ELECgrid Proposal
Singapore is rolling out its plan for the privatisation of the electricity market. Currently, there are as many as 12 electricity retailers who typically charge a price lower than that set by Singapore Power – the de facto energy retailer. These retailers purchase electricity in bulk from electricity generating companies. At the moment, electricity retailers are unable to forecast electricity consumption accurately with the kind of data available publicly (average electricity consumption per postal code). This inevitably means that retailers are not buying a close enough amount of electricity to meet the actual electricity demand of their customers. Resources and potential revenue are therefore being wasted and lost because of this. This project therefore utilises Small Area Estimate to improve accuracy of forecasting by combining the already available data on average electricity consumption per postal code and other auxiliary information.
To reduce electricity retailers’ cost and wasted resources by accurately estimating the total monthly electricity consumption per subzone.
Ultimately, cost-savings for retailers would be passed onto the consumers. This is of great opportunity to look into as various consumers even our families are shifting into private-provided electricity.
| Label | Data Set | Format | Attributes |
|---|---|---|---|
| elec1 | Average Monthly Household Electricity Consumption Jan- June 2016 | xls |
|
| elec2 | Average Monthly Household Electricity Consumption Jul- Dec 2016 | xls |
|
| Singapore Residents by Subzone and Type of Dwelling June 2016 | shp |
| |
| Subzone_HDB_Postal | shp |
|
1. Small Area Estimate (SAE) - SAE is a statistical technique which involves estimating parameters for small sub-populations.
2. R Shiny Applications
