Technical Papers
Apr 10, 2018

Wind-Thermal Generating Unit Commitment Considering Short-Term Fluctuation of Wind Power

Publication: Journal of Energy Engineering
Volume 144, Issue 3

Abstract

The integration of large-scale wind power in a power grid brings tremendous challenges to the power system operation because of the variability of wind power. Adequate spinning reserve is always required for effective accommodation of wind power variability by the automatic generation control system. The generation schedule and required spinning reserve are usually determined by hourly unit commitment, but the system frequency regulating process under wind power intrahour fluctuation is ignored. This increases the system operation risk. A novel wind-thermal generating unit commitment method considering short-term (<1  h) fluctuation of wind power (SFWP) is presented. A simulation model based on the k-means clustering technique is developed to describe the SFWP information, and the system frequency regulation is incorporated as the spinning reserve constraint of the unit commitment model. The proposed method enables more accurate assessment of the required spinning reserve capacity than the existing methods. It also improves the security of power system operation. Case studies are presented to demonstrate the effectiveness of the proposed method.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China (No. 51377178) and in part by the Chongqing University Postgraduates’ Innovation Project (No. CYB15035).

References

Ahmadi, H., and H. Ghasemi. 2014. “Security-constrained unit commitment with linearized system frequency limit constraints.” IEEE Trans. Power Syst. 29 (4): 1536–1545.
An, Y., and B. Zeng. 2015. “Exploring the modeling capacity of two-stage robust optimization: Variants of robust unit commitment model.” IEEE Trans. Power Syst. 30 (1): 109–122.
Ban, M., J. Yu, M. Shahidehpour, and Y. Yao. 2017. “Integration of power-to-hydrogen in day-ahead security-constrained unit commitment with high wind penetration.” J. Mod. Power Syst. Clean Energy, 5 (3): 337–349.
Cardozo, C., L. Capely, and P. Dessante. 2017. “Frequency constrained unit commitment.” Energy Syst. 8 (1): 31–56.
Carrión, M., and J. M. Arroyo. 2006. “A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem.” IEEE Trans. Power Syst. 21 (3): 1371–1378.
Chen, C. L. 2008. “Optimal wind-thermal generating unit commitment.” IEEE Trans. Energy Convers. 23 (1): 273–280.
Chen, C. L., and N. Chen. 2001. “Direct search method for solving economic dispatch problem considering transmission capacity constraints.” IEEE Trans. Power Syst. 16 (4): 764–769.
Chen, C. L., and S. C. Wang. 1993. “Branch-and-bound scheduling for thermal generating units.” IEEE Trans. Energy Convers. 8 (2): 184–189.
China Meteorological Data Service Center (CMDC). 2016. “Meteorological data.” Accessed March 17, 2016. http://data.cma.cn/en/?r=article/getLeft/id343/keyIndex/30.
Damousis, I. G., M. C. Alexiadis, J. B. Theocharis, and P. S. Dokopoulos. 2004. “A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation.” IEEE Trans. Energy Convers. 19 (2): 352–361.
De Vos, K., and J. Driesen. 2014. “Dynamic operating reserve strategies for wind power integration.” IET Renewable Power Gener. 8 (6): 598–610.
De Vos, K., J. Morbee, J. Driesen, and R. Belmans. 2013. “Impact of wind power on sizing and allocation of reserve requirements.” IET Renewable Power Gener. 7 (1): 1–9.
Di Piazza, A., M. Di Piazza, A. Ragusa, and G. Vitale. 2011. “Environmental data processing by clustering methods for energy forecast and planning.” Renewable Energy 36 (3): 1063–1074.
Dvorkin, Y., P. Henneaux, D. S. Kirschen, and H. Pandžić. 2016. “Optimizing primary response in preventive security-constrained optimal power flow.” IEEE Syst. J., PP (99): 1–10.
Ela, E., V. Gevorgian, A. Tuohy, B. Kirby, M. Milligan, and M. O’Malley. 2014. “Market designs for the primary frequency response ancillary service. I: Motivation and design.” IEEE Trans. Power Syst. 29 (1): 421–431.
Frangioni, A., C. Gentile, and F. Lacalandra. 2009. “Tighter approximated MILP formulations for unit commitment problems.” IEEE Trans. Power Syst. 24 (1): 105–113.
Fu, Y., W. Hu, F. Xu, C. Zhang, and X. Wang. 2017. “Clean heating scheduling optimization with wind power in Northern China.” J. Energy Eng. 143 (6): 014017056.
Gurobi Optimization, Inc. 2017. Gurobi optimizer reference manual v7.5. Houston, TX: Gurobi Optimization, Inc.
Hong, Y. Y., and C. T. Li. 2006. “Short-term real-power scheduling considering fuzzy factors in an autonomous system using genetic algorithms.” IEE Proc. Gener. Transm. Distrib. 153 (6): 684–692.
IBM Corporation. 2018. IBM ILOG CPLEX optimization studio cplex user’s manual v12.8. New York: IBM Corporation.
Johnston, L., F. Díaz-González, O. Gomis-Bellmunt, C. Corchero-García, and M. Cruz-Zambrano. 2015. “Methodology for the economic optimisation of energy storage systems for frequency support in wind power plants.” Appl. Energy 137: 660–669.
Ketchen, D. J., and C. L. Shook. 1996. “The application of cluster analysis in strategic management research: An analysis and critique.” Strategies Manage. J. 17 (6): 441–458.
