The following projects are Philomathia seed projects:
RECONCILABLE DIFFERENCES? EXAMINING THE GAP BETWEEN ENGINEERING PROJECTIONS AND EX-POST REALIZED GAINS FROM ENERGY EFFICIENCY INVESTMENTS
- Professor Meredith Fowlie (Agricultural and Resource Economics)
- Professor Catherine Wolfram (Business)
Professors Fowlie and Wolfram are conducting a state-of-the-art evaluation of the nation’s largest residential energy-efficiency program: the Weatherization Assistance Program (WAP). The American Recovery and Reinvestment Act (ARRA) committed $5 billion over two years to this important initiative. Federal funds are being used to improve the energy performance of dwellings of low-income families. The primary objective of this research project is to estimate household-level impacts of the energy‐efficiency retrofits administered through WAP and similar utility‐funded programs. The researchers will measure the direct causal impacts of weatherization on energy consumption and expenditures. The researchers will also examine the persistent gap between engineering projections and ex post realized savings from investments in residential energy-efficiency improvements. In particular, they will investigate behavioral responses to household efficiency improvements which can lead to increased demand for energy services.
This work will facilitate a comparison of WAP’s cost effectiveness relative to other programs that aim to reduce the negative externalities associated with energy consumption. Importantly, this analysis relies on a randomized control trial so the results will be highly credible. The project thus demonstrates proof of an important concept. There is broad consensus in the social-science research community that, under certain conditions, well-designed and implemented randomized control trials provide the most valid estimate of an intervention’s impact on outcomes of interest. There is no precedent for incorporating random assignment into energy-efficiency policy evaluation. The research will demonstrate how random assignment can be used to generate estimates of energy-efficiency policy impacts that are transparent, simple to explain, and free of selection bias.
ITERATIVE DESIGN AND ECONOMIC ANALYSIS OF A SOLAR-POWERED DC MICROGRAM FOR UNELECTRIFIED RURAL COMMUNITIES
- Professor Eric Brewer (Electrical Engineering and Computer Science)
- Professor Edward Miguel (Economics)
- Professor Seth Sanders (Electrical Engineering and Computer Sciences)
Roughly 1.3 billion people in developing countries still live without access to reliable electricity. These households will drive most of the medium-term growth in energy consumption. As expanding access using current technologies will accelerate global climate change, we must find novel solutions that displace fossil fuels and are financially viable for developing regions. The overarching goal of this team of engineers and economists is to design, build and field-test a scalable, sustainable electrification system based on renewable generation, for communities that are unlikely to gain access to the grid in the near term. They plan to do this by capturing high quality information about household energy demand in developing countries, and using these data to design and pilot a novel microgrid technology with innovative metering, payment and operating models in rural Kenya.This will be the first project to study the economic and technological aspects of rural electrification in Kenya from both on- and off-grid perspectives, with direct implications for other developing countries.
A COMMUNITY CLIMATE ACTION TOOL FOR U.S. CITIES AND COUNTIES
- Professor Dan Kammen (Energy and Resources Group)
- Chris Jones (Energy and Resources Group)
The goal of this project is to create a user-‐friendly online platform for city planners, residents, businesses and other actors to quickly identify the most promising greenhouse gas reduction strategies for any U.S. city. This project will build upon work previously conducted for the California Air Resources Board to develop a Local Government Decision-‐Support Tool (LGDST) for California. The LGDST is a spreadsheet-‐based tool that allows cities to 1) instantly view an estimate of greenhouse gas emissions resulting from all households, businesses and local government operations in the community, 2) evaluate the greenhouse gas reductions and financial costs and savings from a list of 60+ common measures, and 3) adjust any assumptions in the tool to develop a customized climate action plan for the community.
Unlike other GHG planning tools the LGDST’s smart default settings allow analysts to instantly engage with a default climate action plan that highlights the actions with the most potential in each community. The project team specifically intends to: 1) extend the smart default settings in the tool to all U.S. cities or counties, 2) increase the number of GHG mitigation measures from 40 to at least 60, and 3) develop an integrated open source application programming interface (API) that can be used to develop multiple third party software tools, (4) create a user-‐friendly user interface so city planners and residents can quickly develop customized climate action plans for each city, while learning from the input of other users, and 5) document the work in papers and public fora to increase transparency and public awareness of the tool’s benefits and limitations.
CLIMATE, WEATHER, AND FIRE: PROJECTED WILDFIRE EVENTS IN A WARMER WORLD
- Professor David Ackerly (Integrative Biology)
- Professor Max Moritz (Environmental Science, Policy and Management)
- Professor William Collins (Lawrence Berkeley National Laboratory, Earth Sciences Division)
This project team aims to develop and calibrate a new model for the occurrence and severity of large wildfires (>1000 acres) using historical data for California, and then to use the model to project the frequency and distribution of fire events under warmer future climates. The project will fill a gap in existing models of fire frequency and distribution, combining the PIs skills in modeling of vegetation, fire and global climate. The calibrated and extensible model we propose to develop would address the critical need for improved prediction of extreme events at local to regional scales enhancing societal resilience and contributing to climate adaptation planning to reduce loss of infrastructure in the face of rapid climate change.