Abstract
Optimal cascade reservoir scheduling is a complex problem related to the broad interests of society, economy, and environment. This study proposes a solution for dispatching cascade reservoir operation optimization based on the multi-objective water cycle algorithm (MWCA). Search strategies for confluence, diversion, seepage, evaporation, and rainfall are established in the MWCA by simulating the natural water cycle process. A relative gravity mechanism under multi-objective is constructed to achieve an adequate search for optimal solutions. In the simulation section, the calculation results of the proposed approach are compared with the other methods in the literature, e.g., particle swarm optimization (MOPSO) and the genetic algorithm (NSGA-II). Compared results show that MWCA is superior to other algorithms in calculation diversity and an effective solution to the multi-objective optimal scheduling problem of cascade reservoir groups.
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References
Cosslett, T.L., Cosslett, P.D.: Water Resources and Food Security in the Vietnam Mekong Delta. Springer (2014)
Nguyen, T.-T., Wang, H.-J., Dao, T.-K., Pan, J.-S., Liu, J.-H., Weng, S.-W.: An improved slime mold algorithm and its application for optimal operation of cascade hydropower stations. IEEE Access. 8, 1 (2020)
Dao, T.-K., Chang, K.-C., Chu, K.-C., Nguyen, T.-T.-T., Ngo, T.-G., Nguyen, T.-T.: A solution for cascade hydropower station reservoirs optimal operation based on improved bat algorithm BT. In: Advanced Presented at the Machine Learning Technologies and Applications (2021)
Tsai, C.F., Dao, T.K., Pan, T.S., Nguyen, T.T., Chang, J.F.: Parallel bat algorithm applied to the economic load dispatch problem. J. Internet Technol. 17, 761–769 (2016). https://doi.org/10.6138/JIT.2016.17.4.20141014c
Nguyen, T.-T., Wang, M.-J., Pan, J.-S., Dao, T., Ngo, T.-G.: A load economic dispatch based on ion motion optimization algorithm BT. In: Presented at the Advances in Intelligent Information Hiding and Multimedia Signal Processing (2020)
Nguyen, T.T., Ngo, T.G., Dao, T.K., Nguyen, T.T.T.: Microgrid operations planning based on improving the flying sparrow search algorithm. Symmetry 14 (2022)
Nguyen, T.-T., Shieh, C.-S., Horng, M.-F., Dao, T.-K.: A genetic algorithm with self-configuration chromosome for the optimization of wireless sensor networks
Shi, Y., Eberhart, R.C.: Empirical study of particle swarm optimization. In: Proceedings of the 1999 Congress on Evolutionary Computation, 1999. CEC 99, vol. 3, pp. 1945–1950 (1999)
Cuevas, E., Cienfuegos, M.: A new algorithm inspired in the behavior of the social-spider for constrained optimization. Expert Syst. Appl. 41, 412–425 (2014)
Yang, X.-S., Deb, S.: Cuckoo search via Lévy flights. In: 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), pp. 210–214. IEEE (2009)
Eskandar, H., Sadollah, A., Bahreininejad, A., Hamdi, M.: Water cycle algorithm—a novel metaheuristic optimization method for solving constrained engineering optimization problems. Comput. Struct. 110, 151–166 (2012)
Nasir, M., Sadollah, A., Choi, Y.H., Kim, J.H.: A comprehensive review on water cycle algorithm and its applications. Neural Comput. Appl. 32(23), 17433–17488 (2020). https://doi.org/10.1007/s00521-020-05112-1
Nguyen, T.T., Pan, J.S., Dao, T.K.: An improved flower pollination algorithm for optimizing layouts of nodes in wireless sensor network. IEEE Access. 7, 75985–75998 (2019). https://doi.org/10.1109/ACCESS.2019.2921721
Dao, T.-K., Nguyen, T.-T., Nguyen, V.-T., Nguyen, T.-D.: A hybridized flower pollination algorithm and its application on microgrid operations planning. Appl. Sci. 12, 6487 (2022)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6, 182–197 (2002)
Coello Coello, C. A., Reyes-Sierra, M.: Multi-objective particle swarm optimizers: a survey of the state-of-the-art. Int. J. Comput. Intell. Res. 2, 287–308 (2006). https://doi.org/10.5019/j.ijcir.2006.68
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This study was supported by the Thai Nguyen University of Technology.
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Dao, TK., Nguyen, TT., Do, TV., Nguyen, TD., Nguyen, VT. (2023). An Optimal Cascade Reservoir Operation Based on Multi-objective Water Cycle Algorithm. In: Nguyen, D.C., Vu, N.P., Long, B.T., Puta, H., Sattler, KU. (eds) Advances in Engineering Research and Application. ICERA 2022. Lecture Notes in Networks and Systems, vol 602. Springer, Cham. https://doi.org/10.1007/978-3-031-22200-9_20
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DOI: https://doi.org/10.1007/978-3-031-22200-9_20
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