Abstract
In this article we propose the use of black box global stochastic optimization techniques to address the complex problem of sizing renewable sources and electrochemical storage to feed a reverse osmosis desalination plant. We present a scenario simulation technique based on field and synthetic data, and then that complex engineering simulation will be used as the objective function of an optimization problem. Finally the results and conclusions are presented proving the feasibility of the approach for the problem at hand.
The original version of this chapter was revised: Incorrect author names have been corrected. The erratum to this chapter is available at https://doi.org/10.1007/978-3-319-67618-0_36
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References
Eriksson, D., Bindel, D., Shoemaker, C.: Surrogate Optimization Toolbox (pySOT) (2015). github.com/dme65/pySOT
Desalination plant software (2017). https://github.com/SanPen/DesalinationPlant
Regis, R.G., Shoemaker, C.A.: Combining radial basis function surrogates and dynamic coordinate search in high-dimensional expensive black-box optimization. Eng. Optim. 45, 529–555 (2013)
Tsiakis, P., Papageorgiou, L.G.: Optimal design of an electrodialysis brackish water desalination plant. Desalination 173(2), 173–186 (2005)
Rubio-Maya, C., Uche-Marcuello, J., Martínez-Gracia, A., Bayod-Rújula, A.A.: Design optimization of a polygeneration plant fuelled by natural gas and renewable energy sources. Appl. Energy 88(2), 449–457 (2011)
Garcia, R.S., Weisser, D.: A wind-diesel system with hydrogen storage: joint optimisation of design and dispatch. Renew. Energy 31(14), 2296–2320 (2006)
Voros, N.G., Kiranoudis, C.T., Maroulis, Z.B.: Solar energy exploitation for reverse osmosis desalination plants. Desalination 115(1), 83–101 (1998)
Bourouni, K., M’Barek, T.B., Al Taee, A.: Design and optimization of desalination reverse osmosis plants driven by renewable energies using genetic algorithms. Renew. Energy 36(3), 936–950 (2011)
Guria, C., Bhattacharya, P.K., Gupta, S.K.: Multi-objective optimization of reverse osmosis desalination units using different adaptations of the Non-dominated Sorting Genetic Algorithm (NSGA). Comput. Chem. Eng. 29(9), 1977–1995 (2005)
Djebedjian, B., Gad, H., Khaled, I., Rayan, M.A.: Optimization of reverse osmosis desalination system using genetic algorithms technique. In: Twelfth International Water Technology Conference, IWTC12, Alexandria, Egypt, March 2008
Lee, Y.G., Lee, Y.S., Jeon, J.J., Lee, S., Yang, D.R., Kim, I.S., Kim, J.H.: Artificial neural network model for optimizing operation of a seawater reverse osmosis desalination plant. Desalination 247(1–3), 180–189 (2009)
Yu, B.Y., de Weck, O., Yang, M.C.: Parameter design strategies: a comparison between human designers and the simulated annealing algorithm. In: ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, pp. V007T06A033–V007T06A033. American Society of Mechanical Engineers, August 2015
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Colmenar-Santos, A., Peñate-Vera, S., Rosales-Asensio, E. (2018). Sizing of Wind, Solar and Storage Facilities Associated to a Desalination Plant Using Stochastic Optimization. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Cybernetics Approaches in Intelligent Systems. CoMeSySo 2017. Advances in Intelligent Systems and Computing, vol 661. Springer, Cham. https://doi.org/10.1007/978-3-319-67618-0_16
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DOI: https://doi.org/10.1007/978-3-319-67618-0_16
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