposition in several cities [26]—must be accompanied by a proportional rise in renewable energy integration, which reaches full penetration by 2040, thereby enabling near-zero emission mobility. Simultaneously, the grid’s carbon intensity declines sharply, falling below 100 g CO₂/kWh, a forced prerequisite for ensuring that electric vehicles deliver net climate benefits compared to internal combustion engines. Figure 10 underscores the interdependence of vehicle electrification, renewable expansion, and grid decarbonisation, showing that progress in one dimension must be matched by advances in the others to achieve systemic sustainability in the Canary Islands. We project the 2023–2030 electric passenger car stock using a constrained logistic (S-curve) anchored to (a) 2023 baseline stock (ISTAC/DGT), and (b) 2030 policy targets (PTECan/PNIEC). The logistic form is as follows:

(t) = K/1 + exp[−r(t − t0)]

where K is the 2030 target stock, r is the intrinsic adoption rate, and t0 is the inflection year. We calibrate r, 0 to match historical registrations and ensure annual additions remain within charging and grid constraints. Sensitivity ranges (±20% on r) are reported. As a robustness check, we also estimated a Bass diffusion model; parameters p, qp, qp, and q were calibrated on 2018–2024 registrations and constrained to the same KKK. Results are consistent with the logistic within ±5–10% by 2030, as shown in Figure 10.

The estimation of electricity demand from battery electric vehicles (BEVs) was conducted by applying a simple bottom–up approach, where annual energy consumption is a function of the number of vehicles, the average annual mileage, and the average specific consumption per kilometre. The formula used is:

E_EV = N_EV × km/year × C_EV

where N_EV denotes the number of EVs in the fleet, km/year represents the average annual mileage (10,000–12,000 km depending on assumptions), and corresponds to the average consumption of EVs (0.155–0.20 kWh/km). Three scenarios were assessed: a baseline (2025) with approximately 35,000 BEVs, a medium-term (2030) scenario with ~225,000 BEVs, and a long-term (2040) scenario with ~600,000 BEVs, representing the majority of the fleet, as shown in Figure 11.

The bars represent low-, medium-, and high-demand assumptions based on variations in average mileage (10,000–12,000 km/year) and consumption rates (0.155–0.20 kWh/km). The results indicate that EVs would require approximately 54–84 GWh/year of additional electricity in 2025, rising sharply to 349–540 GWh/year by 2030. In long-term scenario of 2040, demand reaches between 0.93 and 1.44 TWh/year, with a central estimate of 1.16 TWh/year. These values highlight the growing pressure on the Canary Islands’ power system as electromobility scales up, underscoring the need for significant investments in renewable generation, grid reinforcement, and smart charging strategies to accommodate the projected demand. Although the methodology for estimating peak load is presented below, the detailed calculation has not been carried out in this work; this is because the values would represent an even more demanding requirement than the aggregate annual demand, as peak load scenarios assume the coincidence of charging within short time windows. In uncontrolled charging conditions, this could multiply instantaneous power needs severalfold compared to annual averages, leading to grid stresses that exceed the currently installed capacity in the Canary Islands. Even under smart charging or V2G strategies, the peak power to be provided would still require the substantial reinforcement of local networks. For this reason, the present study focuses on annual electricity demand and charging infrastructure needs, acknowledging that peak load analysis would further reinforce the urgency of grid adaptation.

3.3.3. Validation of the EV Adoption Model

To validate the scenario-based EV stock projections, we fitted a logistic growth model to the historical evolution of electric vehicles in the Canary Islands using annual registrations from 2012 to 2024. The logistic curve is defined as follows:

$$EV\left(t\right)={\displaystyle \frac{K}{1+\mathrm{e}\mathrm{x}\mathrm{p}[-r\left(t-t_0\right)]}}$$

where K is the carrying capacity, r is the intrinsic growth rate, and t₀ is the inflection point. The parameters were optimized via nonlinear least squares. Model performance was evaluated using the coefficient of determination (R²), root mean square error (RMSE), and graphical residual inspection. To cross-validate the results, we also calibrated a Bass diffusion model:

$$EV\left(t\right)=m·{\displaystyle \frac{1-\mathrm{e}\mathrm{x}\mathrm{p}[-\left(p+q\right)t]}{1+\frac{q}{p}\mathrm{e}\mathrm{x}\mathrm{p}[-\left(p+q\right)t]}}$$

