Optimization of static wind power investment in the Australian national electricity market

This paper studies the Australian market conditions and subsidies in place to promote the growth of wind power through the use of a stochastic linear programming model. This model optimizes the profit obtained for a static investment based on a variety of wind and price scenarios. It is subject to d...

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Published in:2015 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) pp. 1 - 5
Main Authors: Forsyth, Sebastian, Mahmoudi, Nadali, Saha, Tapan
Format: Conference Proceeding
Language:English
Published: IEEE 01.11.2015
Subjects:
Australia
Australian National Electricity Market
Decision support systems
Investment
Linear programming
optimization methods
planning
Reactive power
renewable energy target
Stochastic processes
stochastic programming
wind generation
Wind power generation
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Abstract This paper studies the Australian market conditions and subsidies in place to promote the growth of wind power through the use of a stochastic linear programming model. This model optimizes the profit obtained for a static investment based on a variety of wind and price scenarios. It is subject to different constraints which focus on the amount of initial capital injected by an investor, selling power through a Power Purchase Agreement (PPA) or using the Market Clearing Price (MCP). The Conditional Value-at-risk (CVaR) risk is also considered in this model to assist in differentiating between a risk-neutral and risk-averse investor. This has been evaluated for Portland on the coast of Victoria, Australia, using current data.
AbstractList This paper studies the Australian market conditions and subsidies in place to promote the growth of wind power through the use of a stochastic linear programming model. This model optimizes the profit obtained for a static investment based on a variety of wind and price scenarios. It is subject to different constraints which focus on the amount of initial capital injected by an investor, selling power through a Power Purchase Agreement (PPA) or using the Market Clearing Price (MCP). The Conditional Value-at-risk (CVaR) risk is also considered in this model to assist in differentiating between a risk-neutral and risk-averse investor. This has been evaluated for Portland on the coast of Victoria, Australia, using current data.
Author Saha, Tapan
Mahmoudi, Nadali
Forsyth, Sebastian
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  organization: Sch. of Inf. Technol. & Electr. Eng., Univ. of Queensland, Brisbane, QLD, Australia
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  givenname: Nadali
  surname: Mahmoudi
  fullname: Mahmoudi, Nadali
  email: n.mahmoudi@uq.edu.au
  organization: Sch. of Inf. Technol. & Electr. Eng., Univ. of Queensland, Brisbane, QLD, Australia
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  givenname: Tapan
  surname: Saha
  fullname: Saha, Tapan
  email: saha@itee.uq.edu.au
  organization: Sch. of Inf. Technol. & Electr. Eng., Univ. of Queensland, Brisbane, QLD, Australia
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Snippet This paper studies the Australian market conditions and subsidies in place to promote the growth of wind power through the use of a stochastic linear...
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SubjectTerms Australia
Australian National Electricity Market
Decision support systems
Investment
Linear programming
optimization methods
planning
Reactive power
renewable energy target
Stochastic processes
stochastic programming
wind generation
Wind power generation
Title Optimization of static wind power investment in the Australian national electricity market
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