Prediction of Electric Grid Frequency for a state power generation using Artificial Intelligence

Solution  

An Artificially Intelligent software solution (prediction analysis) that provides  every 15 mins projection of frequency over the next 2 hours in 8 distinct points (corresponding to 15 mins each in the next 2-hour window)

Functional level Milestones

• Data Preprocessing
  • Data collection
  • Collation of data into a central database

• Exploratory Data Analysis (For Insights)
• • Data Manipulation
  • Plotting charts is involved wherever necessary
  • Statistical Stationarity test
  • Identifying Trend and Seasonality
  • Estimating and Eliminating (Differencing) Trend
  • Decomposing (Breaking TS into different charts/TS i.e. seasonality) ARIMA model parameter identification and modelling
  • Try different version of ARIMA models and set the baseline

• Data Pipeline
• • Data Augmentation (various standardized models tried)

• Network Design
• • Our Team will have to try and see different Network Architecture
  • Involves research as well
    • Simple LSTM (Starting Point)
    • Bayesian Forecasting

• Training Pipeline Design
• • Training Pipeline Design
  • Training Strategy

• Model Training
• • Assumed Training time for multiple passes of data

• Model Hyper-parameter tuning
• • Model fine tuning with various data-lag values to have the best accuracy subjective to performance
    • Model fine tuning with network architectural changes
    • Loss Function Addition
    • Data Augmentation Implementation

• BackTesting (With historical data)
• • Developing Accuracy metrics for data points
  • Test on different time series samples from the past overall performance
  • Measurement metrics

• Minor Feedback based adjustments

• Dashboard charting for frequency trend