Renewable Portfolio Integration
Why this use case matters
Recent initiatives by leaders across all industries have brought numerous new commitments to zero carbon emission goals and an accompanying surge in the construction of wind and solar generation over the next few decades. Not surprisingly, machine learning & advanced analytics can play a prominent role in assisting utilities and their customers with insights and recommendations on meeting these targets.
Gradient Descent, RMSProp, Stochastic Forecasting, Simulation, Cross-Entropy Method, Bracketing
Saving the world, just kidding, but kind of…integrate renewable energy sources into your existing portfolio with minimum disruptive effects to the existing customer base. ML automates & recommends optimal energy policies to current accounts, ensuring a smooth transition and reducing Greenhouse Gas emissions.