Modelling wind power spatial-temporal correlation in multi-interval optimal power flow: A sparse correlation matrix approach

Fang, Xin; Hodge, Bri-Mathias; Du, Ershun; Zhang, Ning; Li, Fangxing

doi:10.1016/j.apenergy.2018.08.123

Title: Modelling wind power spatial-temporal correlation in multi-interval optimal power flow: A sparse correlation matrix approach

Journal Article · Fri Aug 31 00:00:00 EDT 2018 · Applied Energy

DOI:https://doi.org/10.1016/j.apenergy.2018.08.123· OSTI ID:1471480

^[1]; Hodge, Bri-Mathias ^[1]; Du, Ershun ^[2];

^[2];

^[3]

National Renewable Energy Lab. (NREL), Golden, CO (United States)
Tsinghua Univ., Beijing (China)
Univ. of Tennessee, Knoxville, TN (United States)

The significantly increasing deployment of wind power necessitates that system operation considers the spatial-temporal correlation of power forecast from different wind power plants. How to model this spatial-temporal correlation in the actual system dispatch is challenging. In this paper, a sparse correlation matrix is utilized to efficiently model the spatial-temporal correlation of wind power forecast in the generation dispatch model. A novel, adjustable, and distributionally-robust chance-constrained multi-interval optimal power flow (ADRCC-MIOPF) model is proposed to obtain reliable economic dispatch (ED) solutions. The spatial-temporal correlation of wind power plants power forecasts is represented by the sparse correlation covariance matrix obtained from historical, time series wind power forecast error data. The chance constraints in the ADRCC-MIOPF model are transformed into a set of second-order-cone (SOC) constraints in which an adjustable coefficient in the chance constraints controls the robustness of the ADRCC-MIOPF model to the wind power forecast errors distribution. Case studies performed on the PJM 5-bus system and IEEE 118-bus system verify the proposed method to improve the system security and reduce the cost especially under the high wind penetration levels. All the cases can be solved within several minutes for both the small and large cases which validates the efficiency of the proposed sparse matrix model. In addition, considering the spatial-temporal correlation of wind power forecast and the distributional robustness of wind power forecast error leads to a more reliable economic dispatch with lower system violations.

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Research Organization:: National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)

Grant/Contract Number:: AC36-08GO28308

OSTI ID:: 1471480

Alternate ID(s):: OSTI ID: 1734370

Report Number(s):: NREL/JA-5D00-72132

Journal Information:: Applied Energy, Vol. 230, Issue C; ISSN 0306-2619

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 26 works

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References (19)

Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform Tascikaraoglu, Akin; Sanandaji, Borhan M.; Poolla, Kameshwar Applied Energy, Vol. 165 https://doi.org/10.1016/j.apenergy.2015.12.082	journal	March 2016
Efficient Uncertainty Quantification in Stochastic Economic Dispatch Safta, Cosmin; Chen, Richard L. -Y.; Najm, Habib N. IEEE Transactions on Power Systems, Vol. 32, Issue 4 https://doi.org/10.1109/TPWRS.2016.2615334	journal	July 2017
Modeling Dynamic Spatial Correlations of Geographically Distributed Wind Farms and Constructing Ellipsoidal Uncertainty Sets for Optimization-Based Generation Scheduling Li, Pai; Guan, Xiaohong; Wu, Jiang IEEE Transactions on Sustainable Energy, Vol. 6, Issue 4 https://doi.org/10.1109/TSTE.2015.2457917	journal	October 2015
A new optimal power flow approach for wind energy integrated power systems Rahmani, Shima; Amjady, Nima Energy, Vol. 134 https://doi.org/10.1016/j.energy.2017.06.046	journal	September 2017
A chance constrained optimal reserve scheduling approach for economic dispatch considering wind penetration Tang, Yufei; Luo, Chao; Yang, Jun IEEE/CAA Journal of Automatica Sinica, Vol. 4, Issue 2 https://doi.org/10.1109/JAS.2017.7510499	journal	April 2017
Modeling Conditional Forecast Error for Wind Power in Generation Scheduling Zhang, Ning; Kang, Chongqing; Xia, Qing IEEE Transactions on Power Systems, Vol. 29, Issue 3 https://doi.org/10.1109/TPWRS.2013.2287766	journal	May 2014
A conditional model of wind power forecast errors and its application in scenario generation Wang, Zhiwen; Shen, Chen; Liu, Feng Applied Energy, Vol. 212 https://doi.org/10.1016/j.apenergy.2017.12.039	journal	February 2018
An investigation of wind power density distribution at location with low and high wind speeds using statistical model Katinas, Vladislovas; Gecevicius, Giedrius; Marciukaitis, Mantas Applied Energy, Vol. 218 https://doi.org/10.1016/j.apenergy.2018.02.163	journal	May 2018
A statistical cognitive model to assess impact of spatially correlated wind production on market behaviors Rahimiyan, Morteza Applied Energy, Vol. 122 https://doi.org/10.1016/j.apenergy.2014.02.004	journal	June 2014
Short-Term Spatio-Temporal Wind Power Forecast in Robust Look-ahead Power System Dispatch Xie, Le; Gu, Yingzhong; Zhu, Xinxin IEEE Transactions on Smart Grid, Vol. 5, Issue 1 https://doi.org/10.1109/TSG.2013.2282300	journal	January 2014
Distributionally robust hydro-thermal-wind economic dispatch Chen, Yue; Wei, Wei; Liu, Feng Applied Energy, Vol. 173 https://doi.org/10.1016/j.apenergy.2016.04.060	journal	July 2016
Characterizing and Modeling Wind Power Forecast Errors from Operational Systems for Use in Wind Integration Planning Studies Hodge, Bri-Mathias S.; Ela, Erik G.; Milligan, Michael Wind Engineering, Vol. 36, Issue 5 https://doi.org/10.1260/0309-524X.36.5.509	journal	October 2012
Day-ahead coordinated operation of utility-scale electricity and natural gas networks considering demand response based virtual power plants Cui, Hantao; Li, Fangxing; Hu, Qinran Applied Energy, Vol. 176 https://doi.org/10.1016/j.apenergy.2016.05.007	journal	August 2016
A modified bacteria foraging based optimal power flow framework for Hydro-Thermal-Wind generation system in the presence of STATCOM Panda, Ambarish; Tripathy, M.; Barisal, A. K. Energy, Vol. 124 https://doi.org/10.1016/j.energy.2017.02.090	journal	April 2017
On Distributionally Robust Chance-Constrained Linear Programs Calafiore, G. C.; Ghaoui, L. El Journal of Optimization Theory and Applications, Vol. 130, Issue 1 https://doi.org/10.1007/s10957-006-9084-x	journal	December 2006
Strategic CBDR bidding considering FTR and wind power Hu, Qinran; Li, Fangxing; Wei, Yanli IET Generation, Transmission & Distribution, Vol. 10, Issue 10 https://doi.org/10.1049/iet-gtd.2015.1305	journal	July 2016
Strategic scheduling of energy storage for load serving entities in locational marginal pricing market Wei, Yanli; Cui, Hantao; Fang, Xin IET Generation, Transmission & Distribution, Vol. 10, Issue 5 https://doi.org/10.1049/iet-gtd.2015.0144	journal	April 2016
Coupon-Based Demand Response Considering Wind Power Uncertainty: A Strategic Bidding Model for Load Serving Entities Fang, Xin; Hu, Qinran; Li, Fangxing IEEE Transactions on Power Systems, Vol. 31, Issue 2 https://doi.org/10.1109/TPWRS.2015.2431271	journal	March 2016
Scenario reduction and scenario tree construction for power management problems Growe-Kuska, N.; Heitsch, H.; Romisch, W. 2003 IEEE Bologna Power Tech Conference Proceedings, https://doi.org/10.1109/PTC.2003.1304379	conference	January 2003

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Adjustable and distributionally robust chance-constrained economic dispatch considering wind power uncertainty Fang, Xin; Hodge, Bri-Mathias; Li, Fangxing Journal of Modern Power Systems and Clean Energy, Vol. 7, Issue 3 https://doi.org/10.1007/s40565-019-0526-5	journal	April 2019

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