====== Forecasting Meeting Minutes for Week of September 13, 2016 ====== 
** Present: Gordon, Brieanna, Jaimie **

===== Updates =====
   * Modified Meeting Hours:  Tuesday 4:30-7:00 & Thursday 4:30-7:00

Saturday, September 10, 2016 (Proposal Presentations)


Tuesday, September 13, 2016
  * Produce:
    * Well-written code
    * New python libraries to pull off of
    * Build library of functions other groups can use
    * Solar Industry
    * Calibrate Data
  * Decisions:
    * Normalization Method (Zenith Angle?)
    * Prediction time (1 hr?)
    * Solar Irradiance doesn't need to be sampled too quickly (1-2 mins ok)
  * Understanding PV:
    * How much in Hawaii
      * Commercial and residential
      * Projection of these
    * Solar Thermal
    * Solar Farms
    * Concentrated Solar
    * Energy Production
      * PV Data Sheets
      * 10-15% efficiency w/ lower cost panels
      * 40% efficiency w/ increase in efficiencies, cost, etc.
    * Breaks for Federal and State and HECO
      * Larger contracts (PPA)
  * Forecasting:
    * Weather and time series prediction
    * Predicting an hour
    * Reasonable with just Least Squares
      * Depends on normalization (ex. subtract mean of specific time of day/std, or zenith angle)
      * Take **zenith angle**: Time of day and day of year in account
    * Window (FIR filters)
      * Straight average of data over time   
  * Online Methods:
    * Estimate of parameter weight and update estimate based on new data
    * New linear estimate
    * Recursive Least Squares (RLS)
      * Depends on first and second order (mean and covariance matrixes)
    * Least Mean Squares (LMS)
      * Won't perform as well
  * Supervised and Unsupervised Learning:
    * Nearest Neighbor (supervised)
    * Support Vector Machine Kernels ()
    * Deep Learning ()
    * Clustering used for large dimensional data (unsupervised, Lots of factors)
  * Estimation (regression) and Detection (classification)


===== Reminders =====
  * Weekly REIS Thursday Seminar 4:30-5:30