Development of a model to relate electricity supply disruption and designated causal factors
ETSA Utilities, Adelaide South Australia
Mr Jim Whaites (email@example.com)
Mr. Ben Thompson (firstname.lastname@example.org)
Dr. John Boland UniSA (email@example.com)Prof. Bill Whiten UQ (firstname.lastname@example.org)
ETSA Utilities has its roots in the privately owned Adelaide Electric Supply Company, which was created in 1904 following the closure of the Port Adelaide electricity plant. The Government of South Australia established the Electricity Trust of South Australia (ETSA) in 1946 as a publicly owned utility responsible for all aspects of providing electricity to the state. From its inception, ETSA played a pivotal role in the development of the state of South Australia.
With the advent of deregulation, the state government formed ETSA Corporation. The corporation was disaggregated between 1996 and 1998 into several separate business entities, with ETSA Utilities responsible for distribution. ETSA Utilities is now a member of the Cheung Kong Group of companies, being leased by CKI Holdings Limited and Hongkong Electric Holdings Limited.
With over 734,000 customers and a distribution network of 73,111 km of lines, ETSA Utilities is looking ahead to an exciting future built on a century of trust.
ETSA Utilities (EU) distributes electricity to consumers across South Australia. EU is responsible for operating and maintaining the consumer end of the power supply network in this region. For the most part their lines distribute power at 11 kilovolts or less, but do operate lines up to 66 kilovolts between substations. EU measures their electrical performance as a distributor by using three basic inter-related statistics calculated over various time intervals and geographic regions. The three statistics are the System Average Interruption Duration Index (), the System Average Interruption Frequency Index () and the Customer Average Interruption Duration Index (). For those of you who are mathematically gifted it will be clear that
ETSA Utilities use as a basic measure to evaluate supply interruptions and record up to five discrete components/details of duration and customers affected for each incident to calculate as
and for many incidents
Similarly, EU calculate using the relationship for a single incident as
and for many incidents
ETSA Utilities also calculates the measure , the average interruption duration. A fourth measure is also determined, one that calculates the time taken to restore 80% of the customers affected by interruption(s). For each incident the data held by ETSA Utilities also includes the geographic region to which the network belongs and the cause of the interruption. The geographic region is recorded as Central Business District, Metropolitan, Rural or Remote although the first two are often combined as Urban. The causes are listed as Weather, Equipment Failure, Unknown, Operational, Third Party, Other or Planned.
ETSA Utilities performance is monitored by an independent electricity regulator (South Australia Independent Industry Regulator SAIIR) with respect to the requirements of the SA Distribution Code. EU is required to meet or exceed explicit reliability performance standards that involve the indicators of , , & 80% restoration time. If any of the indicators are significantly higher than the agreed target then the Code imposes a financial penalty on EU while if the indicators are significantly lower then EU receives a financial bonus. ETSA Utilities is keen to improve customer service and believes it can do this more effectively by examining the statistics with a view to identifying the regions where supply interruptions are likely to occur and the causes of those interruptions. They would also like to determine any significant trend in the statistics. ETSA Utilities have identified the following problem for MISG 2002.
ETSA UTILITIES Problem
Examine the ETSA Utilities data to
The calculations and the model should be applied to each BOM district and to the whole state. Experience suggests that the dominant causal factors may vary from district to district and that seasonal considerations may also be significant. The question of direct dependence of the model on weather conditions and the precise relationship between the first and second questions should also be considered.
ETSA Utilities have contracted Dr John Field to undertake some preliminary statistical analysis that will ensure that the necessary data is available in a user-friendly form and that some fundamental statistical analysis is available to the meeting. John has been asked to undertake the following analysis.
There are many detailed aspects of the data for this problem and of the specific findings that must remain confidential. The published findings will be illustrated with simulated data if necessary.