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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| Vydáno v: | 2015 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) s. 1 - 5 |
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| Hlavní autoři: | , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
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IEEE
01.11.2015
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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. |
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| 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 |
| Author_xml | – sequence: 1 givenname: Sebastian surname: Forsyth fullname: Forsyth, Sebastian email: sebastian.forsyth@uqconnect.edu.au organization: Sch. of Inf. Technol. & Electr. Eng., Univ. of Queensland, Brisbane, QLD, Australia – sequence: 2 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 – sequence: 3 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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