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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

  • 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)
  • 윤해나 (서울대학교 공과대학 건설환경공학부) ;
  • 서승범 (서울대학교 공학연구원) ;
  • 김영오 (서울대학교 공과대학 건설환경공학부)
  • Received : 2018.09.06
  • Accepted : 2018.11.01
  • Published : 2018.11.30

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.

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 알려져 있다. 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.

Keywords

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Fig. 1. The example of decision scaling plot

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Fig. 2. The example of parallel coordinates plot

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Fig. 3. location of study site, boryeong dam basin (WAMIS)

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Fig. 4. Stroage curve of boryeong dam (1998 ~ 2017)

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Fig. 5. Decision scaling plot of WDR (p.o.)

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Fig. 6. Decision scaling plot of risk

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Fig. 7. Decision scaling plot of risk (30%)

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Fig. 8. Parallel coordinates plot

Table 1. Classification of performance indices

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Table 2. Features of boryeong dam

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Table 3. Optimization model with different weight values

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Table 4. The threshold value of each indices

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Table 5. The results of MSDS for six performance indices

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