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IGDT Opportunity Method in the Trading Framework of Risk-Seeker Demand Response Aggregators

Vahid-Ghavidel, Morteza; Catalão, João P. S.; Shafie-khah, Miadreza; Seyyedeh Barhagh, Sahar; Mohammadi-Ivatloo, Benham (2019-08-26)

 
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https://doi.org/10.1109/PTC.2019.8810601

Vahid-Ghavidel, Morteza
Catalão, João P. S.
Shafie-khah, Miadreza
Seyyedeh Barhagh, Sahar
Mohammadi-Ivatloo, Benham
IEEE
26.08.2019
doi:10.1109/PTC.2019.8810601
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https://urn.fi/URN:NBN:fi-fe202102195413

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© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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In this study, a non-probabilistic program is proposed to a trading framework for demand response (DR) aggregators. Both sides of the aggregator, including upper side and down side of this entity, have been taken into account. In the down-side of the aggregator, two popular programs are considered such as reward-based program and time-of-use (TOU) program, where DR is obtained from these resources. The acquired DR is being sold to the purchasers in the other side of the aggregator through DR options and fixed DR contracts. To the aim of increasing the desired target profit of risk-seeker aggregator, an opportunity function of information-gap decision theory (IGDT) is used to handle the uncertainty, which is solved in General Algebraic Modeling System (GAMS) software. This model is implemented in a realistic case study.
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