PiV EI Economics and Carbon Benefits: Energy Scenarios Comparison Report (WP3.5)
||Guest, P., Anelli, D., Jakeman, N. and Ballardin, G. PiV EI Economics and Carbon Benefits: Energy Scenarios Comparison Report (WP3.5), ETI, 2011. https://doi.org/10.5286/UKERC.EDC.000733. Cite this using DataCite
||Guest, P., Anelli, D., Jakeman, N. and Ballardin, G.
||Shell Research Ltd, E.ON Engineering (UK) Ltd, Electricité de France SA (EDF SA), IBM, The MathWorks, Inc, Ove Arup & Partners Ltd, Ricardo, TRL Limited, Institute for Transport Studies - University Of Leeds, University of Aberdeen, University
||The Plug-in Vehicle Economics and Infrastructure: Economics and Carbon Benefits project is a strategic level analysis of the potential size of the market for plug-in vehicles, the total level of investment needed and the total carbon offset for the UK.
This is a detailed report on the analysis of the UK electricity system to 2050, to derive the electricity prices and carbon intensity factors used within the Economics and Carbon Benefits project. This report should be read as a supplement to the Scenario Development Final Report. The resulting dataset has been embedded into the Consumer Choice Model.
- The installed generation capacity in the chosen UKERC scenarios was not sufficient to supply demand once the loads from plug-in charging modelled within this project were applied: the adopted method of increasing plant capacityby scaling up the capacity ofeach plant category was chosen so that the scenarios conform as closely as possible to the initial mix in the UKERC scenarios.This scaling was found to be critically important to the outcome of the modelling.
- The modelling show sthat choice of scenario (i.e. combination of capacity mix and commodity price) and its evolution through the years are much stronger drivers of modelling outcomes than are the different charging profiles
- Cost of electricity and carbon intensities should only be taken from the No EV demand scenarios. We do not recommend using figures from scenarios with EV charging overnight or at peak times;
- Within day profiles (including regressions) for cost of electricity and carbon intensity should only be used (if at all) for low levels of EV demand (say, less than 2 GW). For larger levels of EV demand, we recommend using a single annual average figure;
- We recommend using average carbon intensities when evaluating the carbon intensity of EVs as these provide the best approximation to the true impact;
- The observed grid emission factor for 2009 should be used as an estimate of 2010 rather than the model output
- The charging regime adopted for electric vehicles has little impact on annual average electricity wholesale prices;
- Under some, but not all, choices of mechanism for incentivising investment in low carbon electricity generation overnight charging would result in lower emissions than would after-journey charging and the magnitude of this benefit is highly dependent on other scenario conditions;
- There are benefits from overnight charging in the transmission and distribution sectors of the electricity industry and it seems unlikely that there are credible scenarios in which there is a dis-benefit from overnight charging in the generation sector, so there seem to be adequate grounds to encourage this behaviour.
||ETI-TR1003: PIVEI: Large Scale Consumer Trial S1 SP3 - Economics and Carbon Benefits
||No associated datasets
PiV EI Economics and Carbon Benefits: Detailed Report on Computer Modelling (WP3.4)
PiV EI Economics and Carbon Benefits: Economics and Carbon Offset Analysis - Final Report (WP3.6)
PiV EI Economics and Carbon Benefits: Executive Summary (WP3)
PiV EI Economics and Carbon Benefits: Generic Business Models for Plug-in Vehicle Environment (WP3.1)
PiV EI Economics and Carbon Benefits: New Revenue Opportunities within Plug-in Vehicle Environment (WP3.3)
PiV EI Economics and Carbon Benefits: Request for Proposal
PiV EI Economics and Carbon Benefits: Scenario Development Final Report (WP3.2)