Ansar Lemon

MIT Department: Nuclear Science and Engineering

Undergraduate Institution: Cornell University

Faculty Mentor: Jacopo Buongiorno

Research Supervisor: Nestor Sepulveda

Website: LinkedIn

2018 Research Poster

Biography

I grew up in Kansas City, Missouri but now live in Watertown, Massachusetts. I am a rising senior at Cornell University majoring in engineering physics and minoring in applied mathematics. After graduating, I intend to pursue a PhD in physics or engineering and conduct research in a renewable energy related field. I am also heavily involved with music as I play the piano, guitar, sing, and write music. I also enjoy eSports and am one of the original founding members of the club Esports at Cornell.

2018 Research Abstract

GenX Tool: Planning Power Systems for Net-Zero Carbon Emissions

Ansar Lemon1, Nestor Sepulveda1 and Jacopo Buongiorno1

1Department of Nuclear Science and Engineering, Massachusetts Institute of Technology

There is a scientific consensus that climate change mitigation will demand power systems worldwide to reach net-zero carbon emissions in order to prevent potentially catastrophic weather conditions. This means we must reduce the use of CO2 emitter technologies in our power systems, replacing them instead with clean energy technologies. Using all of the available clean energy technologies – such as solar, wind, nuclear, and so on – will be mandatory for achieving this goal of carbon neutrality. The question which follows is: How can this be optimally attained? To answer this, the GenX tool is being developed and used. It analyzes data for all the currently available clean energy solutions, or those which are specified by the user, and determines the best set of planning investment and hourly operation decisions to fulfill electricity demand at a minimum cost while keeping emissions below a pre-specified limit. This is done via mixed-integer linear programming. While GenX is functional already, it needs various improvements. My work focuses on improving the usability of the software, as current use of the software requires knowledge of the backend coding. The GenX software also requires long computing times, lowering the number of calculations that can be performed with the software in a given time-frame. I have therefore created a web-based user-interface to help solve both issues. The GenX software can now be more easily used to test more sets of data, allowing us to better analyze the optimal way to deploy and use clean energy technologies.