where p denotes the innovation parameter and q the imitation parameter. The Bass model, widely used for technology diffusion studies, served as a benchmark for the logistic projection. The logistic model yielded an excellent fit (R² > 0.98), accurately capturing the observed acceleration of EV adoption since 2018 and the anticipated saturation dynamics. The Bass diffusion model produced a comparable fit but exhibited higher sensitivity to early-year fluctuations, reflecting the small initial market size of the Canary Islands. For this reason, and due to its stability under policy-driven expansion, the logistic model was retained for scenario projections.

Figure 12 shows the historical evolution of the BEV stock in the Canary Islands (2012–2024) together with the fitted logistic curve and the Bass diffusion model. Both models reproduce the empirical trajectory with a very high goodness of fit (logistic: R² ≈ 0.99, RMSE ≈ 350; Bass: R² ≈ 0.99, RMSE ≈ 360). The inflection point of the logistic curve is located around 2022, which is consistent with the recent acceleration of EV adoption observed in the archipelago.

The analysis of well-to-wheel (WTW) emissions complements the estimation of annual EV electricity demand by translating energy consumption into greenhouse gas equivalents. While EVs eliminate direct tailpipe emissions, their environmental benefit ultimately depends on the carbon intensity of the electricity mix used for charging. In the Canary Islands, this factor is particularly critical given the current predominance of fossil fuel generation. The WTW approach therefore multiplies the specific energy consumption of EVs (CEV), expressed in grams of CO₂ per kilowatt-hour. A sensitivity range of 300–900 gCO₂/kWh is applied to capture present conditions and potential decarbonization trajectories, with results benchmarked against conventional internal combustion engine (ICE) vehicles (~160–190 gCO₂/km). This comparison provides an essential framework to assess whether the electrification of transport leads to genuine reductions in emissions under the evolving energy scenarios defined for 2025, 2030, and 2040. WTW (well-to-wheel) accounting follows the JEC (JRC–EUCAR–Concawe) framework: TTW tailpipe emissions plus WTT upstream fuel/electricity supply emissions. Only WTW is reported per km using official energy intensities and WLTP consumption, and selected indicators (WTW emissions, EV-per-charger ratio, total installed charging power, and grid carbon intensity) align with EAFO/IEA practice and the WTW literature, and directly link scenario drivers (adoption, charging mix, grid mix) to energy needs and emissions outcomes.

3.3.4. Charging Infrastructure Location and Needs

The relationship between territorial structure and the deployment of charging infrastructure is a decisive factor for the feasibility of electromobility in ultraperipheral regions. Unlike continental systems, where distances between urban centres can span several hundred kilometres, in insular territories, such as Tenerife, the geographical scale is inherently limited, and daily trips rarely exceed 50 kilometres. This condition provides a strategic advantage: the range of current battery electric vehicles (BEVs), averaging 250–400 km, is more than sufficient to cover the vast majority of everyday trips for both residents and tourists. However, this apparent advantage masks critical complexities related to mountainous topography, the fragmentation of population centres, and land-use pressures in urban and touristic areas. Figure 13 illustrates how the spatial distribution of charging stations at different density levels (high, medium, and low) translates into effective territorial coverage when mapped with service radii of 20 km, 30 km, and 50 km. This spatial analysis shows that, while a properly distributed network could theoretically provide complete island-wide coverage, the precise location of charging points is decisive for ensuring service continuity.

Table 9. Coverage radius of charging stations in islanded systems and their strategic implications. The table highlights the relationship between territorial scale, functional role of charging points, and potential co-location with conventional fuel stations and hydrogen hubs. Source: Authors.

