Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty

The output of wind turbine is volatile and difficult to predict. Energy storage can help wind turbine offset the deviation between forecast and actual output. Based on the concept of sharing economy, there will be more alliance for wind turbines and energy storage in the electricity market. However,...

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Autores principales:	Peiyue Li, Zhijie Wang, Jiahui Jin
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Wind-energy storage alliance regulation participation ratio bi-level optimization problem strategic bidding Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/d10f20a929ec452f892e41b2eb74914d
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id	oai:doaj.org-article:d10f20a929ec452f892e41b2eb74914d
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spelling	oai:doaj.org-article:d10f20a929ec452f892e41b2eb74914d2021-12-02T00:00:52ZMarket Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty2169-353610.1109/ACCESS.2021.3130185https://doaj.org/article/d10f20a929ec452f892e41b2eb74914d2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9624983/https://doaj.org/toc/2169-3536The output of wind turbine is volatile and difficult to predict. Energy storage can help wind turbine offset the deviation between forecast and actual output. Based on the concept of sharing economy, there will be more alliance for wind turbines and energy storage in the electricity market. However, an open question is how the wind-energy storage alliance’s participation affects market clearing and the profits of market participants. Therefore, a stochastic bi-level optimization model is proposed to describe the bidding behavior of wind-energy storage alliances in energy and frequency regulation markets. At the same time, a new quantitative index of bidding behavior is defined—regulation participation ratio. Considering the uncertainty of wind turbine output, the profits of wind-energy storage alliance are maximized in the upper level. The lower level minimizes the power purchase cost of distribution system operator (DSO) for the joint market clearing. The bi-level model is transformed into a mixed integer linear programming (MILP) model by Karush-Kuhn-Tucker (KKT) conditions, strong duality theory and large M method. Regulation participation ratio is set to different values in the case analysis, so as to analyze the influence of the alliance’s bidding behavior on market. Moreover, the economic impact of alliance on wind turbine and energy storage is compared.Peiyue LiZhijie WangJiahui JinIEEEarticleWind-energy storage allianceregulation participation ratiobi-level optimization problemstrategic biddingElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 156537-156547 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Wind-energy storage alliance regulation participation ratio bi-level optimization problem strategic bidding Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Wind-energy storage alliance regulation participation ratio bi-level optimization problem strategic bidding Electrical engineering. Electronics. Nuclear engineering TK1-9971 Peiyue Li Zhijie Wang Jiahui Jin Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty
description	The output of wind turbine is volatile and difficult to predict. Energy storage can help wind turbine offset the deviation between forecast and actual output. Based on the concept of sharing economy, there will be more alliance for wind turbines and energy storage in the electricity market. However, an open question is how the wind-energy storage alliance’s participation affects market clearing and the profits of market participants. Therefore, a stochastic bi-level optimization model is proposed to describe the bidding behavior of wind-energy storage alliances in energy and frequency regulation markets. At the same time, a new quantitative index of bidding behavior is defined—regulation participation ratio. Considering the uncertainty of wind turbine output, the profits of wind-energy storage alliance are maximized in the upper level. The lower level minimizes the power purchase cost of distribution system operator (DSO) for the joint market clearing. The bi-level model is transformed into a mixed integer linear programming (MILP) model by Karush-Kuhn-Tucker (KKT) conditions, strong duality theory and large M method. Regulation participation ratio is set to different values in the case analysis, so as to analyze the influence of the alliance’s bidding behavior on market. Moreover, the economic impact of alliance on wind turbine and energy storage is compared.
format	article
author	Peiyue Li Zhijie Wang Jiahui Jin
author_facet	Peiyue Li Zhijie Wang Jiahui Jin
author_sort	Peiyue Li
title	Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty
title_short	Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty
title_full	Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty
title_fullStr	Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty
title_full_unstemmed	Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty
title_sort	market impact of wind-energy storage alliance strategic bidding under uncertainty
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/d10f20a929ec452f892e41b2eb74914d
work_keys_str_mv	AT peiyueli marketimpactofwindenergystoragealliancestrategicbiddingunderuncertainty AT zhijiewang marketimpactofwindenergystoragealliancestrategicbiddingunderuncertainty AT jiahuijin marketimpactofwindenergystoragealliancestrategicbiddingunderuncertainty
_version_	1718404014087864320

Market Impact of Wind-Energy Storage Alliance Strategic Bidding Under Uncertainty

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