E3S Web Conf.
Volume 107, 20192019 4th International Conference on Sustainable and Renewable Energy Engineering (ICSREE 2019)
|Number of page(s)||4|
|Section||Power Electronic System|
|Published online||05 July 2019|
Robust energy storage allocation for transmission grid integrated by multiple wind farms
State Grid Jiangsu Electric Power Co., Ltd., Nanjing 210000, China
2 East China Electric Power Design Institute Co., Ltd., Shanghai 200063, China
* Corresponding author: firstname.lastname@example.org
Since optimal planning for energy storage sizing and locating is critical to meet the requirement of total wind power absorption, a robust optimization theory based energy storage allocation model for transmission grid with multiple wind farms integrated is proposed in this paper. The model fully considers the transmission capacity limitation, and uses linear decision rule to optimize the allocation of the reserve capacity of the adjustable units and energy storage devices to cope with the fluctuation of wind power, which makes full use of the regulation capacity in the system. Some statistical information of wind power, such as expectation and interval, is used to describe the uncertainty of wind power. The uncertainty model is transformed into a deterministic model by using the duality optimization theory, which provides convenience for engineering application. The Garver’s 6-bus transmission system model is used for example analysis, which shows that the proposed method can effectively solve the energy storage planning problem for uncertain wind power integrated power systems.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.