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Alternative fuel portfolio analysis using a stochastic MAC curve approach Kevin Fingerman 1 Colin Sheppard 2, Andrew Harris 1 1 Humboldt State University/

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Presentation on theme: "Alternative fuel portfolio analysis using a stochastic MAC curve approach Kevin Fingerman 1 Colin Sheppard 2, Andrew Harris 1 1 Humboldt State University/"— Presentation transcript:

1 Alternative fuel portfolio analysis using a stochastic MAC curve approach Kevin Fingerman 1 Colin Sheppard 2, Andrew Harris 1 1 Humboldt State University/ Schatz Energy Research Center 2 University of California, Berkeley Transportation Engineering Energy Policy Research Conference September 10 th, 2015

2 Alternative Fuels Readiness

3 Low Carbon Fuel Standard GHG reduction from transport can be broken into three distinct policy agendas – Reduction in total VMT – Increase in vehicle fuel efficiency – Reduction in fuel Carbon intensity (CI) LCFS addresses the third case. 10% reduction in average fuel CI by 2020. Offers a convenient “goal post” for aggregate alt fuel deployment.

4 The Fuels

5 Marginal Abatement Cost Curves Marginal Abatement Cost Curve (MAC Curve)

6 Cost model elements (MACC y axis) Vehicle Cost (levelized) $/MJ Incremental above BAU conventional vehicle Limited to new vehicles 2020 projections where possible Distribution Cost (levelized) Applies to EV, H 2, Flex Fuel Inclusive of financing Fuel Cost Incremental above (or below) gas/diesel Built from the “ground up” in most cases Co-varied based on historic prices Probability distributions derived from time series data and known uncertainties enable Monte Carlo simulation of prices

7 2020 Fuel Throughput

8 Fuel penetration (MACC x-axis) Each fuel penetrates the various segments based on its characteristics. Ethanol is constrained by the blend wall, but enters all gasoline segments. Biodiesel ≤20% of all diesel segments EV ≤70% of new LDVs PHEV ≤100% of new LDVs H 2 ≤65% of new LDVs Etc.

9 Incremental Cost of Alternatives

10 Costs are Random Variables with Covariance in Fuels

11 LCFS Target To achieve target: ~$37M net cost 2.5% of BAU Portfolio MAC Average MACC (500 trials)

12 Internal variation

13 Sensitivity to incremental cost of BEVs

14 Sensitivity to gasoline price

15 Sensitivity to biofuel prices Sugarcane ethanol price Soy biodiesel price

16 General findings We’ll be seeing a lot more EVs in an LCFS market. This is robust to almost any conceivable circumstance (including repeal of LCFS). There's no silver bullet, due to market limitations, we need to pursue a variety of alt fuels to meet the LCFS goal. We should expect credit prices in excess of $200/T. ARB may end up limiting prices, thereby reducing impact. Since there is an either/or element to this (unlike the McKinsey curve we’re familiar with), naive $/T analysis misses key dynamics.

17 kevin.fingerman@humboldt.edu THANKS! Questions?

18 Issue with MAC Approach Sorghum ethanol cheaper than gasoline and cheapest MAC in most cases but very small ability to offset emissions. Market opportunities eaten up by ethanol, leaving us far short of the target.

19 Solution Other alt fuels allowed to go ahead of some of the sorghum ethanol even though more expensive in order to reach target.


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