Historical Insights for Electricity Transition Scenarios in California and Flexible Energy Demand Modeling for Residential Air Conditioning with Improved Behavioral Specificity

Improving ability and tools to understand, anticipate, and shape energy use transitions in California

Ghoulem Research


San Rafael, CA

Recipient Location


Senate District


Assembly District



Amount Spent



Project Status

Project Result

The research team convened in-depth discussions with members from the CEC's Demand Analysis Office, Supply Analysis Office, Building Standards Office, and Research Division as they worked to refine their flexible residential air conditioning demand forecast model ("SIMSAND"). SIMSAND, a prototype model to enable exploration of impacts of a number of human factors on residential air conditioning demand, was enhanced to have the flexibility to explore scenarios related to technology policy, adoption, and projected climate change. Through an agreement with Canadian smart thermostat manufacturer EcoBee, researchers obtained a very large data set of thermostat settings from 'Donate Your Data' volunteer households. Researchers submitted a final report for publication and presented their work at the 2019 Behavior, Energy, and Climate Change Conference (BECC).

View Final Report

The Issue

Planning and executing an energy transition of the scale and scope envisioned by California is new territory. New types of information, processes, tools, and frameworks are needed. Fortunately, highly granular consumption data, advances in computational power, and high-resolution climate projections are available to support sophisticated analysis of transition scenarios. California has been revising its approach to energy planning and demand forecasting. This presents an opportunity for adoption of flexible demand modeling tools that conceptualize energy demand as a dynamic socio-technical system, using data streams to illuminate technology trends, policy choices, and consumer response.

Project Innovation

Analysis of quantitative and qualitative data sheds light on past energy technology transitions, planned and unplanned. The research team's analysis of these transition histories provided examples, principles and insights that can be used in future planning. Leveraging insights from historical technology transitions, the research team designed and tested a flexible, agent-based modeling platform ("SIMSAND") that enables researchers, utilities, and CEC demand modeling and forecasting staff to draw upon a wealth of empirical data as well as projected climate data to simulate dynamic residential demands for air conditioning. This model served as a proof of concept that might later be broadened to other energy uses and demand sectors. The model also illustrated the power of providing a platform that can draw on a variety of data streams available to illuminate energy consumption and potential transition trajectories, rather than representing key parameters as simple averages.

Project Benefits

Results improve the state's ability to estimate timing of technology penetration and accrual of benefits, and costs of desirable residential sector technologies. These results are key to improving the performance of efficiency measures outlined in AB 758 and the California Energy Code. They also support goals of CPUC's Energy Efficiency Strategic Plan, and inform updated estimates of timing and benefits as appropriate. Results portraying penetration and performance of key technologies (e.g., air conditioning) are expected to be of direct use in the scenario development and demand forecasts used in the Integrated Energy Policy Report.

Environmental & Public Health

Environmental Sustainability

The study developed a rigorous model that enables exploration of human dimensions that could hinder or enable the technologies that are essential in the transition to a deeply decarbonized electricity system.

Key Project Members

Project Member

Mithra Moezzi

Lead Researcher

Contact the Team