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