Coverage Radius (km)	Key Implications	Synergy with Gas Stations/Hydrogen Stations	Area of Influence (km2)
0–5	High density urban coverage; suitable for short commutes and tourism-oriented demand	Very high—co-location feasible with existing petrol stations and potential hydrogen hubs	78.5
5–10	Intermediate coverage enabling urban–periurban trips; essential for commuter flows	High—co-location at periurban gas stations, logistic hubs, shopping centres	235.6
10–20	Regional connectivity between municipalities; reduces range anxiety on larger islands	Moderate—fewer existing petrol stations; hydrogen co-location more strategic	942.5
20+	Critical for inter-island rural and low-density zones; requires strategic nodes at ports/airports	Low—sparse gas station presence; hydrogen hubs more critical for connections	>1256.6

shows how territorial structure, population density, and the existing distribution of fuel stations constrain or enable the shift from combustion vehicles to electric ones, and how integrating hydrogen infrastructure could complement EV charging; this is especially the case in areas with lower coverage density strategic corridors, such as the north–south axis connecting Santa Cruz de Tenerife, La Laguna, and Adeje. Here, the bulk of daily resident and touristic mobility is concentrated, implying the need for a high density of fast and ultra-fast charging stations. Conversely, rural or low-density areas such as Vilaflor or El Tanque may require fewer stations, yet their presence is essential to prevent “coverage voids” that could undermine equitable access to electromobility across the island.

In this regard, the transition from combustion vehicles to BEVs in insular systems depends less on the technological limits of battery autonomy and more on the intelligent design of a territorially integrated charging network. This network must respond to local mobility patterns while accounting for strong touristic seasonality. Strategic availability of charging infrastructure at airports, ports, major tourist hubs, and along main transport corridors is therefore indispensable to ensure that large-scale EV adoption is not hindered by perceived risks of insufficient coverage or charging insecurity. This illustrates a key structural difference compared to fossil fuel systems: while conventional refuelling relies on a small number of high-throughput stations, electromobility depends on a dense, distributed, and intelligently located network of charging points.

Dimensioning the charging network is pivotal for three reasons. First, it links fleet targets to grid-capacity planning: without enough charging points (CPs) in the right places and with adequate power, EV adoption stalls and queues appear, especially in tourist peaks. Second, the number and type of chargers (AC ≤ 22 kW vs. DC ≥ 50 kW) determines the connected load that distribution grids must host, informing substation upgrades, feeders, and smart charging/V2G control. Third, charger density (EV/CP) is a service-level indicator aligned with EU benchmarks (≈7–10 EV per public CP) that allows international comparison and policy tracking. We compute the required number of public charging points per scenario from the EV stock using the EU service ratio R (EV per CP):

N_CP = RN_EV, R ∈ [7, 10]

We then split technology as 70% AC (≤22 kW) and 30% DC (≥50 kW), consistent with mixed residential/touristic patterns, and estimate connected power assuming typical ratings of 11 kW (AC) and 100 kW (DC):

P_AC = N_AC⋅11 kW

P_DC = N_DC⋅100 kW

The actual matched power will be lower thanks to smart charging and power management; we report the installed power for design purposes here (

Table 10. Core variables—BEV stock, EV share, renewable share, grid carbon intensity, and EV/CP density—across three scenarios: providing a quantitative frame for infrastructure sizing and grid planning. Source: authors.

Variable	Baseline (2025)	Medium-Term (2030)	Long-Term (2040)
Number of BEVs	~35,000	~225,000	>600,000 (majority fleet)
EV share of fleet	~1.5%	~10–12%	>70%
Renewable share (RES)	~20%	~60%	~95–100%
Grid CO2 intensity (g/kWh)	850	400–500	<100
CP density (EVs/CP)	~20	7–10	≤7

and

Table 11. Annual EV electricity demand under low/central/high assumptions; these values are the basis for peak load and infrastructure calculations. Source: authors.

Scenario	Case	EVs (Units)	Mileage (km/year)	Consumption (kWh/km)	Annual EV Demand (GWh)
2025 (Baseline)	Low demand	35,000	10,000	0.155	54.2
2025 (Baseline)	Middle demand	35,000	11,000	0.175	67.4
2025 (Baseline)	High demand	35,000	12,000	0.2	84
2030 (Medium-term)	Low demand	225,000	10,000	0.155	348.8
2030 (Medium-term)	Middle demand	225,000	11,000	0.175	433.1
2030 (Medium-term)	High demand	225,000	12,000	0.2	540
2040 (Long-term)	Low demand	600,000	10,000	0.155	930
2040 (Long-term)	Middle demand	600,000	11,000	0.175	1155
2040 (Long-term)	High demand	600,000	12,000	0.2	1440

).

