Abstract :
This track tackles issues related to renewable energy requiring problem solving techniques that can deal with imprecision, uncertainty, partial truth, and approximation to achieve low cost solutions that are robust and traceable. It includes topics such as Fuzzy Logic (FL), Neural Computing (NC), Evolutionary Computation (EC), Machine Learning (ML), and Probabilistic Reasoning (PR). Applications in this area may include modeling and simulations, diagnosis, Control, and monitoring of renewable energy process and systems.
