Zhu, J-H, Li, K orcid.org/0000-0001-6657-0522, Xu, R et al. (3 more authors) (2021) Energy Storage Capacity Optimization for Deviation Compensation in Dispatching Grid-Connected Wind Power. In: Recent Advances in Sustainable Energy and Intelligent Systems: 7th International Conference on Life System Modeling and Simulation, LSMS 2021 and 7th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2021, Han. 7th International Conference on Life System Modeling and Simulation, LSMS 2021 and 7th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2021, 30 Oct - 01 Nov 2021, Hangzhou, China. Springer, Singapore , pp. 97-109. ISBN 978-981-16-7209-5
Abstract
Many uncertain factors in wind power forecasting lead to large prediction errors. Various prediction technologies have been developed to reduce errors and improve the dispatch-ability of grid-connected wind power. To install energy storage systems is an effective approach to reduce the scheduling deviation in dispatching the grid-connected wind power. This paper considers the optimal capacity allocation, a key issue in smoothing the grid wind power generation and integration. Based on the analysis of wind power prediction technologies and the resultant prediction deviations, the relationship between the distribution characteristics of wind power prediction errors and energy storage capacity demand is first investigated. Then, an optimization method is proposed, considering the stability of grid operation and the relationship between compensation necessity and load changes. Further, load fitness factor is introduced in processing the deviation data samples, together with an economic dispatch model for the deviation compensation, considering the operation costs. Finally, based on the analysis of various factors, the technical route to achieve energy storage capacity allocation for scheduling deviation compensation is proposed. Case studies are also presented to demonstrate the effectiveness of the proposed approach.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer Nature Singapore Pte Ltd. 2021. This is an author produced version of a conference paper published in Recent Advances in Sustainable Energy and Intelligent Systems: 7th International Conference on Life System Modeling and Simulation, LSMS 2021 and 7th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2021, Hangzhou, China, October 22–24, 2021, Proceedings, Part II. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Wind power dispatching; Deviation compensation; Prediction error distribution characteristics; Storage capacity |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 Oct 2021 13:10 |
Last Modified: | 19 Oct 2022 00:17 |
Status: | Published |
Publisher: | Springer, Singapore |
Identification Number: | 10.1007/978-981-16-7210-1_10 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:179568 |