The infrastructure requirements derived from the scenarios represent a scale-up several orders of magnitude above the current availability of charging points in the Canary Islands. Figure 14 highlights the step change from 2025 to 2030 and the substantial scale-up needed by 2040, as well as the increasing DC share required to support tourist mobility and inter-urban travel. The estimation of total connected power (

Table 12. Required public charging points for each scenario using EU service ratios R = 7–10 EV/CP. The table disaggregates AC (≤22 kW) and DC (≥50 kW) units and reports associated connected power. Results indicate ~22.5–32.1 k CP in 2030 (6.8–9.6 k DC) with ~0.85–1.21 GW connected, rising to 60–85.7 k CP in 2040 (18.0–25.7 k DC) with ~2.26–3.23 GW connected power. Source: authors.

Scenario	EVs (Units)	R (EV/CP)	Total CP	AC CP (70%)	DC CP (30%)	AC Connected Power (MW)	DC Connected Power (MW)	Total Connected Power (MW)
2025 (Baseline)	35,000	7	5000	3500	1500	38.5	150	188.5
2025 (Baseline)	35,000	10	3500	2450	1050	26.95	105	131.95
2030 (Medium-term)	225,000	7	32,143	22,500	9643	247.5	964.3	1211.79
2030 (Medium-term)	225,000	10	22,500	15,750	6750	173.25	675	848.25
2040 (Long-term)	600,000	7	85,714	60,000	25,714	660	2571.4	3231.43
2040 (Long-term)	600,000	10	60,000	42,000	18,000	462	1800	2262

) uses representative nominal power levels of 11 kW for AC chargers (≤22 kW category) and 100 kW for DC chargers (≥50 kW category). These values are not arbitrary; they correspond to the statistical mid-points of the two charger classes most commonly deployed in Europe according to EAFO and IDAE datasets. AC public charging in the Canary Islands is overwhelmingly dominated by 7.4–22 kW units, with 11 kW being the median value used in regional tenders and municipal deployments. Likewise, the DC fast-charging segment ranges widely from 50 kW to 350 kW, but the majority of existing installations (≈70%) fall between 50 kW and 120 kW, with 100 kW representing a robust central benchmark. Using these mid-point values allows the model to achieve the following goals: (i) avoid underestimating DC demand by using minimum values (50 kW); (ii) avoid artificially inflating required capacity by using extreme values (150–350 kW); (iii) maintain cross-scenario comparability.

With only around 935 charging points installed by 2025, the medium-term scenario for 2030—requiring between 22,500 and 32,100 chargers—implies a network expansion of 24 to 34 times the present stock. In the long-term 2040 scenario, with 60,000 to 85,700 chargers needed, the expansion factor reaches 64 to 92 times the current level. When compared to the approximate 228 fuel stations currently operating in the archipelago, even the 2030 scenario would involve deploying an infrastructure 100–140 times larger than the number of conventional refuelling facilities, reflecting the fundamentally different spatial and operational logic of electromobility. These figures underscore the magnitude of the systemic transition required: while the fossil fuel system relies on a small number of high-throughput refuelling nodes, electromobility depends on a dense, distributed, and diversified charging network integrated into urban, touristic, and residential contexts. In addition, according to Redeia, recorded intensities in the islands exceed those on the mainland, based on time-series analyses and the operational particularities of the Canary Islands’ power system. Under these current assumptions for a compact car (electric use at the plug ≈ 17.9 kWh/100 km from IDAE guidance; charging efficiency 0.92), the break-even grid carbon intensity I* at which a BEV’s WTW equals a modern diesel’s WTW is calculated as follows:

I* ≈ (Diesel WTW (g CO₂/km))/(EV at-metre kWh/km/η charge)

For a diesel WTW of 150–170 g CO₂/km (JEC indicative range for C-segment), I* lies around ~770–870 g CO₂/kWh. Therefore, when average grid intensity is below ~0.8–0.9 tCO₂/MWh, BEVs outperform modern diesel on a WTW basis. We report results as a band, not a single point, and provide a sensitivity analysis in the text. WTW analysis converts standardized vehicle-level electricity use into greenhouse gas intensity per kilometre and benchmarks it against ICE comparators. Operationally, we take the EV’s specific energy use at the metre, E_WLTP (kWh/km), consistent with the consumption ranges used in the demand calculations (0.155–0.20 kWh/km; 10–12 thousand km/year), adjust for charging efficiency η_ch (0.90–0.95) to obtain generation-side kWh/km, and multiply by the scenario-dependent average grid carbon intensity I_grid (300–900 g CO₂/kWh): WTW_EV = (E_WLTP)/(η_ch) × I_grid. ICE benchmarks are expressed directly in g CO₂/km on a WTW basis and used for comparison in the text (~160–190 g CO₂/km).

