Robust, Efficient, and Scalable Control of Hybrid Energy Systems usingArtificial Intelligence Planning

In the energy industry, as a result of global warming, population growth, and environmental, political, and
economic considerations, a fundamental shift in technology is expected. To address this, in this project we
propose to test the applicability of our Artificial Intelligence technology for solving a challenging computational
problem in the energy sector. We anticipate that our approach can offer significant benefits over currently
employed techniques.

Faculty Supervisor:

Mikhail Soutchanski

Student:

Shakil M. Khan

Partner:

I-INC Foundation for Business Development

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Ryerson University

Program:

Accelerate

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