Coordination of Wind Power Plants and Energy Storage Devices in Security-Constrained Unit Commitment Problem Using Robust Optimization

Document Type : Power Article

Authors

Abstract

Security-Constrained Unit commitment, one of the most critical tasks in electric power system operations, faces new challenges as the supply and demand uncertainty increases dramatically due to the integration of variable generation resources such as wind power generation. To cope with these concerns, we propose a two-stage adaptive robust unit commitment model for the security constrained unit commitment problem in the presence of load and wind uncertainty.   In addition to being robust model to deal with the uncertainty of wind power production, energy storage devices has been considered for further handling of this issue. Compared to the conventional stochastic programming approach, the robust optimization model is more practical because only requires a deterministic uncertainty set , while in stochastic programming to obtain a probability distribution function of parameter uncertainty is very difficult. To resolve the SCUC problem using robust optimization that is very complex and difficult, Benders decomposition algorithm is used to make smaller problems, which makes reduced complexity of the problem, which results in to solve it easier. 

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[1] Rebours. Y., Kirschen, D. A. (2005). “Survey of definitions and specifications of reserve services”. Tech. Report, University of Manchester.
[2] Matos, M. A., Bessa, R. J. (2011). “Setting the operating reserve using probabilistic wind power forecasts”. IEEE Transactions on Power Systems, vol. 26, no. 2, pp. 594-603.
[3] Morales, J. M., Conejo, A. J., Perez-Ruiz, J. (2009). “Economic valuation of reserves in power systems with high penetration of wind power”. IEEE Transactions on Power Systems, vol. 24, no. 2, pp. 900-910.
[4] Ruiz, P. A., Philbrick, C. R., Zak, E., Cheung, K. W., Sauer, P. W. (2009). “Uncertainty management in the unit commitment problem”. IEEE Transactions on Power Systems, vol. 24, no. 2, pp. 642-651.
[5] Wang, J., Botterud, A., Bessa, R., Keko, H., Carvalho, L., Issicaba, D., Sumaili, J., Miranda, V. (2011). “Wind power forecasting uncertainty and unit commitment”. Applied Energy, vol. 88, no. 11, pp. 4014-4023.
[6] Birge, J. R., Louveaux, F. (2011). Introduction to Stochastic Programming. Springer.
[7] Bertsimas, D., Sim, M. (2004). The price of robustness. Operations Research, vol. 52, no. 1, pp. 35-53.
[8] Ghofrani, M., Arabali, A. (2014). “A Stochastic Framework for Power System Operation with wind Generation and Energy Storage Integration”. Innovative Smart Grid Technologies Conference (ISGT), IEEE PES.
[9] Jiang, R.,Wang, J., and Guan, Y. (2012). Robust Unit Commitment with Wind Power and Pumped Storage Hydro,” IEEE Transactions on Power Systems, vol. 27, no. 2, pp. 800-810.
[10] Pozo, D., Contreras, J., Sauma, E. E. (2014). “Unit Commitment With Ideal and Generic Energy Storage Units,” IEEE Transactions on Power Systems, vol. 29, no. 6, pp. 2974-2984.  
[11] Guan, X., Luh, P., Yan, H., Amalfi, J. (1992). “An optimization based method for unit commitment,” Int. J. Elect. Power Energy Syst., vol. 14, no. 6, pp. 9–17.
[12] Bertsimas, D., Litvinov, E., Sun, X. A., Zhao, J., Zheng, T. (2013). “Adaptive robust optimization for the security constrained unit commitment problem,”IEEE Trans. Power Syst., vol. 28, no. 1, pp. 52–63.
[13] Conejo, A. J., Castillo, E., Mínguez, R., García-Bertrand, R. (2006). Decomposition Techniques in Mathematical Programming. Engineering And Science Applications.  
[14] Hedman, K. W., Ferris, M. C., O'Neill, R. P., Fisher, E. B., et al. (2010). “Optimization Of Generation Unit Commitment and Transmission Switching With N-1 Reliability,” IEEE Transactions on Power System, vol. 25, no. 2, pp. 1052-1063.
[15] Hedman, K. W., O'Neill, R. P., Fisher, E. B., Oren, S. S. (2009). “Optimal Transmission Switching With Contingency Analysis,” IEEE Transactions on Power System, vol. 24, no. 3, pp. 1577-1586.