3.3.5. Peak Load Considerations and Methodological Limitations

Although a complete peak load calculation would require detailed feeder-level grid data (including transformer loading profiles, distribution line impedances, and the spatial allocation of charging demand), such information is not publicly available for the Canary Islands. For this reason, the analysis adopts a transparent quantitative approximation using the standard relationship P_peak = E_EV/h_charge and evaluates three charging window scenarios (unmanaged 2–3 h, semi-managed 4–6 h, and smart-coordinated 8–12 h). The resulting peak load range is presented as a sensitivity band rather than a single deterministic value, reflecting realistic behavioural and technical variability. This approach aligns with the existing literature on EV peak load estimation under data-limited conditions. The results show that, even under conservative assumptions, additional peak power requirements in 2030 and especially 2040 exceed the current hosting capacity of several island grids, highlighting the necessity of controlled charging, the reinforcement of local distribution networks, and the deployment of V2G-enabled flexibility resources. A full AC load–flow simulation was not feasible given the lack of disaggregated grid topology and historical loading data, and this limitation is now explicitly acknowledged.

4. Towards New Mobility in the Islanded Territories

4.1. Integrative Transformation Proposal

Energy transition of the transport system in the Canary Islands must be understood as not merely a technological remediation process but also as a structural strategy aimed at enhancing environmental sustainability, the efficiency of the insular energy system, and the quality of urban life [27]. Given the high dependence on imported fossil fuels, the territorial limitations, and the ecological fragility of the archipelago, the proposal focuses on a model of urban mobility supported by battery–electric vehicles (BEVs) and complemented, where feasible, by hydrogen-based mobility, all managed through smart and interconnected systems [28]. Quantitative calculations of electricity demand, peak load, well-to-wheel emissions, and charging infrastructure requirements form the analytical core of the methodology. The outputs (Figure 15) include measurable indicators (GWh/year, gCO₂/km, EV/CP density, MW connected) and policy-relevant insights (grid bottlenecks, renewable integration thresholds), enabling an evaluation of feasibility, resilience, and sustainability. This framework ensures that the transformation strategy is both conceptual and operationalisable and replicable in other insular contexts.

To guide this transformation, the following objectives are established:

• Progressively replace the internal combustion fleet with high-efficiency battery electric vehicles (BEVs) [29].
• Complement BEVs with hydrogen fuel cell vehicles in specific segments (long-haul, heavy-duty, or where storage density is critical).
• Develop an interconnected charging infrastructure network adapted to the urban and touristic distribution of the archipelago, combining electricity and hydrogen [30]
• Integrate electromobility into land-use planning, public transport systems, and sustainable urban development strategies [29].
• Maximise the share of renewable energy in electricity supply linked to mobility, reducing both emissions and vulnerability to fossil fuel imports.

These objectives are reinforced by public incentives, targeted investments, and growing societal awareness, placing the Canary Islands in a favourable position to adopt pilot models of sustainable mobility that can be extrapolated to other insular or isolated territories [31]. In the specific case of the Canary Islands, the widespread deployment of battery-based electric vehicles (and/or hydrogen) responds to both the need for technological modernization and the need for a territorial adaptation strategy. The limited availability of fossil fuels, the high cost of maritime fuel transport, and the archipelago’s environmental vulnerability make the transition to electromobility a socioeconomic and ecological priority.

4.2. Role of Batteries and Second-Life Applications

A cornerstone of this proposal is the strategic use of used batteries, both during their first life in electric vehicles and in their subsequent “second life” applications. After 8–10 years of vehicular use, when capacity degrades below mobility requirements, batteries retain sufficient performance for stationary applications. Their reuse not only extends resource life but also mitigates environmental impacts and reduces dependence on critical raw materials. Potential second-life applications include the following:

• Residential and commercial storage systems.
• Integration with photovoltaic installations in community energy projects.
• Backup power for industries or rural areas with weaker supply quality.
• Auxiliary storage for fast-charging stations, reducing peak demand and operational costs.

