Difference between revisions of "ELECgrid"
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| − | As we speak, Singapore is rolling out its plan for the privatisation of the electricity market. | + | As we speak, Singapore is rolling out its plan for the privatisation of the electricity market. There are currently as many as 12 electricity retailers competing to sell their energy package, and each retailer charges a price lower than the tariff price set by Singapore Power - the de facto energy retailer. These retailers also purchase electricity in bulk from electricity-generating companies instead of producing their own, subsequently selling the resource to their customers. One of the challenges faced by these retailers is the lack of accurate demand forecast for electricity. This is a key issue as a poor forecast of demand for electricity results in the resource being wasted and revenue lost for the company. |
| − | + | Our project therefore aims to estimate the total monthly electricity consumption per housing units to provide these electricity retailers a picture of how much electricity is needed in the grid | |
| − | Our project aims to estimate the total monthly electricity consumption per housing units to provide these electricity retailers a picture of how much electricity is needed in the grid | + | To achieve that we will be using 2 different techniques: |
| − | |||
| − | To achieve that | ||
<ul>1. Small area estimate</ul> | <ul>1. Small area estimate</ul> | ||
<ul>2. Geographic segmentation with spatially constrained cluster analysis </ul> | <ul>2. Geographic segmentation with spatially constrained cluster analysis </ul> | ||
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Latest revision as of 14:06, 5 March 2019
| Group Members |
| Project Description |
As we speak, Singapore is rolling out its plan for the privatisation of the electricity market. There are currently as many as 12 electricity retailers competing to sell their energy package, and each retailer charges a price lower than the tariff price set by Singapore Power - the de facto energy retailer. These retailers also purchase electricity in bulk from electricity-generating companies instead of producing their own, subsequently selling the resource to their customers. One of the challenges faced by these retailers is the lack of accurate demand forecast for electricity. This is a key issue as a poor forecast of demand for electricity results in the resource being wasted and revenue lost for the company. Our project therefore aims to estimate the total monthly electricity consumption per housing units to provide these electricity retailers a picture of how much electricity is needed in the grid To achieve that we will be using 2 different techniques:
- 1. Small area estimate
- 2. Geographic segmentation with spatially constrained cluster analysis
