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- W4214689843 abstract "China has made clear its goal to peak CO <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</inf> emissions before 2030 and achieve CO <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</inf> neutrality before 2060. Emission-trading (ET) is widely deemed as an efficient way to mitigate the emission of CO <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</inf> . The power industry is the largest emitter of CO <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</inf> in many countries and regions, and hence the implementation of the ET will certainly have important impacts on the operation of electricity markets and further on the development of the power industry. Given this background, the issue of strategic bidding with emission-constrained for generation companies(Gencos) participating in a day-ahead electricity market is investigated. The price of the CO <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</inf> emission allowance on the trading day is predicted first. Then under the assumption that each Genco has incomplete information and bids a linear function through estimating the electricity load and rivals' strategies, a stochastic optimization model is presented and used for building the risk-constrained optimal bidding strategy for the Gencos. Finally, the solving method is developed." @default.
- W4214689843 created "2022-03-02" @default.
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- W4214689843 date "2021-10-22" @default.
- W4214689843 modified "2023-10-18" @default.
- W4214689843 title "Strategic Bidding of Emission-Constrained Generation Companies with Incomplete Information in Day-Ahead Electricity Markets" @default.
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- W4214689843 doi "https://doi.org/10.1109/ei252483.2021.9713228" @default.
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