Li, C., R. B. Johnson, and A. J. Svoboda. 1997. “A new unit commitment method.” IEEE Trans. Power Syst. 12(1): 113–119.
Li, Z., L. Ye, Y. Zhao, X. Song, J. Teng, and J. Jin. 2016. “Short-term wind power prediction based on extreme learning machine with error correction.” Prot. Control Mod. Power Syst. 1 (1): 1–8.
Liang, Z., J. Liang, C. Wang, X. Dong, and X. Miao. 2016. “Short-term wind power combined forecasting based on error forecast correction.” Energy Convers. Manage. 119: 215–226.
Liu, H., H. Tian, X. Liang, and Y. Li. 2015a. “New wind speed forecasting approaches using fast ensemble empirical model decomposition, genetic algorithm, mind evolutionary algorithm and artificial neural networks.” Renewable Energy 83: 1066–1075.
Liu, H., H. Tian, X. Liang, and Y. Li. 2015b. “Wind speed forecasting approach using secondary decomposition algorithm and Elman neural networks.” Appl. Energy 157: 183–194.
Machowski, J., J. Bialek, and J. Bumby. 2011. Power system dynamics: Stability and control. New York: Wiley.
Ongsakul, W., and N. Petcharaks. 2004. “Unit commitment by enhanced adaptive Lagrangian relaxation.” IEEE Trans. Power Syst. 19 (1): 620–628.
Ostrowski, J., M. F. Anjos, and A. Vannelli. 2012. “Tight mixed integer linear programming formulations for the unit commitment problem.” IEEE Trans. Power Syst. 27 (1): 39–46.
Padhy, N. P. 2004. “Unit commitment-a bibliographical survey.” IEEE Trans. Power Syst. 19 (2): 1196–1205.
Pappala, V. S., I. Erlich, K. Rohrig, and J. Dobschinski. 2009. “A stochastic model for the optimal operation of a wind-thermal power system.” IEEE Trans. Power Syst. 24 (2): 940–950.
Senjyu, T., K. Shimabukuro, K. Uezato, and T. Funabashi. 2003. “A fast technique for unit commitment problem by extended priority list.” IEEE Trans. Power Syst. 18 (2): 882–888.
Sikorski, K. 1982. “Bisection is optimal.” Numer. Math. 40 (1): 111–117.
Standardization Administration of the P.R. China. (2008). Power quality—Frequency deviation for power system. GB/T 15945–2008. Beijing: Standardization Administration of the P.R. China.
Teng, F., V. Trovato, and G. Strbac. 2016. “Stochastic scheduling with inertia-dependent fast frequency response requirements.” IEEE Trans. Power Syst. 31 (2): 1557–1566.
Wang, H., G. Li, G. Wang, J. Peng, H. Jiang, and Y. Liu. 2017. “Deep learning based ensemble approach for probabilistic wind power forecasting.” Appl. Energy 188: 56–70.
Wang, Y.-H., C.-H. Yeh, H.-W. V. Young, K. Hu, and M.-T. Lo. 2014. “On the computational complexity of the empirical mode decomposition algorithm.” Phys. Stat. Mech. Appl. 400: 159–167.
Wen, Y., C. Guo, H. Pandžić, and D. S. Kirschen. 2016. “Enhanced security constrained unit commitment with emerging utility-scale energy storage.” IEEE Trans. Power Syst. 31 (1): 652–662.
Xie, K., J. Dong, C. Singh, and B. Hu. 2016. “Optimal capacity and type planning of generating units in a bundled wind-thermal generation system.” Appl. Energy 164: 200–210.
Xu, Q., D. He, N. Zhang, C. Kang, Q. Xia, J. Bai, and J. Huang. 2015. “A short-term wind power forecasting approach with adjustment of numerical weather prediction input by data mining.” IEEE Trans. Sustainable Energy 6 (4): 1283–1291.
Zhang, N., Z. Hu, X. Han, J. Zhang, and Y. Zhou. 2015. “A fuzzy chance-constrained program for unit commitment problem considering demand response, electric vehicle and wind power.” Int. J. Electr. Power 65: 201–209.
Zhang, Z.-S., Y.-Z. Sun, J. Lin, and G.-J. Li. 2012. “Coordinated frequency regulation by doubly fed induction generator-based wind power plants.” IET Renewable Power Gener. 6 (1): 38–47.
Zhong, Q. C., Z. Ma, W. L. Ming, and G. C. Konstantopoulos. 2015. “Grid-friendly wind power systems based on the synchronverter technology.” Energy Convers. Manage. 89: 719–726.
Zhou, Y., W. Hu, Y. Min, X. Xu, and Y. Li. 2017. “Modeling and optimization of multitype power sources stochastic unit commitment using interval number programming.” J. Energy Eng. 143 (5): 04017036.

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Go to Journal of Energy Engineering
Journal of Energy Engineering
Volume 144Issue 3June 2018

History

Received: Apr 3, 2017
Accepted: Nov 17, 2017
Published online: Apr 10, 2018
Published in print: Jun 1, 2018
Discussion open until: Sep 10, 2018

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Ph.D. Candidate, State Key Laboratory of Power Transmission Equipment and System Security, Chongqing Univ., No. 174 Shazhengjie, Shapingba, Chongqing 400044, China. Email: [email protected]
Professor, State Key Laboratory of Power Transmission Equipment and System Security, Chongqing Univ., No. 174 Shazhengjie, Shapingba, Chongqing 400044, China (corresponding author). Email: [email protected]
Heng–Ming Tai [email protected]
Professor, Dept. of Electrical and Computer Engineering, Univ. of Tulsa, 800 South Tucker Dr., Tulsa, OK 74104. Email: [email protected]
Jizhe Dong, Ph.D. [email protected]
Researcher, Construction Corporation of State Grid Jilin Electric Power Company Ltd., No. 2017, Baihui Street, Chaoyang District, Changchun 130000, China. Email: [email protected]

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