Reactive power planning under high penetration of wind energy using Benders decomposition

Xu, Yan; Wei, Yanli; Fang, Xin; Li, Fangxing; Azim, Riyasat

doi:10.1049/iet-gtd.2014.1117

Title: Reactive power planning under high penetration of wind energy using Benders decomposition

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Abstract

This study addresses the optimal allocation of reactive power volt-ampere reactive (VAR) sources under the paradigm of high penetration of wind energy. Reactive power planning (RPP) in this particular condition involves a high level of uncertainty because of wind power characteristic. To properly model wind generation uncertainty, a multi-scenario framework optimal power flow that considers the voltage stability constraint under the worst wind scenario and transmission N 1 contingency is developed. The objective of RPP in this study is to minimise the total cost including the VAR investment cost and the expected generation cost. Therefore RPP under this condition is modelled as a two-stage stochastic programming problem to optimise the VAR location and size in one stage, then to minimise the fuel cost in the other stage, and eventually, to find the global optimal RPP results iteratively. Benders decomposition is used to solve this model with an upper level problem (master problem) for VAR allocation optimisation and a lower problem (sub-problem) for generation cost minimisation. Impact of the potential reactive power support from doubly-fed induction generator (DFIG) is also analysed. Lastly, case studies on the IEEE 14-bus and 118-bus systems are provided to verify the proposed method.

Authors:

Xu, Yan ^[1]; Wei, Yanli ^[2]; Fang, Xin ^[3]; Li, Fangxing ^[4]; Azim, Riyasat ^[3]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Southern California Edison, Rosemead, CA (United States)
Univ. of Tennessee, Knoxville, TN (United States)
Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Publication Date:: Thu Nov 05 00:00:00 EST 2015

Research Org.:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1279433

Alternate Identifier(s):: OSTI ID: 1786628

Grant/Contract Number:: AC05-00OR22725

Resource Type:: Accepted Manuscript

Journal Name:: IET Generation, Transmission, & Distribution

Additional Journal Information:: Journal Volume: 9; Journal Issue: 14; Journal ID: ISSN 1751-8687

Publisher:: Institution of Engineering and Technology

Country of Publication:: United States

Language:: English

Subject:: 17 WIND ENERGY; 24 POWER TRANSMISSION AND DISTRIBUTION; reactive power; wind power plants; power generation planning; load flow; power system stability; stochastic programming; investment; power generation economics; reactive power planning; wind energy penetration; Benders decomposition; VAR sources; reactive

Citation Formats


                    Xu, Yan, Wei, Yanli, Fang, Xin, Li, Fangxing, and Azim, Riyasat. Reactive power planning under high penetration of wind energy using Benders decomposition.  United States: N. p., 2015. 
Web.  doi:10.1049/iet-gtd.2014.1117.

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                    Xu, Yan, Wei, Yanli, Fang, Xin, Li, Fangxing, & Azim, Riyasat. Reactive power planning under high penetration of wind energy using Benders decomposition.  United States.  https://doi.org/10.1049/iet-gtd.2014.1117

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                    Xu, Yan, Wei, Yanli, Fang, Xin, Li, Fangxing, and Azim, Riyasat. Thu .  
"Reactive power planning under high penetration of wind energy using Benders decomposition".  United States.  https://doi.org/10.1049/iet-gtd.2014.1117.  https://www.osti.gov/servlets/purl/1279433.

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@article{osti_1279433,

  title        = {Reactive power planning under high penetration of wind energy using Benders decomposition},

  author       = {Xu, Yan and Wei, Yanli and Fang, Xin and Li, Fangxing and Azim, Riyasat},

  abstractNote = {This study addresses the optimal allocation of reactive power volt-ampere reactive (VAR) sources under the paradigm of high penetration of wind energy. Reactive power planning (RPP) in this particular condition involves a high level of uncertainty because of wind power characteristic. To properly model wind generation uncertainty, a multi-scenario framework optimal power flow that considers the voltage stability constraint under the worst wind scenario and transmission N 1 contingency is developed. The objective of RPP in this study is to minimise the total cost including the VAR investment cost and the expected generation cost. Therefore RPP under this condition is modelled as a two-stage stochastic programming problem to optimise the VAR location and size in one stage, then to minimise the fuel cost in the other stage, and eventually, to find the global optimal RPP results iteratively. Benders decomposition is used to solve this model with an upper level problem (master problem) for VAR allocation optimisation and a lower problem (sub-problem) for generation cost minimisation. Impact of the potential reactive power support from doubly-fed induction generator (DFIG) is also analysed. Lastly, case studies on the IEEE 14-bus and 118-bus systems are provided to verify the proposed method.},

  doi          = {10.1049/iet-gtd.2014.1117},

  journal      = {IET Generation, Transmission, & Distribution},

  number       = 14,

  volume       = 9,

  place        = {United States},

  year         = {Thu Nov 05 00:00:00 EST 2015},

  month        = {Thu Nov 05 00:00:00 EST 2015}

}

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