6.S963 Final Paper 7/1/2024

Lilian Alves
Massachusetts Institute of Technology

Abstract:

Over the last 20 years, the power grid has experienced the most complex transformations ever seen in its 40-year history. The emergence of new technologies such as wind and solar power generation, energy storage, electric vehicles, “prosumers” (consumers who can produce their own energy), smart devices, and Internet-of-Things (IoT) have created new uses and challenges that the grid was not planned for. Climate extreme events such as snowstorms, droughts, and wildfires test the power system’s resilience. As a result, the grid has become more volatile, more exposed to risks and uncertainties, and “peakier”.

While data science can be applied to optimizing generation, transmission & distribution, and retailing, this paper primarily focuses on demand-side applications such as tariff structures and regulation, net metering, demand response, virtual power plants, and time-of-use pricing. We used the Analysis Rubric presented in class to evaluate these data science applications.

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Full Paper

Disclaimer

This paper was written for Alfred Spector’s MIT Spring 2024 course 6.S963 Beyond Models – Applying Data Science/AI Effectively. It has not been peer-reviewed, and it may contain errors.