Powering the Transition: Data Science for Smarter Energy
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Please join Charlottesville Data Science for a double-feature on the data science powering humanity's transition to smarter, cleaner energy. Manaar Salama, a Data Operations Analyst at RECmint, will explore how machine learning is improving solar forecasting — helping maintain grid stability and ensuring the economic viability of renewable energy. Next, Charlie Henderson, founder and CEO of Stacker Group, will dive into real-time decisioning architecture, showing how closed-loop systems can sense, decide, and act at millisecond speed. Together, these talks illuminate how data science is reshaping energy systems from the rooftop to the grid.
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Talk 1: Solar Forecasting: Driving the Shift from Gas to Grid
The transition to a less gas-driven, more-electrified future is a critical step in addressing climate change, but it relies heavily on our ability to predict the unpredictable. As solar energy becomes a key variable of this shift, the vast amounts of data generated by residential systems present a unique opportunity. Accurate forecasting is becoming a necessity for maintaining grid stability and ensuring the economic viability of renewable energy for homeowners.
In this talk, Manaar Salama will explore the intersection of data science and solar energy, focusing on the growing landscape of the Mid-Atlantic. She will discuss the challenges of modeling energy production data and how machine learning is being used to solve problems — such as ensuring accurate estimations so that homeowners’ SREC (Solar Renewable Energy Certificate) payments are processed without delay. By the end of this presentation, attendees will understand the key role of predictive modeling in the green energy transition and how ML can remove financial friction for everyday users.
This talk is relevant for data analysts, scientists, or professionals in the energy industry, as well as anyone interested in how data science can drive real progress toward sustainability.
Talk 2: Next Best Action: Architecting the Future of Model-driven, Real-time Decisioning
The energy sector requires real-time decision-making. “NBA” (Next Best Action) is an architectural pattern that brings more data into the context of every decision, while enabling continuous learning. Charlie Henderson, founder and CEO of Stacker Group, will break down how real-time decisioning combines millisecond-speed execution, continuous data integration, and live decision context to move beyond batch-based decisioning. You'll see how closed-loop systems that sense, decide, act, and learn make it possible to deliver fast, in-app AI decisions, with fewer trade-offs.