These applications contribute to democratising energy storage access, increasing local resilience, and reducing both emissions and costs. For consolidation, regulatory, technical, and digital enablers are required:

• Technical standards and interoperability frameworks for battery integration with grids.
• Business models and tariff structures that remunerate flexibility and ancillary services.
• Energy management systems (EMSs) for households, buildings, and communities.
• Digital aggregation platforms enabling virtual power plants (VPPs).
• Traceability and certification protocols ensuring safe and transparent second-life deployment.

Investment in smart grids, real-time control systems, and aggregation platforms will be essential to articulate this new ecosystem. In addition, battery-based energy transition is not solely a technical shift, but also a socioeconomic transformation. It generates new value chains, skilled jobs, and innovation opportunities across the life cycle of batteries—from production and deployment to reuse and recycling. Moreover, it promotes a fairer energy model where citizens become active participants capable of generating, storing, and exchanging energy. Energy communities, supported by storage, can play a decisive role in combating energy poverty and fostering rural development. Environmentally, the reuse of batteries reduces extractive activities for raw materials and lowers the carbon footprint of the transport energy system. The transition also reduces local pollutant emissions and urban noise, yielding tangible health and quality-of-life benefits for residents and tourists alike. Recent EEA and ICCT assessments confirm that BEVs in Europe deliver substantially lower life cycle GHGs than ICEVs; continued grid decarbonisation further widens the gap.

4.3. Proposed Roadmap

According to all the parameters analysed in this study—including the current structure of the Canary Islands’ power system, the dependence on fossil fuel imports, the limited interconnection capacity, the increasing electricity demand from projected EV penetration, the well-to-wheel emission balances, and the massive scale-up of charging infrastructure required—the need for a systemic transformation is unequivocal. The transition towards electromobility in the archipelago cannot be understood merely as the substitution of internal combustion vehicles by battery electric vehicles, but rather as the redesign of the entire mobility–energy nexus.

On this basis, a comprehensive transformation proposal has been developed, centred on batteries as both propulsion units and active grid assets, complemented by hydrogen for specific niches, and supported by a dense, smart, and renewable-powered charging infrastructure. This strategy is articulated into a phased roadmap (2025–2040) that combines incentives, regulatory reforms, infrastructure deployment, second-life battery integration, circular economy practices, and continuous innovation. The roadmap thus ensures that the Canary Islands can progress towards a resilient, decentralised, and low-carbon transport energy system that not only meets mobility needs but also strengthens energy sovereignty and environmental sustainability in one of Europe’s most vulnerable insular territories. The proposed transition is structured in five phases, ensuring gradual implementation and alignment with technological, regulatory, and social evolution:

• Phase 1: Incentives and pilots (2025–2027)—deployment of incentives for household and business storage; subsidies for pilot V2G, BESS, and second-life battery projects; training programmes for technical professionals.
• Phase 2: Regulatory framework and digitalisation (2026–2028)—development of specific legislation for second-life batteries; implementation of dynamic tariffs; roll-out of digital aggregation and monitoring platforms.
• Phase 3: Large-scale integration (2028–2032)—mass deployment of bidirectional charging infrastructures; inclusion of batteries in wholesale and capacity markets; interconnection of energy communities with distributed storage.
• Phase 4: Circular economy and resilience (2032–2040)—consolidation of local reuse and recycling value chains; reinforcement of vulnerable zones through community storage; promotion of energy self-sufficiency in critical sectors (health, water, telecommunications).
• Phase 5: Continuous innovation (2040 onwards)—adoption of advanced battery technologies (solid-state, metal–air, molecular recycling); hybridisation with green hydrogen and microgrids; progression towards autonomous and AI-managed decentralised energy systems.

