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

Hae Na Yoon; Seung Beom Seo; Young-Oh Kim

doi:10.3741/JKWRA.2018.51.S-1.1135

All Issue

2018 Vol.51, Issue 11S Preview Page Next Page

Research Article

Development of Robust-SDP for improving dam operation to cope with non-stationarity of climate change 기후변화의 비정상성 대비 댐 운영 개선을 위한 Robust-SDP의 개발

30 November 2018. pp. 1135-1148

PDF XML

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

기존의 저수지 운영 연구들은 미래의 기후가 과거와 유사하다는 정상성의 가정을 전제로 하였다. 하지만 기후의 비정상성으로 인해 불확실성이 더욱 커질 경우에는 큰 불확실성에서도 안정된 최적해를 찾을 수 있는 로버스트 최적화 과정(Robust Optimization, 이하 RO)이 필요하다고 알려져있다. RO는 입력자료의 비정상성으로 인해 야기되는 불확실성을 제어하는 로버스트 항을 목적함수에 추가하여 기존의 최적화 방법을 개선한다. 본 연구는 기후변화의 비정상성을 대비하는 저수지 운영규칙 산정을 위해 추계학적동적계획법(Stochastic Dynamic Programing, 이하 SDP)과 RO를 결합하는 Robust-SDP를 제안하였고, 이를 최근 4년간 가뭄을 겪었던 보령댐에 적용하였다. 즉, 비정상성이 반영된 미래 유입량 자료를 생성하고 이를 6가지의 평가지표와 2가지의 의사결정 지원그림을 사용하여 과거 유입량 자료로부터 산출된 저수지 운영규칙의 수행능력을 평가하였다. 그 결과, Robust-SDP가 기후의 비정상성 하에서 극단적인 물 부족 사건의 발생률과 물 부족 사건의 실패의 크기를 감소시켰지만, 작은 크기의 물 부족 발생률은 증가하는 상충관계(trade-off)를 가져옴을 확인할 수 있었다. 이를 바탕으로 의사결정자가 우선시하는 평가지표의 결과에 따라 최적화 모형을 선택할 수 있음을 제안하였다.

키워드

기후변화

로버스트 최적화

의사결정 방법론

저수지 운영

References

Ben-Tal, A., and Nemirovski, A. (2002). "Robust optimization- methodology and applications." Mathematical Programming, Vol. 92, No. 3, pp. 453-480.

10.1007/s101070100286

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.

10.1029/2011WR011212

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.

10.1029/2011WR010596

K water (2016). Practical Manual of Dam Op eration.

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.

10.1016/j.envsoft.2012.12.007

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.

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.

10.1061/(ASCE)0733-9496(2007)133:1(4)

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.

10.1287/opre.43.2.264

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.

10.1002/2014WR015380

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.

10.1061/(ASCE)WR.1943-5452.0000389

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.

10.3390/su10072409

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.

10.1007/s00382-018-4210-7

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.

10.1029/95WR02172

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.

10.1061/(ASCE)0733-9496(1997)123:1(49)

Information

Publisher :KOREA WATER RESOURECES ASSOCIATION
Publisher(Ko) :한국수자원학회
Journal Title :Journal of Korea Water Resources Association
Journal Title(Ko) :한국수자원학회 논문집
Volume : 51
No :11
Pages :1135-1148
Received Date : 2018-09-06
Revised Date : 2018-11-01
Accepted Date : 2018-11-01
DOI :https://doi.org/10.3741/JKWRA.2018.51.S-1.1135

Journal of Korea Water Resources Association ISSN:2799-8746(Print) 2799-8754(Online) 한국수자원학회 논문집

All Issue