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Past Project in Detail

Energex - analysis of domestic electricity load patterns (pt 2)

24/09/2003

ENERGEX

Project duration: 2nd semester, 2003

Student: Luke Price, UQ B.Electrical Engineering

BACKGROUND

Energex is a government-owned company, responsible for managing sophisticated energy distribution networks and delivering energy products, services and expertise throughout Eastern Australia and New Zealand. Based in S.E. Queensland, Energex has an 80 year operational history and was previously known as the South East Queensland Electricity Board (SEQEB) prior to energy industry deregulation.

Energex has noticed that domestic customer load patterns have changed significantly in the last couple of years. The greater penetration of significant end-use loads such as air conditioning have generally resulted in greater than expected yearly growth in Maximum Demands. Additionally, the distribution system has recently experienced and seems sure to continue experiencing peak summer loads, as opposed to the traditional peak winter loads.

Thus, Bevan Holcombe, Network Strategic Planning Manager, Energex identified this as an area that requires research in order to understand the ways in which customers use electricity and the patterns which model such usage.

This is the 2nd stage of a large project, designed to improve Energex’s understanding of domestic customer energy demand, especially in the peak summer period. This information will be used to improve Energex’s forecasting accuracy, so that consumers experience a more consistent electricity supply, even at peak periods.

The 1st stage of the project was completed in 1st semester, 2003 by QUT B.Electronic Engineering / B.Information Technology student, Reuben Maguire (see separate Energex project description - part 1).

PROJECT OBJECTIVES

In this stage of the project, Luke’s objectives will be to:

· Analyse customer load profiles and correlate with results from questionnaire developed by Reuben Maguire in stage 1, and the total energy use

· Assign customer classifications to all distribution transformers using Census data and land use classifications

· Determine sample population for each customer classification, to be used for calculating After Demand Maximum Demand (ADMD) at a 95% confidence limit

Luke is due to complete his project end-November 2003.

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