Optimal Multipurpose-Multireservoir Operation Model with Variable Productivity of Hydropower Plants

Stochastic dual dynamic programming (SDDP) is one of the few methods available to solve multipurpose-multireservoir operation problems in a stochastic environment. This algorithm requires that the one-stage optimization problem be a convex program so that the efficient Benders decomposition scheme can be implemented to handle the large state-space that characterizes multireservoir operation problems. When working with hydropower systems, one usually assumes that the production of hydroelectricity is dominated by the release term and not by the head (storage) term to circumvent the nonlinearity of the hydropower production function. Although this approximation is satisfactory for high head power stations for which the difference between the maximum and the minimum head is small compared to the maximum head, it may no longer be acceptable when a significant portion of the energy originates from low and/or medium head power plants. Recent developments improve the representation of the nonlinear hydropower fu...

[1]  Peter K. Kitanidis,et al.  Limitations of Deterministic Optimization Applied to Reservoir Operations , 1999 .

[2]  Lyn C. Thomas,et al.  An aggregate stochastic dynamic programming model of multireservoir systems , 1997 .

[3]  A. Tilmant,et al.  Assessing marginal water values in multipurpose multireservoir systems via stochastic programming , 2008 .

[4]  David P. Dobkin,et al.  The quickhull algorithm for convex hulls , 1996, TOMS.

[5]  D. McKinney,et al.  Decomposition methods for water resources optimization models with fixed costs , 1998 .

[6]  Carlos Tomei,et al.  Optimal hydrothermal scheduling with variable production coefficient , 2002, Math. Methods Oper. Res..

[7]  D. Whittington,et al.  Incentive compatibility and conflict resolution in international river basins: A case study of the Nile Basin , 2006 .

[8]  Leon S. Lasdon,et al.  Solving Large Nonconvex Water Resources Management Models Using Generalized Benders Decomposition , 2001, Oper. Res..

[9]  John W. Labadie,et al.  Optimal Operation of Multireservoir Systems: State-of-the-Art Review , 2004 .

[10]  M. Pereira.  Optimal stochastic operations scheduling of large hydroelectric systems , 1989 .

[11]  Cristiano Cervellera,et al.  Optimization of a large-scale water reservoir network by stochastic dynamic programming with efficient state space discretization , 2006, Eur. J. Oper. Res..

[12]  K. Haynes,et al.  International management of the Nile - stage three? , 1981 .

[13]  William W.-G. Yeh,et al.  Reservoir Management and Operations Models: A State‐of‐the‐Art Review , 1985 .

[14]  A. Gjelsvik,et al.  Stochastic dual dynamic programming for seasonal scheduling in the Norwegian power system , 1992 .

[15]  J. J. Bogardi,et al.  Testing Stochastic Dynamic Programming Models Conditioned on Observed or Forecasted Inflows , 1991 .

[16]  Sharon A. Johnson,et al.  Comparison of two approaches for implementing multireservoir operating policies derived using stochastic dynamic programming , 1993 .

[17]  C. S. Buchanan,et al.  Nested Benders decomposition and dynamic programming for reservoir optimisation , 1999, J. Oper. Res. Soc..

[18]  M. Pereira,et al.  Stochastic Optimization of a Multireservoir Hydroelectric System: A Decomposition Approach , 1985 .

[19]  D. Whittington,et al.  Water Resources Management in the Nile Basin: The Economic Value of Cooperation , 2005 .

[20]  L. S. Pereira,et al.  Crop evapotranspiration : guidelines for computing crop water requirements , 1998 .

[21]  Jin-Hee Lee,et al.  Stochastic optimization of multireservoir systems via reinforcement learning , 2007 .

[22]  S. Wallace,et al.  Stochastic Programming Models in Energy , 2003 .

[23]  Haralambos V. Vasiliadis,et al.  Bayesian stochastic optimization of reservoir operation using uncertain forecasts , 1992 .

[24]  Peter Kall,et al.  Stochastic Programming , 1995 .

[25]  Jery R. Stedinger,et al.  Water Resources Systems Planning And Management , 2006 .

[26]  Daniele de Rigo,et al.  Neuro-dynamic programming for designing water reservoir network management policies , 2007 .

[27]  A. Turgeon,et al.  Learning disaggregation technique for the operation of long‐term hydroelectric power systems , 1994 .

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

[29]  Birger Mo,et al.  Integrated risk management of hydro power scheduling and contract management , 2001 .

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

[31]  D. H. Marks,et al.  Agricultural vs. hydropower tradeoffs in the operation of the High Aswan Dam , 1982 .

[32]  M. V. F. Pereira,et al.  Multi-stage stochastic optimization applied to energy planning , 1991, Math. Program..

[33]  Ying Li,et al.  Numerical Solution of Continuous-State Dynamic Programs Using Linear and Spline Interpolation , 1993, Oper. Res..

[34]  Tarjei Kristiansen.  Financial risk management in the electric power industry using stochastic optimization , 2004 .

[35]  Amaury Tilmant,et al.  A stochastic approach to analyze trade‐offs and risks associated with large‐scale water resources systems , 2007 .