Engaging Communities in the Design of Sustainable Energy and Localized Futures (SELF) Models in California's San Joaquin Valley

Through the analysis of "big data" comprising remotely-sensed images an GIS layers, this project is developing an analysis that examines specific dense urban areas with both high potential for retrofits that can help meet the needs of SJV communities

The Regents of the University of California, Berkeley Campus


Berkeley, CA

Recipient Location


Senate District


Assembly District



Amount Spent



Project Status

Project Update

The research team developed a GIS-based dataset for the southern San Joaquin Valley (SSJV) that incorporates a number of layers including population density, built environment, environmental impact, CalEnviroScreen, electrical load, distributed generation, land use, and other data to aid in the development of SELF communities in the SSJV. The research team used this dataset and collaborated with a local community benefits organization, Self Help Enterprises (SHE), to identify six communities with the highest potential for a deeper-dive case study application of the SELF approach. The team is currently working with SHE to perform a household survey of approximately 1,000 households across the six communities to collect more detailed information about demographics, energy use, and willingness to adopt energy upgrade measures.

The Issue

Interdisciplinary analysis is critical for understanding the potential for energy transformation around the interface of dense urban environments with agricultural lands, communities, and natural resources. This research specifically addresses the people and communities most affected by development in these "urban-agriculture interface zones." This project aims to advance the engagement of communities in the design of Sustainable Energy and Localized Futures (SELF) models in California's San Joaquin Valley.

Project Innovation

Through the analysis of "big data" comprising remotely-sensed images (e.g. agriculture lands, road networks, and built environment) and Geographic Information System (GIS) layers (e.g., energy consumption, distribution networks, new build construction, reserve areas, and planning documents), the project team is developing an analysis that examines specific dense urban areas with both high potential for retrofits that can help meet the needs of disadvantaged communities. Through the identification of critical "Urban-Agriculture Interface Zones" using a GIS-based hot spot analysis across the southern San Joaquin Valley, the project identifies and engages with communities (with community-based organizations) to conduct Sustainable Energy and Localized Futures (SELF) modeling. This project identifies opportunities in the SELF communities for efficiency and energy system improvements based on analysis of energy optimization tools such as the Solar, Wind, Investment in Technology, Hydropower (SWITCH) model. An optimization model is being developed for these densely populated zones to design "SELF- SWITCH" systems (SELF-SWITCH model).

Project Benefits

This research is advancing the state of the art by developing a new model that can explore the cost and feasibility of generation, transmission, and storage options for the future electricity system in a sub-regional environment. The model identifies cost-effective investment decisions for meeting electricity demand, taking into account the existing grid as well as projections of future technological developments, renewable energy potential, fuel costs, and public policy. Integrating this model with updated GIS and geographically relevant data and algorithms for a sub-regional development will assist California's energy system planners.

Lower Costs


The project will lower long-term costs through identification of transformational system upgrades that will deliver less costly energy services in dense urban zones.

Greater Reliability


The project will result in the ratepayer benefits of greater reliability by identifying environmental and system risks of meeting transformational system upgrades in the southern San Joaquin Valley region.

Key Project Members

Project Member

Daniel Kammen

Principal Investigator
University of California Berkeley

Contact the Team