The scenario framework developed explicitly incorporates the management of uncertainties associated with technological evolution, the adoption of electric vehicles, and the decarbonisation of the electricity system. Instead of assuming single values, the main parameters—such as energy consumption, annual mileage, charging efficiency or carbon intensity of the electricity mix—are expressed in ranges and combined in alternative scenarios (low, central, and high), allowing the sensitivity of the results to be assessed. This approach recognises that energy and mobility planning in island systems is subject to multiple sources of uncertainty, including regulatory factors, user behaviour, and variability in the availability of renewable resources. The methodology, therefore, does not seek to predict a single future, but to delimit a set of plausible trajectories that guide decision making under conditions of incomplete information. This flexible structure reinforces the validity of the analysis and facilitates its adaptation to future technological or energy policy changes.

4.4. Scalability and Performance in Large-Scale Applications

The methodological framework developed in this study has been designed to remain computationally tractable and easily extendable to larger systems with many variables. Unlike optimization-based charging-station siting models—such as mixed-integer linear programming or nonlinear spatial allocation algorithms—our approach relies on analytical formulations, scenario scaling factors, and empirically calibrated diffusion curves. As such, the computational complexity increases linearly with the number of regions, EV categories, or infrastructure types incorporated into the analysis. Because the core calculations are based on closed-form expressions (EV energy demand, well-to-wheel emissions, EV/CP ratios, and connected power estimation), the framework can be applied to larger test cases without requiring burdensome numerical solvers or detailed feeder-level grid modelling. This scalability has two advantages:

(1)

The method remains computationally lightweight, with execution times of only a few milliseconds even when hundreds of subregions are included.

(2)

The model is robust under high-dimensional scenario expansion, as the calculations do not suffer from combinatorial growth.

While more detailed optimization approaches are suitable for specific siting or network-reinforcement studies, the proposed framework is intended to provide a system-level, transparent, and reproducible assessment of energy, emissions, and infrastructure needs. Its structure makes it well suited for large-scale analyses where granular grid topology or high-resolution mobility datasets may be unavailable.

4.5. Sensitivity to Parametric Variability

The applicability and robustness of the proposed methodological framework depend on its ability to adapt to different territorial, infrastructural, and energy system conditions. Although the model has been calibrated for the specific characteristics of the Canary Islands—an isolated, fragmented, and fossil-fuel-dependent archipelago—the underlying structure is designed to remain valid across a wide range of regional contexts. From a methodological standpoint, sensitivity arises primarily from five dimensions: (i) fleet composition and annual mileage, (ii) topographic constraints, (iii) renewable energy availability, (iv) grid carbon intensity, and (v) charging infrastructure density.

First, variations in fleet size, usage intensity, and mobility patterns can significantly alter the resulting electricity demand projections. Regions with longer average trip distances, higher private vehicle dependency, or different modal split assumptions would experience proportional changes in yearly EV energy requirements. Second, topography and land-use constraints strongly condition not only vehicle consumption profiles but also the siting potential for charging stations; mountainous territories, areas with dispersed settlements, or locations with strict land-protection regimes require a tailored spatial planning approach. Third, renewable resource endowment—particularly the availability of solar, wind, or hydroelectric potential—directly affects well-to-wheel (WTW) emissions and determines the degree to which electromobility can be decarbonised. The model incorporates this through scenario-dependent carbon intensity inputs, enabling rapid recalibration for regions with different energy mixes. Fourth, the framework is sensitive to grid characteristics, including hosting capacity, redundancy, and the degree of isolation. Systems with strong interconnections can buffer EV-related peaks, whereas isolated grids—such as those of island territories—require stricter assumptions regarding peak-demand periods.

5. Conclusions

The results of this study confirm that the transition towards electromobility in insular systems such as the Canary Islands must be conceived not as a mere technological substitution but as a comprehensive restructuring of the energy–mobility nexus. Quantitative estimations demonstrate that the projected growth of the battery electric vehicle (BEV) fleet—from approximately 35,000 units in 2025 to more than 600,000 by 2040—will generate an additional annual electricity demand ranging between 0.93 and 1.44 TWh. While technically achievable, such an increase requires a profound reconfiguration of the insular power system, which remains highly dependent on imported fossil fuels and which is structurally fragmented into isolated subsystems. The initial conditions—high vehicle density per capita, strong reliance on petroleum derivatives, absence of inter-island interconnections, and limited renewable penetration—represent significant constraints compared to continental systems. At the same time, they highlight the potential for a structural leap forward. The abundance of solar and wind resources, when combined with large-scale deployment of stationary storage and vehicle-to-grid (V2G) technologies, could transform the vehicle fleet into an active participant in the decarbonisation process, enhancing flexibility, reliability, and resilience in fragile island grids.

