Abstract
In this paper we investigate a robust optimization framework for controlling energy storage devices in power networks with high share of fluctuating renewable energy sources. Our approach relies on the industry-standard DC power flow approximation, together with a multi-stage model that incorporates renewable uncertainty and an approximation of battery dynamics. More precisely, we consider storage device operation under linear control and taking into account power limits, energy conversion efficiencies, and energy limits for the state of charge. The aim of the robust optimization is to minimize costs for generating energy from conventional power generators while relying on storage to compensate for renewable output forecast errors. In order to obtain a solution we propose a cutting-plane procedure which can be used for investigating practical case studies.
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References
Beaudin, M., Zareipour, H., Schellenberglabe, A., Rosehart, W.: Energy storage for mitigating the variability of renewable electricity sources: An updated review. Energy for Sustainable Development 14(4), 302 – 314 (2010). DOI http://dx.doi.org/10.1016/j.esd.2010.09.007
Ben-Tal, A., El Ghaoui, L., Nemirovski, A.: Robust optimization. Princeton University Press (2009)
Benders, J.: Partitioning procedures for solving mixed-variables programming problems. Numerische Mathematik 4(1), 238–252 (1962)
Bertsimas, D., Brown, D.B., Caramanis, C.: Theory and applications of robust optimization. SIAM review 53(3), 464–501 (2011)
Bienstock, D.: Histogram models for robust portfolio optimization. J. Comput. Finance 11, 1 – 64 (2007)
Bienstock, D.: Electrical Transmission System Cascades and Vulnerability: An Operations Research Viewpoint, vol. 22. SIAM (2016)
Bienstock, D., Chertkov, M., Harnett, S.: Chance-constrained DC-OPF. SIAM Review 56, 461–495 (2014)
Bienstock, D., Mattia, S.: Using mixed-integer programming to solve power grid blackout problems. Discrete Optimization 4, 115 – 141 (2007)
Bienstock, D., Özbay, N.: Computing robust basestock levels. Discrete Optimization 5, 389 – 414 (2008)
Bienstock, D., Verma, A.: The N - k Problem in Power Grids: New Models, Formulations and Numerical Experiments. SIAM J. Optimization 20, 2352–2380 (2010)
Bludszuweit, H., DomĂnguez-Navarro, J.A.: A probabilistic method for energy storage sizing based on wind power forecast uncertainty. IEEE Transactions on Power Systems 26(3), 1651–1658 (2011)
Bludszuweit, H., DomĂnguez-Navarro, J.A., Llombart, A.: Statistical analysis of wind power forecast error. IEEE Transactions on Power Systems 23(3), 983–991 (2008)
Brown, P.D., Lopes, J.P., Matos, M.A.: Optimization of pumped storage capacity in an isolated power system with large renewable penetration. IEEE Transactions on Power systems 23(2), 523–531 (2008)
Dufo-LĂłpez, R., Bernal-AgustĂn, J.L., Contreras, J.: Optimization of control strategies for stand-alone renewable energy systems with hydrogen storage. Renewable energy 32(7), 1102–1126 (2007)
Glover, J., Sarma, M., Overbye, T.: Power System Analysis and Design. Cengage Learning (2011)
Hedayati, M., Zhang, J., Hedman, K.: Joint transmission expansion planning and energy storage placement in smart grid towards efficient integration of renewable energy (2014)
Houston, E., Kennelly, A.: The electric motor and the transmission power. Elementary electro-technical series. The W. J. Johnston Company (1896)
Jannati, M., Hosseinian, S., Vahidi, B., Li, G.J.: A survey on energy storage resources configurations in order to propose an optimum configuration for smoothing fluctuations of future large wind power plants. Renewable and Sustainable Energy Reviews 29, 158–172 (2014)
Jiang, R., Wang, J., Guan, Y.: Robust unit commitment with wind power and pumped storage hydro. IEEE Transactions on Power Systems 27(2), 800–810 (2012)
Lorca, A., Sun, X.: Multistage robust unit commitment with dynamic uncertainty sets and energy storage. IEEE Transactions on Power Systems PP(99), 1–1 (2016)
Luo, X., Wang, J., Dooner, M., Clarke, J.: Overview of current development in electrical energy storage technologies and the application potential in power system operation. Applied Energy 137, 511 – 536 (2015). DOI http://dx.doi.org/10.1016/j.apenergy.2014.09.081
Matke, C., Medjroubi, W., Kleinhans, D.: SciGRID - An Open Source Reference Model for the European Transmission Network (v0.2) (2016). URL http://www.scigrid.de
Oldham, K.: The Doctrine of Description: Gustav Kirchhoff, Classical Physics, and the ”purpose of All Science” in 19th-century Germany. University of California, Berkeley (2008)
Qiu, T., Xu, B., Wang, Y., Dvorkin, Y., Kirschen, D.: Stochastic multi-stage co-planning of transmission expansion and energy storage. IEEE Transactions on Power Systems PP(99), 1–1 (2016). DOI 10.1109/TPWRS.2016.2553678
Schavemaker, P., van der Sluis, L.: Electrical Power System Essentials. Wiley (2008)
Siemer, L., Schöpfer, F., Kleinhans, D.: Cost-optimal operation of energy storage units: Benefits of a problem-specific approach. Journal of Energy Storage 6, 11–21 (2016)
Wu, J., Zhang, B., Li, H., Li, Z., Chen, Y., Miao, X.: Statistical distribution for wind power forecast error and its application to determine optimal size of energy storage system. International Journal of Electrical Power & Energy Systems 55, 100–107 (2014)
Zimmerman, R.D., Murillo-Sanchez, C.E.: Matpower 6.01b User’s Manual. Power Systems Engineering Research Center (Pserc) (2016). URL http://www.pserc.cornell.edu//matpower/manual.pdf
Zimmerman, R.D., Murillo-Sanchez, C.E., Thomas, R.J.: MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education. IEEE Transactions on Power Systems 26(1), 12–19 (2011). DOI 10.1109/TPWRS.2010.2051168
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Matke, C., Bienstock, D., Muñoz, G., Yang, S., Kleinhans, D., Sager, S. (2017). Robust optimization of power network operation: storage devices and the role of forecast errors in renewable energies. In: Cherifi, H., Gaito, S., Quattrociocchi, W., Sala, A. (eds) Complex Networks & Their Applications V. COMPLEX NETWORKS 2016 2016. Studies in Computational Intelligence, vol 693. Springer, Cham. https://doi.org/10.1007/978-3-319-50901-3_64
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DOI: https://doi.org/10.1007/978-3-319-50901-3_64
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