GAN
GAN training: tip 1
Reinforcement Learning
Usefull Resources
2. Data Types:
Weather data
Market data
SCADA data, PMU Data, smart meter data
networks data
outage data
customer data
GIS data
3. Research Needs
Data storage, access, and management- network compute
Data Science platform (secure, privacy, metadata & data management)b
visualization tool for reporting capability
Data policy and access
Data Science R&D lifecycle to make the use repeatable
Acquire - Store - Clean - report -Analyze
artificial intelligence: recognize the values in the data
Synthetic Data Sets
communication network data storage (secure and fast to retrieve, data management, processing power,
Goal: better and informative decisions
challenges: volume, variety, velocity, not structured data, have different qualities and integrity levels, can be bad or mission or outliers,
Techniques: determine the relevancy,
Applications: customized DR, asset management, EV/PV/Wind integration,
Should we use only real data? In other domain, data can be simulated data. They are also informative.
4. Tools and environment
HPC Environment (Linux Cluster), Numerous MS SOL instances, My SQL, MS Access, XLS, CSV, AWS data store
SQL, SAS, SPSS, Python, Matlab
5. Related Discussions