Abstract
Dynamic programming(DP) is an effective and powerful mathematical tool to solve reservoir operation optimization(ROO) problems because it can yield global optimal solutions. But with the increase of the reservoirs’ number, DP will face problems like long computation time, large calculation scale, which is called ‘curse of dimensionality’. Heuristic random search algorithms and improved DP algorithms can decrease the computation time but they can only get near-optimal solutions. By analyzing the principle of DP in ROO, this paper finds that DP involves complex iterative computation and repeated procedures, which is very time-consuming. Aiming at solving these problems, this paper proposes a new notion called Hydropower Station Output Function (HSOF) and uses it to optimize and improve traditional DP, which can reduce the iterative computation and repeated procedures then improve computational efficiency. This paper takes Yayangshan hydroelectric power station in Li Xianjiang River Basin and the cascade hydropower station consisting of Yayangshan and Shimenkan hydropower stations as examples for single reservoir optimal operation (SROO) and cascade reservoir operation optimization (CROO). By comparing with the operation result of traditional DP and the progressive optimality algorithm (POA), case presents that the improved DP based on HSOF can reduce the programming complexity of DP, thus effectively alleviates the time-consuming problem and in the meantime, keeps the global convergence feature of DP.
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References
Akbari-Alashti H, Haddad OB, Mario MA (2015) Application of Fixed Length Gene Genetic Programming (FLGGP) in hydropower reservoir operation[J]. Water Resour Manag 29(9):3357–3370
Braga BPF, Yen WW, Becker L et al (1991) Stochastic optimization of multiple-reservoir-system operation[J]. J Water Resour Plan Manag 117(4):471–481
Fallah-Mehdipour E, Haddad OB, Mariño MA (2012) Real-time operation of reservoir system by genetic programming[J]. Water Resour Manag 26(14):4091–4103
Ji C, Jiang Z, Sun P et al (2014) Research and application of multidimensional dynamic programming in cascade reservoirs based on multilayer nested structure[J]. J Water Resour Plan Manag 141(7)
Kumar DN, Baliarsingh F (2003) Folded dynamic programming for optimal operation of multireservoir system[J]. Water Resour Manag 17(5):337–353(17)
Kumar DN, Reddy MJ (2010) Multipurpose reservoir operation using particle swarm optimization[J]. Am Soc Civil Eng 2006(3):192–201
Li-Ya MA, Lei XH, Jiang YZ et al (2012) Optimal operation of cascade reservoirs based on DPSA[J]. J China Inst Water Resourc Hydropower Res
Lu B, Li K, Zhang H et al (2013) Study on the optimal hydropower generation of Zhelin reservoir[J]. J Hydro Environ Res 7(4):270–278
Mousavi SJ, Ponnambalam K, Karray F (2005) Reservoir operation using a dynamic programming fuzzy rule-based approach[J]. Water Resour Manag 19(5):655–672
Pinthong P, Gupta AD, Babel MS et al (2009) Improved reservoir operation using hybrid genetic algorithm and neurofuzzy computing[J]. Water Resour Manag 23(4):697–720
Sun G, Zhao R (2014) Dynamic partition search algorithm for global numerical optimization[J]. Appl Intell 41(4):1108–1126
Sun P, Wang LP, Jiang ZQ et al (2014) Application of two multi-dimensional dynamic programming algorithms in optimization of cascade reservoirs operation[J]. Shuili Xuebao/J Hydraul Eng 45(11):1327–1335
Teegavarapu RSV, Simonovic SP (2002) Optimal operation of reservoir systems using simulated annealing[J]. Water Resour Manag 16(5):401–428
Tospornsampan J, Kita I, Ishii M et al (2005a) 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[J]. Paddy Water Environ 3(1):29–38
Tospornsampan J, Kita I, Ishii M et al (2005b) Optimization of a multiple reservoir system using a simulated annealing−A case study in the Mae Klong system, Thailand[J]. Paddy Water Environ 3(3):137–147
Umamahesh NV, Sreenivasulu P (1997) Technical communication: Two-phase stochastic dynamic programming model for optimal operation of irrigation reservoir[J]. Water Resour Manag 11(5):395–406
Xie W, Chang-Ming JI, Yue-Qiu WU et al (2010) Particle swarm optimization based on cultural algorithm for flood optimal scheduling of hydropower reservoir[J]. J Hydraul Eng
Yakowitz S (1982) Dynamic programming applications in water resources[J]. Water Resour Res 18(4):673–696
Yang CC, Chang LC, Yeh CH et al (2007) Multiobjective planning of surface water resources by multiobjective genetic algorithm with constrained differential dynamic programming[J]. J Water Resour Plan Manag 133(6):499–508
Zhang W, Liu P, Chen X et al (2015) Optimal operation of multi-reservoir systems considering time-lags of flood routing[J]. Water Resour Manag 1–18
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Chuangang, L., Changming, J., Boquan, W. et al. The Hydropower Station Output Function and its Application in Reservoir Operation. Water Resour Manage 31, 159–172 (2017). https://doi.org/10.1007/s11269-016-1516-2
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DOI: https://doi.org/10.1007/s11269-016-1516-2