Open and collaborative climate change mitigation planning for electric power grids

Global warming is one of the most significant problems facing humanity, and reducing emissions from the electricity sector is critical for mitigating global warming impacts. My work here focuses on developing computational tools to plan cost effective mitigation pathways for the electricity sector and using them collaboratively. The complexity and scale of globally transitioning electrical power grids away from fossil fuels over the coming decades will require a large-scale collaborative effort with effective coordination of many actors trained in diverse disciplines. Historically, energy-modeling efforts have tended to be siloed and fragmented between and even within research groups. In my research I have attempted to provide an alternative to that status quo by improving an open source renewable planning model, Switch, increasing its usability and accessibility to interdisciplinary researchers, and collaboratively applying it to mitigation planning.;We used the Switch model to conduct detailed research into cost effective mitigation pathways for the Western portion of North America, or the WECC power grid. We found that renewable portfolio standards were insufficient to meet climate stabilization goals, and more targeted policies were needed that specifically focused on emission reductions. We identified investment plans that could lead to dramatic decreases in emissions without significantly increasing electricity costs over the next twenty years by retiring coal and replacing it with natural gas and renewables while evolving the grid to better accommodate variable renewable energy.;Throughout this process, I made significant advancements to Switch as an analytical tool for collaborative work by interdisciplinary research teams. I initially increased the usability and lowered the learning curve while training colleagues who lacked computer science backgrounds, as well as developing execution workflows to increase reproducibility and leverage high performance workstations and computing clusters. I played a crucial role in developing detailed databases to describe the WECC electricity grid and calculating renewable energy potential at a high geographic and temporal resolution over a large area. I developed new techniques for describing policies and tracking both the renewable fraction and emission intensity of electricity. I developed techniques for simulating grid dispatch of investment portfolios on ~100x as many timepoints to better estimate reliability, costs and emissions. I used that instrumentation ability to improve sampling methods and solution quality. Interviews with current and potential users indicated a need for a completely open source software stack, streamlined workflows for data ingestions and processing, as well as a graphical front-end to complement the command line interface. These usability enhancements are the subject of ongoing and future work.;Overall, this open collaborative approach has proven quite successful. We trained four other research teams on two campuses to develop versions of this model for China, Chile and Nicaragua and to conduct a detailed systems-level analysis of Carbon Capture and Sequestration technologies. Those efforts led to recognition by the United Nations during the 2014 Climate Summit. The complete text of this dissertation is freely available online through the University of California Berkeley though other organizations may distribute this text behind a paywall. We have developed partnerships with a second academic campus, a consulting firm and Google who are all contributing to a new implementation of Switch in a completely open source software stack that supports stochastic programming and decomposition (Pyomo). We hope that the new version can serve as a open platform for evaluating and comparing research methodologies as well as supporting investment planning and policy analysis for consulting firms, government agencies, academics, utilities and NGOs. (Abstract shortened by ProQuest.).