Decision Support System for Optimizing Reservoir Operations Using Ensemble Streamflow Predictions

This paper investigates the value of ensemble streamflow predictions and energy price forecasts as aid to decision makers in scheduling the quantity and timing of reservoir releases for daily, weekly, and seasonal operations while meeting regulatory constraints. A decision support system DSS is described as it incorporates two integrated models of system operation: a simulation model that replicates general operating rules for the hydropower system and an optimization model that refines operations based upon forecasts of state variables. The DSS provides a series of recommendations for the quantity and timing of reservoir releases to optimize the economic value of the electrical energy produced, while balancing requirements and concerns related to flood control, environmental flows, and water supply. The DSS generates a range of optimal reservoir releases using an ensemble streamflow forecast and identifies robust operational solutions. The results indicate the value of the forecasts in improving system operation.

[1]  J. Stedinger,et al.  Water resource systems planning and analysis , 1981 .

[2]  Deepti Rani,et al.  Simulation–Optimization Modeling: A Survey and Potential Application in Reservoir Systems Operation , 2010 .

[3]  M. Wigmosta,et al.  A distributed hydrology-vegetation model for complex terrain , 1994 .

[4]  Luis Contesse,et al.  The value of information in a long–term hydro–thermal electrical planning model , 2003 .

[5]  Demetris Koutsoyiannis,et al.  A decision support tool for the management of multi-reservoir systems , 2002 .

[6]  Young-Oh Kim,et al.  Optimizing Operational Policies of a Korean Multireservoir System Using Sampling Stochastic Dynamic Programming with Ensemble Streamflow Prediction , 2007 .

[7]  S. Soares,et al.  Deterministic versus stochastic models for long term hydrothermal scheduling , 2006, 2006 IEEE Power Engineering Society General Meeting.

[8]  Alan F. Hamlet,et al.  PACIFIC NORTHWEST REGIONAL ASSESSMENT: THE IMPACTS OF CLIMATE VARIABILITY AND CLIMATE CHANGE ON THE WATER RESOURCES OF THE COLUMBIA RIVER BASIN 1 , 2000 .

[9]  Jery R. Stedinger,et al.  Reservoir optimization using sampling SDP with ensemble streamflow prediction (ESP) forecasts , 2001 .

[10]  David S. Richardson,et al.  ON THE ECONOMIC VALUE OF ENSEMBLE BASED WEATHER FORECASTS , 2001 .

[11]  Mohammad Karamouz,et al.  Uncertainty based operation of large scale reservoir systems: Dez and Karoon experience , 2003 .

[12]  Eugenia Kalnay,et al.  Ensemble Forecasting at NMC: The Generation of Perturbations , 1993 .

[13]  Daniel P. Loucks,et al.  Developing and implementing decision support systems: a critique and a challenge , 1995 .

[14]  Andrea Sulis,et al.  Water System Management through a Mixed Optimization-Simulation Approach , 2009 .

[15]  B. F. Sule,et al.  Stochastic dynamic programming models for reservoir operation optimization , 1984 .

[16]  Dennis P. Lettenmaier,et al.  Economic Value of Long-Lead Streamflow Forecasts for Columbia River Hydropower , 2002 .

[17]  Richard N. Palmer,et al.  Value of Seasonal Flow Forecasts in Bayesian Stochastic Programming , 1997 .

[18]  Sharon A. Johnson,et al.  The Value of Hydrologic Information in Stochastic Dynamic Programming Models of a Multireservoir System , 1995 .

[19]  Daniel P. Loucks,et al.  Water Resource Systems Models: Their Role in Planning , 1992 .