Forecasting Meeting Minutes for Week of September 27, 2016

Present: Gordon, Brieanna, Jaimie

• More coordination with Seyyed

• 1. Well documented code
• 2. Learning abt signal processing/machine learning
• Reproducing what Masaki did
  • Visualizing Data w/ 3D plotting:
    • Contact Masaki
• Work on normalized data with Zenith Angle
• 3. Forecast Solar Irradiance
  • Recursive least squares
  • Least mean squares
• Machine learning aspect
• 4. Understanding solar data
  • PV and solar data (non-linear relationship)
  • Weather effects sudden changes in weather
    • Reserve or storage energy
    • Shift demands

* 2 types of algorithms:

• Regression/
• Classification (binary/descrete)/Detection
• Classification: Iris Problem
  • Linear threshold function: Hyperplane separating data (0 | 1)
    • 2 items from 1 item = possible