STUDY APPROACH & METHODOLOGY
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2.3 Decarbonization modeling and fuels infrastructure analysis Demand-side and supply-side models with high temporal, sectoral, and spatial49 resolution were integrated in this study to provide an economy-wide view on potential decarbonization pathways for California. This pair of models produces energy, cost, and emissions data over the 30‐year study period, 2020 – 2050. This modeling approach is similar in architecture to those used in other California decarbonization studies, such as the 2018 report by the CEC.50 Likewise, it is similar to the approach used in the 2020 CARB report51, while also employing a dedicated capacity expansion model for supply-side optimization, (see details in Appendix). The demand-side model estimates final energy demand in a bottom-up fashion, for each of the over sixty end-uses or subsectors of the economy, ranging from residential space heating to heavy-duty trucks. Demand estimates are based on user decisions about technology adoption and energy service activity levels. Energy efficiency and end-use electrification measures are incorporated in demand-side scenarios. The final energy demand for fuels along with time‐ varying (8760 hour52) electricity demand profiles are used as inputs to the supply-side model. The supply-side model used for this analysis is a linear programming model that combines capacity expansion and sequential hourly operations to find least‐cost supply‐side pathways. It optimizes annual investments for the electricity and fuels sectors to meet carbon targets and other constraints. It incorporates estimated final energy demand in future years from the demand-side modeling, as well as the future technology and fuel options available (including their efficiency, operating, and cost characteristics), and clean energy goals such as Renewable Portfolio Standards (RPS), Clean Energy Standards (CES), and carbon intensity. This model is able to reflect detailed interactions among sectors, represented by electricity generation, fuel production and consumption, and carbon capture. With high temporal granularity, the model allows for co‐optimized (electricity and fuels) supply‐side solutions while enforcing economy‐wide emissions constraints. This is important for accurate representation of the economics when electricity is used to produce fuels, for example when renewable over‐ generation is used for hydrogen production. The analysis then goes beyond what many other full decarbonization analyses have historically done, using the results of the economy-wide decarbonization modeling to assess the potential for investment in clean fuels infrastructure, additional potential costs associated with fuel-switching, and potential gas system decommissioning costs and savings.
49Spatial resolution refers to the model’s approach for projecting electric transmission expansion, as discussed in Section 2.1 (Overall Methodology), above. 50California Energy Commission, “Deep decarbonization in a high renewables future”, June 2018, available at: https://www.ethree.com/wp-content/uploads/2018/06/Deep_Decarbonization_in_a_High_Renewables_Future_CEC-500-2018-012.pdf. 51Energy+Environmental Economics, “Achieving Carbon Neutrality in California: Pathways scenarios developed for the California Air Resources Board”, October 2020, available at: https://ww2.arb.ca.gov/sites/default/files/2020-10/e3_cn_final_report_oct2020_0.pdf. 52To cover all hours in a year.
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