Increasing the pace of energy transition
Alexa Canaan SM ’23 recently graduated with a dual Master’s in the Technology and Policy Program and the Department of Electrical Engineering and Computer Science (EECS) at MIT. During her time at MIT, she held a research assistantship at the MIT Center for Energy and Environmental Policy Research (CEEPR), where she investigated how to use data and machine learning to improve energy policies. She served as President of the Technology and Policy Student Society from 2022 to 2023.
What was the focus of your research? What sort of knowledge and disciplines did it bring together? How can it make an impact?
Broadly speaking, my research with CEEPR was primarily focused on using economic principles, data science methods, and domain-knowledge in energy and environmental economics to motivate policy ideas for utilities, federal energy regulators, and governments. I was lucky enough to work on two different projects that both required that I flex my ability to synthesize technology and policy. Before graduation, I had been investigating the policy bottleneck in the interconnection queue for renewable energy projects trying to connect to the grid. For this project, I needed to understand the US energy regulation space and use my data analysis skills to collate the policy information into a singular dataset. This dataset and subsequent analysis have the potential to increase the pace of energy transition exponentially, if we’re able to increase the pace of interconnection.
During my research assistantship, I developed a methodology that utilities can use to analyze their smart metering data to benchmark the energy savings potentials of a variety of household classes, working with a partner utility company of CEEPR. This methodology will help utilities to manage the big-data of utilities (smart meter data), allowing them to create potential demand-response measures that better predict energy consumption in the energy marketplace.
Why did you choose to come to TPP?
Prior to TPP, I worked in the fintech space as a data lifecycle specialist and as a data analysis intern in the NGO space. I saw how starkly different these two industries treated and understood their data. From these two experiences, I could draw direct comparisons between the data standardization in these industries and how efficient they were. I came to understand how crucial data analysis skills are and how important good data is to operating an organization at any level efficiently and with low risk. I wanted to continue to understand how other industries could come to standardize their own types of data to yield better insights. TPP seemed like the perfect place where I could hone my technical skills, while also being able to explore and tackle questions like: what is good data and how much does it matter?
You presented at the Women in Data Science (WiDS) – Cambridge conference. Tell us about your presentation!
I am so grateful for the opportunity to have been able to present at the WiDS – Cambridge conference. I was able to give a lightning talk on my smart meter data methodology, and speak directly with other attendees about my work at my poster session. I was able to present my research methodology in a dashboard visual format that highlighted what my algorithms and script would look like to a sample residential energy consumer. It really brought my research to life and highlighted how my complex analysis could be broken down into incredibly simple, digestible, and actionable insights for consumers to take agency in their energy consumption.
What was a highlight of the conference?
The highlight of the conference was feeling as though I was welcomed into the data science community! It was incredibly validating to present my research to people and have them assure me that the work I am doing is important and impactful. I was also able to learn from so many incredible women about their research projects, including some fellow TPPers. A particular moment that stuck with me: at the end of the conference, as I was packing up my poster, a few attendees sparked a conversation with me about my research, but also the intersection of data science and energy more broadly. We ended up staying an hour past the end of the conference, but it was so fun to get swept away in conversation with people who shared my curiosity and passion for the topic.