Browse > Article
http://dx.doi.org/10.3741/JKWRA.2018.51.S-1.1135

Development of Robust-SDP for improving dam operation to cope with non-stationarity of climate change  

Yoon, Hae Na (Department of Civil & Environmental Engineering, Seoul National University)
Seo, Seung Beom (Institute of Engineering Research, Seoul National University)
Kim, Young-Oh (Department of Civil & Environmental Engineering, Seoul National University)
Publication Information
Journal of Korea Water Resources Association / v.51, no.spc, 2018 , pp. 1135-1148 More about this Journal
Abstract
Previous studies on reservoir operation have been assumed that the climate in the future would be similar to that in the past. However, in the presence of climate non-stationarity, Robust Optimization (RO) which finds the feasible solutions under broader uncertainty is necessary. RO improves the existing optimization method by adding a robust term to the objective function that controls the uncertainty inherent due to input data instability. This study proposed Robust-SDP that combines Stochastic Dynamic Programming (SDP) and RO to estimate dam operation rules while coping with climate non-stationarity. The future inflow series that reflect climate non-stationarity were synthetically generated. We then evaluated the capacity of the dam operation rules obtained from the past inflow series based on six evaluation indicators and two decision support schemes. Although Robust-SDP was successful in reducing the incidence of extreme water scarcity events under climate non-stationarity, there was a trade-off between the number of extreme water scarcity events and the water scarcity ratio. Thus, it is proposed that decision-makers choose their optimal rules in reference to the evaluation results and decision support illustrations.
Keywords
Climate change; Robust optimization; Decision making; Reservoir operation;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Ben-Tal, A., and Nemirovski, A. (2002). "Robust optimizationmethodology and applications." Mathematical Programming, Vol. 92, No. 3, pp. 453-480.   DOI
2 Brown, C., Ghile, Y., Laverty, M., and Li, K. (2012). "Decision scaling: Linking bottom -up vulnerability analysis with climate projections in the water sector." Water Resources Research, Vol. 48, No. 9.
3 Housh, M., Ostfeld, A., and Shamir, U. (2011). "Optimal multiyear management of a water supply system under uncertainty: Robust counterpart approach." Water Resources Research, Vol. 47, No. 10.
4 K water (2016). Practical Manual of Dam Op eration.
5 Kasprzyk, J. R., Nataraj, S., Reed, P. M., and Lempert, R. J. (2013). "Many objective robust decision making for complex environmental systems undergoing change." Environmental Modelling & Software, Vol. 42, pp. 55-71.   DOI
6 Kim, Y. -O., and Chung, E. S. (2017). "Chapter 8. adaptation to climate change: decision-making" In: Kolokytha et al. (eds), Sustainable Water Resources Planning and Management Under Climate Change, Springer Singapore, pp. 189-221.
7 Kim, Y. -O., Eum, H. -I., Lee, E. -G., and Ko, I. H. (2007). "Optimizing operational policies of a Korean multireservoir system using sampling stochastic dynamic programming with ensemble streamflow prediction." Journal of Water Resources Planning and Management, Vol. 133, No. 1, pp. 4-14.   DOI
8 Pan, L., Housh, M., Liu, P., Cai, X., and Chen, X. (2015). "Robust stochastic optimization for reservoir operation." Water Resources Research, Vol. 51, No. 1, pp. 409-429.   DOI
9 Seo, S. B., and Kim, Y.-O. (2018). "Impact of spatial aggregation level of climate indicators on a national-level selection for representative climate change scenarios." Sustainability, Vol. 10, No. 7, p. 2409.   DOI
10 Ray, P. A., Watkins Jr, D. W., Vogel, R. M., and Kirshen, P. H. (2013). "Performance-based evaluation of an improved robust optimization formulation." Journal of Water Resources Planning and Management, Vol. 140, No. 6, 04014006.   DOI
11 Seo, S. B., Kim, Y.-O., Kim, Y., and Eum, H.-I. (2018). "Selecting climate change scenarios for regional hydrologic impact studies based on climate extreme indices." Climate Dynamics, pp. 1-17.
12 Tejada-Guibert, J. A., Johnson, S. A., and Stedinger, J. R. (1995). "The value of hydrologic information in stochastic dynamic programming models of a multireservoir system." Water resources research, Vol. 31, No. 10, pp. 2571-2579.   DOI
13 Watkins Jr, D. W., and McKinney, D. C. (1997). "Finding robust solutions to water resources problems." Journal of water resources planning and management, Vol. 123, No. 1, pp. 49-58.   DOI
14 Mulvey, J. M., Vanderbei, R. J., and Zenios, S. A. (1995). "Robust optimization of large-scale systems." Operations research, Vol. 43, No. 2, pp. 264-281.   DOI