Modelling future private car energy demand using two techno-economic approaches

Panel: 4. Transport and mobility: How to deliver energy efficiency

This is a peer-reviewed paper.

Authors:
Hannah Daly, University College Cork, Ireland
Brian P. Ó Gallachóir, Lecturer in Energy Engineering,, Ireland

Abstract

This study presents two bottom-up approaches for forecasting private car energy demand in Ireland, one a car stock simulation model and the second an energy systems optimisation approach.

The car stock model uses historic sales, activity and car scrappage rates to iteratively simulate the structure of the car fleet and vehicle activity for each year up to 2025. Vehicle fuel efficiency and emissions factors for each vintage and technology type are applied to calculate annual energy demand and associated CO2 emissions. Scenario analysis on new-car sales technology and efficiency is used to evaluate technology orientated measures such as Ireland’s 10% electric vehicle target for 2020, and the EU’s requirement that average new-car emissions be capped at 130g/km by 2015. Different policies can then be evaluated on the basis of their expected contribution to national renewable energy and CO2 reduction targets.

The methodology, baseline results and applications of this car stock model are compared with those of the Irish TIMES project, an energy optimisation framework developed for the Irish energy system. TIMES identifies the least-cost technology mix to satisfy a given energy service demand, subject to renewable and emissions constraints. Specifically for private cars, the least-cost vehicle technology mix to satisfy annual travel demand up to 2025 is produced given a range of energy efficiency, renewable energy and emissions constraint scenarios. Demand elasticities, crude oil price, economic performance and technology costs are key input parameters.

Results from these two studies give insights firstly into the likely outcomes of current government measures in terms of their contribution to meeting climate targets, and secondly, into what measures are necessary and most cost effective for meeting these targets.