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Impact of weather dependency on planning decisions in the Australian national electricity market

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

A long-term planning method for the electricity market is to simulate market operation into the future. Outputs from market simulation include indicators for transmission augmentation and new generation investment. A key input to market simulations is demand forecasts. For market simulation purposes, regional demand forecasts for each half-hour interval of the forecasting horizon are required, and they must accurately represent realistic demand profiles and interregional demand relationships. In this paper, a demand model is developed to accurately model these relationships. The effects of uncertainty in weather patterns and inherent correlations between regional demands on market simulation results are presented. This work signifies the advantages of probabilistic modeling of demand levels when making market-based planning decisions.
Original languageEnglish
Title of host publication7th IET International Conference on Advances in Power System Control, Operation and Management (APSCOM 2006)
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event7th IET International Conference on Advances in Power System Control, Operation and Management, APSCOM 2006 - Hong Kong, China
Duration: 30 Oct 20062 Nov 2006

Publication series

NameIET Conference Publications

Conference

Conference7th IET International Conference on Advances in Power System Control, Operation and Management, APSCOM 2006
PlaceChina
CityHong Kong
Period30/10/062/11/06

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

  • Power generation planning
  • Power system planning
  • Power system simulation

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