In the context of a Data Science mission, Gabriel Greenfield is supporting an energy leader on projects related to renewable energies.
To date, our work concerns solar energy projects (photovoltaics), others related to electric vehicles, as well as purely technical projects (statistics, computer development).
Our achievements
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Implementation of automated, daily calculations of metrics useful for studying different photovoltaic panels
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Modeling and forecasting the power generated by a photovoltaic panel using meteorological data
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Contributing to the team's Git repository to share and group code from different projects
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Participation in the team's technological monitoring: sharing new Data Science libraries, frameworks…
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Implementation of a proof of concept on a data sample using parameter sensitivity analysis methods in a complex physical system
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Implementation of anomaly detection algorithms on time series of power generated by solar energy
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Creation of an algorithm to recognize certain types of roofs from satellite images in order to identify buildings suitable for photovoltaic panels.
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Implementation of short-term (D+1/D+3) forecasting algorithms for the power used by electric vehicle charging stations
Our intervention allows our client to develop their expertise in renewable energies, and to benefit in particular from:
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Development of a roof type recognition tool to help clients determine the most suitable buildings for installing photovoltaic panels
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Access to daily physical metrics facilitating the work of business experts
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Improvement of power generation forecasting models for photovoltaic panels
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Developing algorithms to better predict daily electricity consumption, particularly at electric vehicle charging stations
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Acquisition of codes enabling an initial approach to various useful methods in Data Science, such as time series data cleaning or anomaly detection
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Providing and consolidating theoretical and technological knowledge in Data Science and Statistics
Client benefits
Our added value
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Integration of high-quality scripts adapted to the existing client infrastructure
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Automation of data analysis, transformations, and cleaning
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Skills across the entire data chain, in pure Data Science as well as in Data Engineering
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Clear and concise presentations of the results obtained