Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
권호 표지

Sensitivity Analysis for Operation a Reservoir System to Hydrologic Forecast Accuracy

수문학적 예측의 정확도에 따른 저수지 시스템 운영의 민감도 분석

  • Kim, Yeong-O (Research Associate, Global Hydrology and Climate Center, Huntsville, Alabama, USA)
  • Published : 1998.12.01
Download PDF
⟨ Previous Next ⟩

Abstract

This paper investigates the impact of the forecast error on performance of a reservoir system for hydropower production. Forecast error is measured as th Root Mean Square Error (RMSE) and parametrically varied within a Generalized Maintenance Of Variance Extension (GMOVE) procedure. A set of transition probabilities are calculated as a function of the RMSE of the GMOVE procedure and then incorporated into a Bayesian Stochastic Dynamic Programming model which derives monthly operating policies and assesses their performance. As a case study, the proposed methodology is applied to the Skagit Hydropower System (SHS) in Washington state. The results show that the system performance is a nonlinear function of RMSE and therefor suggested that continued improvements in the current forecast accuracy correspond to gradually greater increase in performance of the SHS.

본 연구는 수력발전을 위한 저수지 관리에 있어 예측오차의 영향을 살펴보기 위해 예측오차를 Root Mean Square Error(RMSE)로 측정하였고, 이를 Generalized Maintenance Of Variance Extension (GMOVE)기법을 통하여 변화시켜보았다.변화된 예측오차의 RMSE는 천이확률을 통하여 Bayesian Stochastic Dynamic Programming (BSDP)에 고려되어졌으며, 이 BSDP 모형을 이용하여 월별 방류량을 결정하였고 그 유용성을 평가하였다. 제시된 연구방법은 미국의 Skagit 시스템에 적용되었고, 그 결과로 Skagit 시스템의 운영은 예측오차의 RMSE에 비선형이므로 반응하므로 이 시스템의 운영을 개선하기 위해서는 현재의 수문학적 예측기법을 개선해야함을 제시하였다.

Keywords

References

  1. Water Resources Research v.25 no.3 A generalized MOVE procedure for extending correlated series Grygier, J.C.;Stedinger, J.R.;Yin, H.B.
  2. Water Resources Bulletin v.16 no.5 Comparison of models for forecasting snowmelt runoff volumes Hawley, M.E.;Mccuen, R.H.;Rango, A.
  3. Water Resources Research v.26 no.3 Sampling stochastic dynamic programming applied to reservoir operation Kelman, J.;Stedinger, J.R.;Cooper, L.A.;Hsu, E.;Yuan, S.
  4. Journal of Water Resources Planning and Management v.123 no.6 Value of seasonal flow forecasts in Bayesian Stochastic programming Kim, Y.-O.;Palmer, R.N.
  5. Journal of Hydraulic Engineering v.110 no.3 Synthetic streamflow forecast generation Lettenmaier, D.P.
  6. Proceedings of 47th Western Snow conference Evaluation of streamflow forecasting methods Lettenmaier, D.P.;Garen, D.C.
  7. Water Resources Bulletin v.24 no.6 Forecast uncertainty in water supply reservoir operation Mishalani, N.R.;Palmer, R.N.
  8. Power System Engineering Information on Seattle city Light Power System for 1990 Seattle City Light
  9. Journal of Water Resources Planning and Management v.108 no.3 Worth of Inflow Forecast for Reservoir Operation Yeh, W.W-G;Becker, L.;Zettlemoyer, R.