Stochastic Sizing of Energy Storage Systems for Wind Integration
Abstract
In this paper, we present an optimal capacity decision model for energy storage systems (ESSs) in combined operation with wind energy in power systems. We use a two-stage stochastic programming approach to take into account both wind and load uncertainties. The planning problem is formulated as an AC optimal power flow (OPF) model with the objective of minimizing ESS installation cost and system operation cost. Stochastic wind and load inputs for the model are generated from historical data using clustering technique. The model is tested on the IEEE 39-bus system.
Keywords:
energy storage system, ESS, OPF, sizing, stochastic, windDownloads
References
P. Taylor, Energy Technology Perspectives 2010 -Scenarios and Strategies to 2050, International Energy Agency, Paris, France, 2010
H. T. Le, T. Q. Nguyen, “Sizing energy storage systems for wind power firming: An analytical approach and a cost-benefit analysis”, IEEE Power and Energy Society General Meeting – Conversionand Delivery of Electrical Energy in the 21st Century Pittsburgh, USA, July 20-24, 2008
Z. Y. Gao, P. Wang, L. Bertling, J. H. Wang, “Sizing of energy storage for power systems with wind farms based on reliability cost and wroth analysis”, IEEE Power and Energy Society General Meeting, San Diego, USA, July 24-29, 2011 DOI: https://doi.org/10.1109/PES.2011.6039468
Y. V. Makarov, P. Du, M. C. W. Kintner-Meyer, C. Jin, H. F. Illian, “Sizing Energy Storage to Accommodate High Penetrationof Variable Energy Resources”, IEEE Transaction on Sustainable Energy, Vol. 3, No. 1, pp. 34-40, 2012 DOI: https://doi.org/10.1109/TSTE.2011.2164101
L. Li; L. Yang, “A chance-constrained programming based energystorage system sizing model considering uncertainty of wind power”, International Conference on Sustainable Power Generation and Supply (SUPERGEN 2012), Hangzhou, China, September 8-9, 2012
P. Pinson, G. Papaefthymiou, B. Klockl, J. Verboomen, “Dynamic Sizing of Energy Storage for Hedging Wind Power Forecast Uncertainty”, IEEE Power & Energy Society General Meeting, PES 2009, Calgary, AB, Canada, July 26-30, 2009 DOI: https://doi.org/10.1109/PES.2009.5275816
T. Hou, Y. Cui, Y. Li, W. Zhang, X. Zhou, “Sizing battery energy storage for wind farms based on wind power forecast uncertainty in the bulk power system”, IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), Xi'an, China, pp. 1548-1552, 2016
M. Bucciarelli, S. Paoletti, A. Vicino, “A scenario reduction approach for optimal sizing of energy storage systems in power distribution networks”, IEEE 56th Annual Conference on Decision and Control (CDC), Melbourne, Australia, pp. 4497-4502, December 12-15, 2017 DOI: https://doi.org/10.1109/CDC.2017.8264322
H. Bludszuweit, J. A. Dominguez-Navarro, “A Probabilistic Method for Energy Storage Sizing Based on Wind Power Forecast Uncertainty”, IEEE Transaction on Power Systems, Vol. 26, No. 3, pp. 1651-1658, 2011 DOI: https://doi.org/10.1109/TPWRS.2010.2089541
K. Baker, G. Hug, X. Li, “Optimal storage sizing using two-stage stochastic optimization for intra-hourly dispatch”, North American Power Symposium (NAPS), Pullman, USA, September 7-9, 2014 DOI: https://doi.org/10.1109/NAPS.2014.6965384
A. P. Sanghvi, I. H. Shavel, “Investment planning for hydrothermal power system expansion: Stochastic programming employing the Dantzig-Wolfe decomposition principle”, IEEE Transaction on Power Systems, Vol. 1, No. 2, pp. 115-121, 1986 DOI: https://doi.org/10.1109/TPWRS.1986.4334916
B. G. Gorenstin, N. M. Campodonico, J. P. Costa, M. V. F. Pereira, “Power system expansion planning under uncertainty”, IEEE Transaction on Power Systems, Vol. 8, Vo. 1, pp. 129-136, 1993 DOI: https://doi.org/10.1109/59.221258
A. Marn, J. Salmern, “Electric capacity expansion under uncertain demand: Decomposition approaches”, IEEE Transaction on Power Systems, Vol. 13, No. 2, pp. 333-339, 1998 DOI: https://doi.org/10.1109/59.667347
M. Carrin, J. M. Arroyo, N. Alguacil, “Vulnerability-constrainedtransmission expansion planning: A stochastic programming approach”, IEEE Transaction on Power Systems, Vol. 22, No. 4, pp. 1436-1445, 2007 DOI: https://doi.org/10.1109/TPWRS.2007.907139
H. Yu, C. Y. Chung, K. P. Wong, J. H. Zhang, “A chance constrained transmission network expansion planning method with consideration of load and wind farm uncertainties”, IEEE Transaction on Power Systems, Vol. 24, No. 3, pp. 1568-1576, 2009 DOI: https://doi.org/10.1109/TPWRS.2009.2021202
T. Akbari, S. Zolfaghari, A. Kazemi, “Multi-stage stochastic transmission expansion planning under load uncertainty using Benders decomposition”, International Review of Electrical Engineering, Vol. 4, No. 5, pp. 976-984, 2009
A. Shapiro, D. Dentcheva, A. Ruszczynski, Lectures on Stochastic Programming: Modeling and Theory, Society for Industrial and Applied Mathematics and Mathematical Programming Society, Philadelphia, USA, 2009 DOI: https://doi.org/10.1137/1.9780898718751
C. S. Park, Fundamentals of Engineering Economics, Pearson Education, Inc., New Jersey, 2004
A. Castillo, D. F. Gayme, “Profit maximizing storage allocation in power grids”, IEEE 52nd Annual Conference on Decision and Control (CDC), pp. 429-435, 2013 DOI: https://doi.org/10.1109/CDC.2013.6759919
Q. Xu, C. Ding, J. Liu, B. Luo, “PCA-guided search for K-means”, Pattern Recognition Letters, Vol. 54, pp. 50-55, 2015 DOI: https://doi.org/10.1016/j.patrec.2014.11.017
D. D. Le, G. Gross, A. Berizzi, “Probabilistic Modeling of Multisite Wind Farm Production for Scenario-based Applications”, IEEE Transactions on Sustainable Energy, Vol. 6, No. 3, pp. 748-756, 2015 DOI: https://doi.org/10.1109/TSTE.2015.2411252
Bonneville Power Administration, Wind Generation &Total Load in The BPA Balancing Authority, available at: http://transmission.bpa.gov/
Business/Operations/Wind/ (date of last access: February 21, 2018)
S. M. Schoenungand, W. V. Hassenzahl, Long- vs. Short-Term Energy Storage Technologies Analysis, Sandia National Laboratories, U.S. Department of Commerce, 2003
S. M. Schoenungand, Characteristics and Technologies for Long- vs. Short-Term Energy Storage, Sandia National Laboratories, U.S. Department of Commerce, 2003
S. M. Schoenungand, Energy Storage Systems Cost Update, Sandia National Laboratories, 2011
Downloads
How to Cite
License
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
