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

Journal Article · Thu Nov 05 00:00:00 EST 2015 · IET Generation, Transmission, & Distribution

DOI:https://doi.org/10.1049/iet-gtd.2014.1117· OSTI ID:1279433

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

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

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.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 1279433
• Alternate ID(s): OSTI ID: 1786628
• Journal Information: IET Generation, Transmission, & Distribution, Journal Name: IET Generation, Transmission, & Distribution Journal Issue: 14 Vol. 9; ISSN 1751-8687
• Publisher: Institution of Engineering and Technology
• Country of Publication: United States
• Language: English

Related Subjects

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