Reports

How to use:

  1. Choose a forecasting model
  2. Select a campus to view its data
Model
Campus
Line Chart - Interactive
Showing Actual vs Predicted Electricity Consumption

Essential Details of Public School Dataset

Public School Cleaned Data Distribution
Distribution of cleaned data points across different Public Schools
Public School 1: 81
Public School 2: 57
Public School 4: 55
Public School 5: 78
Public School 6: 55
Public School 7: 71
Public School 8: 14
Public School 9: 56
Spearman Correlation Results
View the correlation matrix showing the statistical relationships between different variables used in the forecasting model.
Exogenous Variables
Environmental and demographic factors used in the forecasting model

Weather Parameters

VariablesUnits
Wind Speedmeters per second (m/s)
Relative Humiditypercent (%)
Temperature Meandegrees Celsius (°C)
Temperature Maxdegrees Celsius (°C)
Temperature Mindegrees Celsius (°C)
Wind Directiondegrees (° from true north)
Rainfallmillimeters (mm)

Population Data

VariableDescription
Total PopulationTotal residents per public school catchment area

Note: These exogenous variables provide crucial environmental and demographic context that influences electricity consumption patterns across different public school locations.