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
Authors
Contributing authors:
Created by bsundberg on 2016/09/08 04:28.