An optimal algorithm for cascaded reservoir operation by combining the grey forecasting model with DDDP

The operation of the cascaded reservoirs is a complex problem, and lots of algorithms have been developed for optimal cascaded reservoirs operation. However, the existing algorithms usually have the disadvantages such as the ‘curse of dimensionality’ and prematurity. This study proposes a grey discrete differential dynamic programming (GDDDP) algorithm for effectively optimizing the cascaded reservoir operation model, which is a combination of the grey forecasting model and discrete differential dynamic programming (DDDP). Additionally, a modification of the grey forecasting model is presented for better forecast accuracy. The proposed method is applied to optimize the Baishan-Fengman cascaded reservoir system in the northeast of China. The results show that GDDDP obtains more power generation than DDDP with less computing time in three cases, i.e., dry years, wet years and the whole series. Especially in the case of the whole series, the power generation of GDDDP is 2.13 MWH more than that of DDDP, while the computing time is decreased by 66,161 ms. Moreover, the power generation of GDDDP is comparable with that of dynamic programming but the computing time is much less. All these indicate GDDDP has high accuracy and efficiency, which implies that it is practicable for the operation of cascaded reservoir system.

[1]  Chang-Ming Ji,et al.  Large-scale hydropower system optimization using dynamic programming and object-oriented programming: the case of the Northeast China Power Grid. , 2013, Water science and technology : a journal of the International Association on Water Pollution Research.

[2]  Ying Wang,et al.  Multi-objective differential evolution with adaptive Cauchy mutation for short-term multi-objective optimal hydro-thermal scheduling , 2010 .

[3]  Sen Wang,et al.  Parallel discrete differential dynamic programming for multireservoir operation , 2014, Environ. Model. Softw..

[4]  Ping Sun,et al.  Contrastive analysis of three parallel modes in multi-dimensional dynamic programming and its application in cascade reservoirs operation , 2015 .

[5]  Huifeng Zhang,et al.  Optimal Operation of Large-Scale Cascaded Hydropower Systems in the Upper Reaches of the Yangtze River, China , 2014 .

[6]  N. G. F. Sancho,et al.  A new algorithm for the solution of multi-state dynamic programming problems , 1975, Math. Program..

[7]  David R. Maidment,et al.  Computer time and memory requirements for DP and DDDP in water resource systems analysis , 1975 .

[8]  Khalid AHMAD-RASHID,et al.  OPTIMAL OPERATION OF LARGE HYDROPOWER RESERVOIRS WITH UNREGULATED INFLOWS , 2011 .

[9]  R. Bellman.  Dynamic programming. , 1957, Science.

[10]  Omid Bozorg Haddad,et al.  Weed Optimization Algorithm for Optimal Reservoir Operation , 2016 .

[11]  Mücahit Opan.  Çok Barajlı Sistemde Gerçek Zamanlı Optimal İşletme , 2011 .

[12]  P. P. Mujumdar,et al.  Real‐time reservoir operation for irrigation , 1997 .

[13]  Mücahit Opan,et al.  Real-Time Optimal Operation of Multiple Reservoirs System , 2011 .

[14]  Omid Bozorg-Haddad,et al.  Development and Application of the Bat Algorithm for Optimizing the Operation of Reservoir Systems , 2015 .

[15]  M. Janga Reddy,et al.  Multipurpose Reservoir Operation Using Particle Swarm Optimization , 2007 .

[16]  A. Burcu Altan-Sakarya,et al.  Optimization of Multireservoir Systems by Genetic Algorithm , 2011 .

[17]  Pao-Shan Yu,et al.  APPLICATION OF GREY MODEL TOWARD RUNOFF FORECASTING 1 , 2001 .

[18]  Peng Lu,et al.  Daily Generation Scheduling of Cascade Hydro Plants Considering Peak Shaving Constraints , 2016 .

[19]  Yoshinobu Kitamura,et al.  Optimization of a multiple reservoir system operation using a combination of genetic algorithm and discrete differential dynamic programming: a case study in Mae Klong system, Thailand , 2005, Paddy and Water Environment.

[20]  Frank T.-C. Tsai,et al.  Optimization of Large-Scale Hydropower System Operations , 2003 .

[21]  Coşkun Hamzaçebi,et al.  Forecasting the annual electricity consumption of Turkey using an optimized grey model , 2014 .

[22]  Miguel A. Mariño,et al.  Multi-Colony Ant Algorithm for Continuous Multi-Reservoir Operation Optimization Problem , 2007 .

[23]  M. Mao,et al.  Application of grey model GM(1, 1) to vehicle fatality risk estimation , 2006 .

[24]  Songfeng Lu,et al.  An improved quantum-behaved particle swarm optimization method for short-term combined economic emission hydrothermal scheduling , 2010 .

[25]  Li-Chang Hsu,et al.  Applying the Grey prediction model to the global integrated circuit industry , 2003 .

[26]  Chen Lu,et al.  Improved decomposition-coordination and discrete differential dynamic programming for optimization of large-scale hydropower system , 2014 .

[27]  Omid Bozorg Haddad,et al.  Optimal Monthly Reservoir Operation Rules for Hydropower Generation Derived with SVR-NSGAII , 2015 .

[28]  J. Deng,et al.  Introduction to Grey system theory , 1989 .

[29]  A. Turgeon.  Optimal short-term hydro scheduling from the principle of progressive optimality , 1981 .

[30]  Ju-Hwan Yoo,et al.  Maximization of hydropower generation through the application of a linear programming model , 2009 .

[31]  V. T. Chow,et al.  Discrete Differential Dynamic Programing Approach to Water Resources Systems Optimization , 1971 .

[32]  John W. Labadie,et al.  Dynamic Optimal Unit Commitment and Loading in Hydropower Systems , 2003 .