Young-Oh Kim

This paper presents a Bayesian Stochastic Dynamic Programming (BSDP) model to investigate the value of seasonal flow forecasts in hydropower generation. The proposed BSDP framework generates monthly operating policies for the Skagit Hydropower System (SHS), which supplies energy to the Seattle metropolitan area. The objective function maximizes the total benefits resulting from energy produced by the SHS and its interchange with the Bonneville Power Administration. The BSDP-derived operating pol

This study presents state-of-the-art optimization techniques for enhancing reservoir operations which use sampling stochastic dynamic programming (SSDP) with ensemble streamflow prediction (ESP). SSDP used with historical inflow scenarios (SSDP/Hist) derives an off-line optimal operating policy through a backward-moving solution procedure. In contrast, SSDP used with monthly forecasts of ESP (SSSDP/ESP) reoptimizes the off-line policy. These stochastic models are used to derive a monthly joint o

This study reviewed various combining methods that have been commonly used in economic forecasting, and examined their applicability in hydrologic forecasting. The following combining methods were investigated: The simple average, constant coefficient regression, switching regression, sum of squared error, and artificial neural network combining methods. Each method combines ensemble streamflow prediction (ESP) scenarios of the existing rainfall-runoff model, TANK, those of the new rainfall-runo

Reservoir operations should consider both adaptiveness and robustness to deal with two of the main characteristics of climate change: nonstationarity and deep uncertainty. In particular, robust operational strategies are distinguished from risk-neutral expected value optimization in the sense that they should be satisfactory over a wider range of uncertainty and improve the ability of a reservoir system to adapt to climate change. In this study, a new framework named robust stochastic dynamic pr

Abstract The purpose of this study is to propose an alternative forecasting approach for improving the current water supply outlook in Korea. Using a rainfall-runoff model, the existing technique for the water supply outlook in Korea produces monthly low, average, and high runoff forecasts. The proposed technique is called Ensemble Streamflow Prediction (ESP), and is currently implemented by the National Weather Service in the U.S.A. ESP appears particularly valid in Korea where the historical r

Most studies of the uncertainties in climate change impact assessments focus on each stage independently without considering correlations between stages. Therefore, it is difficult to quantify the relative contribution of each stage to the total uncertainty and to identify how uncertainties are propagated as the stages proceed. In this study, we propose a new method for decomposing total uncertainty to components from individual stages. The proposed method is more theoretically sound compared to

Abstract Understanding the ion dynamics within the electric double layer (EDL) is crucial for maximizing the potential of chemo‐mechanical energy harvesters. This study elucidates the electrochemical response of EDL to the compressive mechanical stimulation of carbon nanotube (CNT) yarns from the perspective of ion adsorption. The results revealed that H 3 O + contributed to the ionic capacitance of the EDL by forming a polarized layer with Cl − on the outer Helmholtz plane. The unique molecular

In this study, it was theoretically demonstrated that efficient intrachain energy transfer and robust network structure construction improved the UV resistance of the epoxy matrix.

Abstract Climate change studies usually include the use of many projections, and selecting an essential number of projections is very important, because using all Global Climate Model (GCM) scenarios is impossible in practice. Furthermore, the climate change impact assessment is often sensitive to the choice of GCM scenarios. This study suggests that selecting the best-performing scenarios based on a historical period should be avoided in nonstationary cases like climate change, and then propose