California Energy Modeling for Policy Analysis
California law (AB32) requires statewide greenhouse gas (GHG) emissions to be equal to 1990 levels by 2020 and the state has a goal to achieve an 80% reduction in GHG emissions from 1990 levels by 2050. These goals, especially the 2050 GHG reduction goal, have significant challenges. There is uncertainty on which technological, fuel and energy resource options will be used to help meet the deep reduction goal. Models such as CA-TIMES, a technology-rich partial-equilibrium model being developed by ITS Davis (partially funded by California Air Resources Board) can provide guidance as to the least-cost and most appropriate options to achieve these goals. It represents all the sectors of California energy system. One of the main features of the model is that it has a readily accessible and transparent technology and resource database. The purpose of the modeling exercise is not to predict the future, but to understand the least-cost technology mix assuming perfect decision making and perfect markets and to derive policy lessons, under different technology, resource and policy assumptions.
- CA-TIMES is a technologically rich, partial-equilibrium model that focuses on the energy system of California. It gives an understanding on how the specific selection of policies would impact the trajectory of technology and fuel/resource mix to the year 2050.
- The model includes all the current and future GHG-related policies for all the sectors in the State of California. It is built on a set of MS Excel data files that fully describes the underlying energy system, technology and demands.
- Detailed technology choice is represented in most energy end-use sectors (transportation, residential and commercial) and energy supply sectors (electricity and fuels supply)
- The model develops a portfolio of scenarios exploring the transition to a low-carbon future specifically focusing on 2020-2050.
- Several variants of the Deep GHG scenario are also developed, in order to explore important sensitivities related to the stringency of the emissions cap and the ultimate potential of key resources and technologies to contribute to greenhouse gas mitigation.
- The model relies on insights from other STEPS research, such as infrastructure system design, electric vehicle time-of-day charging, modal switching, combining urban planning and VMT to look at low VMT/low carbon futures.
“CA-TIMES” is a technologically-rich, integrated energy-engineering-
Schematic structure of CA-TIMES model
In Phase I of the CA-TIMES project, scenario analysis, and policy evaluations were carried out given the specific conditions that exist in California. Two major scenarios were developed in the model for analysis: (a) Business-As-Usual scenario and, (b) Deep GHG Reduction Scenario. The Deep GHG scenario has the set of policies, such that the GHG emissions are reduced to 80% of 1990 levels by 2050. In this phase, technological details were focused on the Transportation sector, and top-down approach was used for other sectors (commercial, residential, industrial). The analysis of these scenarios did not include the elasticity values of the end-use demands.
In Phase II, a number of modeling improvements are incorporated in CA-TIMES:
- Detailed energy service and technology representation for residential and commercial sectors
- Incorporate elastic demand analysis is incorporated for end-use demands.
- Updated technology and cost parameters in electricity, fuel supply and transportation sectors
- Improved representation of out-of-state renewable generation for meeting state’s renewable portfolio standard (RPS)
In Phase III, a number of modeling improvements are being developed for future inclusion in CA-TIMES:
- Improved representation of consumer heterogeneity in light-duty vehicle purchases and incorporating non-monetary values (utilities) in decision making
- A regionalized, hydrogen infrastructure model for California that accounts for economies of scale, regional differences in infrastructure requirements
- Flexible electric vehicle charging representation to co-optimize electricity generation and load management
Policymaker Summary: Modeling Optimal Transition Pathways to a Low Carbon Economy in California
Kalai Ramea, PhD Student
Saleh Zakeri, PhD Student