Analyzing Scotland’s Electric Vehicle Charger Needs by 2030
Scotland is preparing for a significant increase in electric vehicles (EVs) by the year 2030, and determining the necessary infrastructure to support this shift is paramount. Two distinct methodologies have been employed to estimate the required number of public EV chargers: one that is geospatially-agnostic and another that incorporates geographic information system (GIS) techniques. These approaches aim to accommodate the Scottish Government’s target of installing 30,000 chargers by 2030, taking into account the population dispersion across the country.
Estimating Charger Needs: Two Methodologies
The methodologies employed involve projections based on EV kilometers traveled and population distribution. The geospatially-agnostic approach focuses on the energy demand from EVs and the capacity of chargers to meet this demand. Using data from previous studies, including a nationally representative public EV charging network dataset, the analysis determines the proportion of energy that must be publicly met and calculates the number of charging sessions required.
Calculation of Public Charging Sessions
The total energy consumed by EVs in 2030 is calculated using projected kilometers and the energy efficiency of an EV. Assuming 44% of Scottish households rely on public charging due to a lack of private parking, the necessary public charging sessions are determined based on average energy consumption per session.
Determining Charger Capacity
Charger capacity is evaluated based on the number of sessions a charger can manage per year, with differing durations for AC and rapid charging. This capacity is crucial in calculating the number of chargers needed for different scenarios, such as all chargers being AC, all being rapid, or a 50/50 split.
Geospatially-driven Approach
Unlike the geospatially-agnostic method, the geospatially-driven approach considers population dispersion across Scotland. Utilizing ArcGIS Pro, a hexagonal grid pattern covers the country’s geographical extent, allowing for equitable access to chargers. This method involves grid partitioning and accounts for local population data, enabling a more accurate estimate of the charger population required.
Population and Charger Distribution
The analysis uses a grid partitioning technique to assess population distribution and charger access. Various grid sizes are considered, and the number of chargers needed per grid cell is calculated to ensure equitable access. The approach accounts for both current and projected population data, scaling as necessary for 2030 projections.
Balancing AC and Rapid Chargers
To meet the Scottish Government’s target, a balance between AC and rapid chargers is necessary. Utilizing the geospatially-agnostic values, the analysis converts these to a mix of AC and rapid chargers that total the required number for achieving the target while considering geographic dispersion effects.
Limitations and Considerations
Several assumptions underpin the research methodology, such as average values for energy consumption and charging durations. The study does not account for night-time charging, tourism, or visiting populations, which could affect demand. Further work is needed to incorporate these factors and the charging needs of commercial vehicles such as vans, which significantly contribute to road traffic.
In conclusion, thorough planning and consideration of both geospatial and energy demand factors are essential in developing Scotland’s EV infrastructure. Meeting the government’s target involves not just numerical goals but also ensuring equitable access and adaptability to future changes in EV usage and technology.
Original Story at www.nature.com