Title
Optimized Reactive Power Capability of Wind Power Plants with Tap-Changing Transformers
Date Issued
01 October 2021
Access level
metadata only access
Resource Type
journal article
Author(s)
University of Campinas
University of Campinas
University of Campinas
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
With the recent advancements in power electronics for wind turbines (WTs) and increasing penetration of wind energy, wind power plants (WPP) have become necessary contributors of reactive power support for the bulk power system. Balancing reactive power support with individual WT operating requirements in a cost-effective manner is a challenge for WPP designers. In this paper, we present a methodology to optimize the WPP reactive power capability as seen from the point of common coupling (PCC), accounting for steady-state operating capabilities of the WPP equipment. Thus, the proposed methodology determines the configuration of the tap-changing transformers within the WPP that maximizes the amount of reactive power the WPP can either consume or inject to the network, considering uncertain levels of wind power generation and voltage magnitudes at the PCC. The optimized reactive power capability (ORPC) problem is initially formulated as a mixed-integer nonlinear programming (MINLP) model. Then, a set of efficient linearization techniques are used to obtain a mixed-integer linear programming (MILP) model that can be solved via off-the-shelf mathematical programming solvers. Results demonstrate that the proposed MILP model is a scalable, flexible and accurate method to maximize the reactive power capability of WPP.
Start page
1935
End page
1946
Volume
12
Issue
4
Language
English
OCDE Knowledge area
Ingeniería, Tecnología
Subjects
Scopus EID
2-s2.0-85104605001
Source
IEEE Transactions on Sustainable Energy
ISSN of the container
19493029
Sponsor(s)
Manuscript received August 21, 2020; revised March 10, 2021; accepted April 8, 2021. Date of publication April 15, 2021; date of current version September 20, 2021. This work was supported by FAPESP under Grants 2019/01906-0, 2015/21972-6, 2017/25425-5, 2019/08200-5, 2016/08645-9, 2018/20104-9, 2019/10033-0, 2017/21752-1, and Coordenação de Aperfeiçoamento de Pessoal de Nivel Superior - Brasil (CAPES) - Finance Code 001 88882.329397/2019-01. Paper no. TSTE-00912-2020. (Corresponding author: Hever Alcahuaman.) Hever Alcahuaman, Juan Camilo López, Daniel Dotta, and Marcos J. Rider are with the University of Campinas, Campinas, SP 13083-852, Brazil (e-mail: h228105@dac.unicamp.br; amezquita53@hotmail.com; dotta@fee.unicamp.br; mjrider@dsee.fee.unicamp.br).
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