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 of now there are as many as 12 electricity retailers competing to sell you their energy package. Each retailer charges a price lower than the tariff price set by Singapore Power which is the de facto energy retailer unless you make the effort to switch to private electricity retailers. These retailers are competing on low prices to woe consumers to switch to a private retailer. One of the business challenges face by these retailers is the lack of knowledge of accurate demand forecast for electricity. These retailers do not produce electricity, instead, they bulk purchase electricity from electricity generating companies and subsequently sell the electricity to their customer. A poor forecast of demand of electricity results in electricity being wasted and revenue lost.  
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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.
 
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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 find more out precisely, down to the postal code level, the average demand of electricity to provide these electricity retailers a picture of how much electricity is needed in the grid.
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To achieve that we will be using 2 different techniques:
 
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<ul>1. Small area estimate</ul>
 
 
We will be using 2 different techniques:
 
<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

TEAM

 

PROPOSAL

 

POSTER

 

APPLICATION

 

RESEARCH PAPER


Group Members
  • Edwin Lim Jun Yun
  • Maegan Joyce Wu
  • Wong Ming Sen

  • 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