The comparison with Zealand (Denmark) illustrates both the feasibility and the limitations of the process. Zealand benefited from a long-standing national strategy initiated in the 1990s, continental grid interconnections, and a stable political framework. By contrast, the Canary Islands must design eight parallel energy transitions—one per island—under a unified regional vision. Moreover, land-use restrictions and environmental sensitivities constrain the large-scale deployment of renewable generation, demanding decentralised solutions such as rooftop photovoltaics, community-based storage, and second-life battery applications. Another critical outcome concerns charging infrastructure. By 2030, between 22,000 and 32,000 charging points will be required, rising to 60,000–85,000 by 2040. This represents a 24- to 92-fold expansion over the current network and far surpasses the approximately 228 fossil fuel stations currently operating in the archipelago. This contrast evidences the structural shift from a concentrated fossil-fuel-based refuelling system towards a dense, distributed, and digitally managed charging network, adapted to urban, residential, and touristic contexts.

Finally, while the focus of this study has been on battery–electric vehicles, the analysis underscores the necessity of a hybrid strategy in which electromobility is complemented by hydrogen-based mobility, particularly for heavy-duty transport, long-distance logistics, and applications requiring high storage density. Hydrogen, together with BEVs, can mitigate systemic vulnerabilities, diversify technological pathways, and reinforce resilience in an archipelago that must balance energy sovereignty with environmental protection.

The analysis presented in this study highlights both the opportunities and the systemic challenges associated with the large-scale adoption of electromobility in insular territories such as the Canary Islands. By integrating quantitative modelling of electricity demand, charging infrastructure needs, and well-to-wheel emissions with comparative insights from Zealand, the research demonstrates that the transition cannot be addressed as a linear substitution of technologies but as a structural reconfiguration of the energy–mobility nexus. The findings emphasise that while battery electric vehicles (BEVs) represent the cornerstone of the transformation, their effective deployment must be coupled with accelerated renewable integration, large-scale digitalisation of the grid, and complementary solutions such as hydrogen for hard-to-electrify segments. Against this background, the following conclusions summarise the key outcomes of the study and outline the strategic implications for policymakers, system operators, and stakeholders involved in the energy transition of insular systems:

• Electromobility in the Canary Islands is technically feasible but requires deep systemic transformation and great investment. The projected expansion of the BEV fleet to over 600,000 units by 2040 implies an additional electricity demand exceeding 1 TWh/year and a charging infrastructure several orders of magnitude larger than today, necessitating unprecedented investments in generation, networks, and digital management.
• The environmental benefits of BEVs are contingent upon deep decarbonisation of the electricity mix. With the current carbon intensity of ~850 gCO₂/kWh, EVs offer limited or no advantage over efficient diesel vehicles, and even worse than hydrogen technology. Only with renewable penetration above 95% by 2040 do BEVs deliver substantial net climate benefits, reducing emissions intensity below 100 gCO₂/kWh.
• The shift from fossil fuels to electromobility requires a rethinking of spatial and operational paradigms. Unlike the concentrated model of ~228 fuel stations, the future mobility system will depend on a dense, distributed network of 60,000–85,000 charging points integrated into residential, urban, and touristic infrastructures, supported by smart grids and digital platforms. In addition, a diversified strategy including hydrogen is indispensable. While BEVs will dominate private and urban mobility, hydrogen fuel cell vehicles offer a complementary solution for heavy transport, inter-island logistics, and niche applications where energy density and rapid refuelling are critical.
• Batteries and V2G technologies constitute the backbone of system resilience. Beyond their primary role in mobility, EV batteries can provide distributed storage, frequency regulation, voltage control, and emergency backup. These functions are crucial for stabilising small, isolated grids with high shares of intermittent renewable generation.
• Long-term stability and governance are prerequisites. The Zealand case study shows that technology alone is insufficient; regulatory consistency, institutional coordination, and citizen participation are equally decisive. For the Canary Islands, achieving electromobility requires a stable, multi-sectoral framework that combines incentives, renewable expansion, circular battery economy, and integrated territorial planning.