Decision Support System for Optimizing Reservoir Operations Using Ensemble Streamflow Predictions
Publication: Journal of Water Resources Planning and Management
Volume 137, Issue 1
Abstract
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.
Get full access to this article
View all available purchase options and get full access to this article.
References
Contesse, L., Donoso, P., and Prina, J. (2003). “The value of information in a long-term hydro-thermal electrical planning model.” Int. Trans. Oper. Res., 10(1), 89–100.
Faber, B. A., and Stedinger, J. R. (2001). “Reservoir optimization using sampling SDP with ensemble streamflow prediction (ESP) forecasts.” J. Hydrol., 249(1–4), 113–133.
Goldsim probabilistic simulation environment user’s guide. (2010). Goldsim Technology Group, Issaquah, Wash., ⟨www.goldsim.com⟩ (11/1/2010).
Hamlet, A. F., Huppert, D., and Lettenmaier, D. P. (2002). “Economic value of long-lead streamflow forecasts for Columbia River hydropower.” J. Water Resour. Plann. Manage., 128(2), 91–101.
Karamouz, M., and Mousavi, S. J. (2003). “Uncertainty-based operation of large scale reservoir systems: Dez and Karoun experience.” J. Am. Water Resour. Assoc., 39(4), 961–975.
Kim, Y. O., Eum, H. I., Lee, E. G., and Ko, I. H. (2007). “Optimizing operational policies of a Korean multi-reservoir system using sampling stochastic dynamic programming with ensemble streamflow prediction.” J. Water Resour. Plann. Manage., 133(1), 4–14.
Kim, Y. O., and Palmer, R. N. (1997). “Value of seasonal flow forecasts in Bayesian stochastic programming.” J. Water Resour. Plann. Manage., 123, 327–335.
Koutsoyiannis, D., Efstratiadis, A., and Karavokiros, G. (2002). “A decision support tool for the management of multireservoir systems.” J. Am. Water Resour. Assoc., 38(4), 945–958.
LINDO Systems Inc. (2007). LINGO user’s guide, Chicago, ⟨www.lindo.com⟩ (11/1/2010).
Loucks, D. P. (1992). “Water resource systems models: Their role in planning.” J. Water Resour. Plann. Manage., 118(3), 214–223.
Loucks, D. P. (1995). “Developing and implementing decision support systems: A critique and a challenge.” Water Resour. Bull., 31(4), 571–582.
Loucks, D. P., Stedinger, J. R., and Haith, D. A. (1981). Water resources systems planning and analysis, Prentice-Hall, Englewood Cliffs, N.J.
Miles, E. L., Snover, A., Hamlet, A. F., Callahan, B., and Fulharty, D. (2000). “Pacific Northwest regional assessment: The impacts of climate variability and climate change on the water resources of the Columbia River Basin.” J. Am. Water Resour. Assoc., 36(2), 399–420.
Rani, D., and Moreira, M. M. (2010). “Simulation-optimization modeling: A Survey and potential application in reservoir systems operation.” Water Resour. Manage., 24, 1107–1138.
Sechi, G. M., and Sulis, A. (2009). “Water system management through a mixed optimization-simulation approach.” J. Water Resour. Plann. Manage., 135(3), 160–170.
Stedinger, J. R., Sule, B. F., and Loucks, D. P. (1984). “Stochastic dynamic programming models for reservoir operation optimization.” Water Resour. Res., 20(11), 1499–1505.
Tejada-Guibert, J., Johnson, S., and Stedinger, J. R. (1995). “The value of hydrologic information in stochastic dynamic programming models of a multireservoir system.” Water Resour. Res., 31(10), 2571–2579.
Toth, Z., and Kalnay, E. (1993). “Ensemble forecasting at NMC: The generation of perturbations.” Bull. Am. Meteorol. Soc., 74, 2317–2330.
Wigmosta, M. S., Vail, L. W., and Lettenmaier, D. P. (1994). “A distributed hydrology vegetation model for complex terrain.” Water Resour. Res., 30(6), 1665–1679.
Zambelli, M., Siqueira, T. G., Cicogna, M. A., and Soares, S. S. (2006). “Deterministic versus stochastic models for long term hydrothermal scheduling.” Proc., Institute of Electrical and Electronics Engineers, Power Engineering Society General Meeting, IEEE, New York.
Zhu, Y., Toth, Z., Wobus, R., Richardson, D., and Mylne, K. (2002). “The economic value of ensemble-based weather forecasts.” Bull. Am. Meteorol. Soc., 83, 73–83.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 137 • Issue 1 • January 2011
Pages: 72 - 82
Copyright
© 2011 ASCE.
History
Received: Nov 23, 2009
Accepted: Mar 27, 2010
Published online: Apr 8, 2010
Published in print: Jan 2011
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.