Long-Term Stochastic Planning in Electricity Markets Under Carbon Cap Constraint : A Bayesian Game Approach

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Author(s)

Detail(s)

Original languageEnglish
Title of host publication2016 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia)
PublisherIEEE
Pages466-471
ISBN (Electronic)978-1-5090-4303-3
ISBN (Print)978-1-5090-5228-8
Publication statusPublished - Nov 2016
Externally publishedYes

Publication series

NameIEEE Innovative Smart Grid Technologies-Asia (ISGT Asia)
PublisherIEEE
ISSN (Electronic)2378-8542

Conference

TitleThe IEEE PES Innovative Smart Grid Technologies 2016 Asian Conference
LocationMelbourne Exhibition & Convention Centre
PlaceAustralia
CityMelbourne
Period28 November - 1 December 2016

Abstract

Carbon price in an electricity market provides incentives for carbon emission abatement and renewable generation technologies. Policies constraining or penalizing carbon emissions can significantly impact the capacity planning decisions of both fossil-fueled and renewable generators. Uncertainties due to intermittency of various renewable generators can also affect the carbon emission policies. This paper proposes a Cournot-based long-term capacity expansion model taking into account carbon cap constraint for a partly concentrated electricity market dealing with stochastic renewables using a Bayesian game. The stochastic game is formulated as a centralized convex optimization problem and solved to obtain a Bayes-Nash Equilibrium (Bayes-NE) point. The stochastic nature of a generic electricity market is illustrated with a set of scenarios for wind availability, in which three generation firms (coal, gas, and wind) decide on their generation and long-term capacity investment strategies. Carbon price is derived as the dual variable of the carbon cap constraint. Embedding the carbon cap constraint in the game indicates more investment on renewable generators and less on fossil-fueled power plants. However, the higher level of intermittency from renewable generation leads to a higher carbon price to meet the cap constraint. This paves the way towards storage technologies and diversification of distributed generation as means to encounter intermittency in renewable generation.

Citation Format(s)

Long-Term Stochastic Planning in Electricity Markets Under Carbon Cap Constraint : A Bayesian Game Approach. / Masoumzadeh, Amin; Nekouei, Ehsan; Alpcan, Tansu.

2016 IEEE Innovative Smart Grid Technologies - Asia (ISGT-Asia). IEEE, 2016. p. 466-471 7796430 (IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia)).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review