A Model Predictive Control Based Generator Start-Up Optimization Strategy for Restoration With Microgrids as Black-Start Resources

Zhao, Yuxuan; Lin, Zhenzhi; Ding, Yi; Liu, Yilu; Sun, Lei; Yan, Yong

doi:10.1109/TPWRS.2018.2849265

Title: A Model Predictive Control Based Generator Start-Up Optimization Strategy for Restoration With Microgrids as Black-Start Resources

Abstract

Microgrids (MGs) can operate in an islanded mode and serve as black-start resources for power system restoration (PSR). Here, a model predictive control (MPC) based generator start-up optimization strategy for PSR is proposed utilizing MGs as black-start resources. First, the generator start-up sequence (GSUS) optimization is formulated as a mixed integer linear programming. Then, the uncertainties of MG black-start resources (MBSRs) are modeled by discretizing the probability distribution of the forecast errors, and representative scenarios for MBSRs extracted by formulating the probability mass transportation problem. Third, the generator start-up optimization strategy considering MBSRs is proposed utilizing the MPC technique, in which the optimization objective is to maximize the energy capability of the power systems and minimize the load curtailment of the MGs in each looking-ahead interval. Simulations on the IEEE 118 bus system with MGs and Zhejiang provincial power system in China verify that the introduced strategy for PSR can successfully restore the power system and effectively determine the optimal GSUS.

Authors:

^[1];

^[1]; Liu, Yilu ^[2];

^[3]; Yan, Yong ^[4]

Zhejiang Univ., Hangzhou (China)
Univ. of Tennessee, Knoxville, TN (United States)
Hefei Univ. of Technology (China)
Electric Power Research Inst., Hangzhou (China)

Publication Date:: Wed Jun 20 00:00:00 EDT 2018

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

Sponsoring Org.:: USDOE; National Key Research and Development Program of China; National Natural Science Foundation of China (NSFC); Zhejiang Provincial Natural Science Foundation of China

OSTI Identifier:: 1523722

Grant/Contract Number:: AC05-00OR22725; 2016YFB0900100; 51777185; LY17E070003

Resource Type:: Accepted Manuscript

Journal Name:: IEEE Transactions on Power Systems

Additional Journal Information:: Journal Volume: 33; Journal Issue: 6; Journal ID: ISSN 0885-8950

Publisher:: IEEE

Country of Publication:: United States

Language:: English

Subject:: 24 POWER TRANSMISSION AND DISTRIBUTION

Citation Formats


                    Zhao, Yuxuan, Lin, Zhenzhi, Ding, Yi, Liu, Yilu, Sun, Lei, and Yan, Yong. A Model Predictive Control Based Generator Start-Up Optimization Strategy for Restoration With Microgrids as Black-Start Resources.  United States: N. p., 2018. 
Web.  doi:10.1109/TPWRS.2018.2849265.

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                    Zhao, Yuxuan, Lin, Zhenzhi, Ding, Yi, Liu, Yilu, Sun, Lei, & Yan, Yong. A Model Predictive Control Based Generator Start-Up Optimization Strategy for Restoration With Microgrids as Black-Start Resources.  United States.  https://doi.org/10.1109/TPWRS.2018.2849265

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                    Zhao, Yuxuan, Lin, Zhenzhi, Ding, Yi, Liu, Yilu, Sun, Lei, and Yan, Yong. Wed .  
"A Model Predictive Control Based Generator Start-Up Optimization Strategy for Restoration With Microgrids as Black-Start Resources".  United States.  https://doi.org/10.1109/TPWRS.2018.2849265.  https://www.osti.gov/servlets/purl/1523722.

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@article{osti_1523722,

  title        = {A Model Predictive Control Based Generator Start-Up Optimization Strategy for Restoration With Microgrids as Black-Start Resources},

  author       = {Zhao, Yuxuan and Lin, Zhenzhi and Ding, Yi and Liu, Yilu and Sun, Lei and Yan, Yong},

  abstractNote = {Microgrids (MGs) can operate in an islanded mode and serve as black-start resources for power system restoration (PSR). Here, a model predictive control (MPC) based generator start-up optimization strategy for PSR is proposed utilizing MGs as black-start resources. First, the generator start-up sequence (GSUS) optimization is formulated as a mixed integer linear programming. Then, the uncertainties of MG black-start resources (MBSRs) are modeled by discretizing the probability distribution of the forecast errors, and representative scenarios for MBSRs extracted by formulating the probability mass transportation problem. Third, the generator start-up optimization strategy considering MBSRs is proposed utilizing the MPC technique, in which the optimization objective is to maximize the energy capability of the power systems and minimize the load curtailment of the MGs in each looking-ahead interval. Simulations on the IEEE 118 bus system with MGs and Zhejiang provincial power system in China verify that the introduced strategy for PSR can successfully restore the power system and effectively determine the optimal GSUS.},

  doi          = {10.1109/TPWRS.2018.2849265},

  journal      = {IEEE Transactions on Power Systems},

  number       = 6,

  volume       = 33,

  place        = {United States},

  year         = {Wed Jun 20 00:00:00 EDT 2018},

  month        = {Wed Jun 20 00:00:00 EDT 2018}

}

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Journal Article:

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https://doi.org/10.1109/TPWRS.2018.2849265

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Cited by: 35 works

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Fig. 1: Generation capability function of units

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Works referencing / citing this record:

Coordinated Dispatch of Integrated Energy Systems Considering the Differences of Multiple Functional Areas
journal, May 2019

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Applied Sciences, Vol. 9, Issue 10
DOI: 10.3390/app9102103

A New Indicator of Transient Stability for Controlled Islanding of Power Systems: Critical Islanding Time
journal, November 2018

Lin, Zhenzhi; Zhao, Yuxuan; Liu, Shengyuan
Energies, Vol. 11, Issue 11
DOI: 10.3390/en11112975

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Title: A Model Predictive Control Based Generator Start-Up Optimization Strategy for Restoration With Microgrids as Black-Start Resources

Abstract

Citation Formats

Figures / Tables:

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