Skip to main content

Advertisement

Log in

Optimal Design of Hybrid Renewable Energy System for a Reverse Osmosis Desalination System in Arar, Saudi Arabia

  • Research Article-Electrical Engineering
  • Published:
Arabian Journal for Science and Engineering Aims and scope Submit manuscript

Abstract

Saudi Arabia tries to build local desalination water stations to supply water to remote areas. Due to the low cost and energy requirements of reverse osmosis (RO) desalination technology, it has been used to supply fresh water to Arar City in the northeast of Saudi Arabia. In this paper, it is proposed to provide an average of 1000 cubic meters of water per day by using autonomous hybrid renewable energy system (RES). This proposed system contains wind turbines (WTs), photovoltaic (PV), battery, and it is designed to feed the RO system with the energy adequate to produce the required amount of fresh water for the minimum cost and minimum loss of supply probability. The proposed system was designed to generate 2440 kW power to produce this amount of water. Matching study between the site and the best WT among 10 market-available WTs is introduced. Three optimization strategies were used and compared for the design of the proposed system to ensure that no premature convergence can occur. These strategies consisted of two well-known techniques, particle swarm optimization and bat algorithm (BA), and a relatively new technique: social mimic optimization. The simulation results obtained from the proposed system showed the superiority of using a RES for feeding a RO desalination power plant in Arar City, and they also showed that the BA is the fastest and most accurate optimization technique to perform this design problem compared with the other two optimization techniques. This detailed analysis shows that the cost of production of fresh water is $0.745/m3.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. Kyriakarakos, G.; Dounis, A.I.; Arvanitis, K.G.; Papadakis, G.: Design of a Fuzzy Cognitive Maps variable-load energy management system for autonomous PV-reverse osmosis desalination systems: a simulation survey. Appl. Energy 187, 575–584 (2017)

    Article  Google Scholar 

  2. Koutroulis, E.; Kolokotsa, D.: Design optimization of desalination systems power-supplied by PV and W/G energy sources. Desalination 258(1–3), 171–181 (2010)

    Article  Google Scholar 

  3. de la Nuez-Pestana, I.; Latorre, F.J.G.; Espinoza, C.A.; Gotor, A.G.: Optimization of RO desalination systems powered by renewable energies. Part I: wind energy. Desalination 160(3), 293–299 (2004)

    Article  Google Scholar 

  4. Soric, A.; Césaro, R.; Perez, P.; Guiol, E.; Moulin, P.: Eausmose project desalination by reverse osmosis and batteryless solar energy: design for a 1 m3 per day delivery. Desalination 301, 67–74 (2012)

    Article  Google Scholar 

  5. Kumarasamy, S.; Narasimhan, S.; Narasimhan, S.: Optimal operation of battery-less solar powered reverse osmosis plant for desalination. Desalination 375, 89–99 (2015)

    Article  Google Scholar 

  6. Laborde, H.M.; Franca, K.B.; Neff, H.; Lima, A.M.N.: Optimization strategy for a small-scale reverse osmosis water desalination system based on solar energy. Desalination 133(1), 1–12 (2001)

    Article  Google Scholar 

  7. Eltamaly, A.M.; Addoweesh, K.E.; Bawa, U.; Mohamed, M.A.: Economic modeling of hybrid renewable energy system: a case study in Saudi Arabia. Arab. J. Sci. Eng. 39(5), 3827–3839 (2014)

    Article  Google Scholar 

  8. Wenceslas, K.Y.; Ghislain, T.: Experimental validation of exergy optimization of a flat-plate solar collector in a thermosyphon solar water heater. Arab. J. Sci. Eng. 44(3), 2535–2549 (2019)

    Article  Google Scholar 

  9. Ra’ad, K.: An innovative receiver design for a parabolic trough solar collector using overlapped and reverse flow: an experimental study. Arab. J. Sci. Eng. 44(9), 7529–7539 (2019)

    Article  Google Scholar 

  10. Ali, E.; Bumazza, M.; Eltamaly, A.; Mulyono, S.; Yasin, M.: Optimization of wind driven RO plant for brackish water desalination during wind speed fluctuation with and without battery. Membranes 11(2), 77 (2021)

    Article  Google Scholar 

  11. Azarpour, A.; Suhaimi, S.; Zahedi, G.; Bahadori, A.: A review on the drawbacks of renewable energy as a promising energy source of the future. Arab. J. Sci. Eng. 38(2), 317–328 (2013)

    Article  Google Scholar 

  12. Maleki, A.: Design and optimization of autonomous solar-wind-reverse osmosis desalination systems coupling battery and hydrogen energy storage by an improved bee algorithm. Desalination 435, 221–234 (2018)

    Article  Google Scholar 

  13. Mohamed, M.A.; Eltamaly, A.M.; Alolah, A.I.; Hatata, A.Y.: A novel framework-based cuckoo search algorithm for sizing and optimization of grid-independent hybrid renewable energy systems. Int. J. Green Energy 16(1), 86–100 (2019)

    Article  Google Scholar 

  14. Naseri, A.; Bidi, M.; Ahmadi, M.H.; Saidur, R.: Exergy analysis of a hydrogen and water production process by a solar-driven transcritical CO2 power cycle with Stirling engine. J. Clean. Prod. 158, 165–181 (2017)

    Article  Google Scholar 

  15. Eltamaly, A.M.; Al-Saud, M.S.: Nested multi-objective PSO for optimal allocation and sizing of renewable energy distributed generation. J. Renew. Sustain. Energy 10(3), 035302 (2018)

    Article  Google Scholar 

  16. Mohamed, M.A.; Eltamaly, A.M.: Modeling of hybrid renewable energy system. In: Modeling and Simulation of Smart Grid Integrated with Hybrid Renewable Energy Systems, pp. 11–21. Springer, Cham (2018)

  17. Tzen, E.; Perrakis, K.; Baltas, P.: Design of a stand alone PV-desalination system for rural areas. Desalination 119(1–3), 327–333 (1998)

    Article  Google Scholar 

  18. Keeper, B.G.; Hembree, R.D.; Schrack, F.C.: Optimized matching of solar photovoltaic power with reverse osmosis desalination. Desalination 54, 89–103 (1985)

    Article  Google Scholar 

  19. Voivontas, D.; Misirlis, K.; Manoli, E.; Arampatzis, G.; Assimacopoulos, D.: A tool for the design of desalination plants powered by renewable energies. Desalination 133(2), 175–198 (2001)

    Article  Google Scholar 

  20. Asayesh, M.; Kasaeian, A.; Ataei, A.: Optimization of a combined solar chimney for desalination and power generation. Energy Convers. Manag. 150(2017), 72–80 (2017)

    Article  Google Scholar 

  21. García-Triviño, P.; Llorens-Iborra, F.; García-Vázquez, C.A.; Gil-Mena, A.J.; Fernández-Ramírez, L.M.; Jurado, F.: Long-term optimization based on PSO of a grid-connected renewable energy/battery/hydrogen hybrid system. Int. J. Hydrogen Energy 39(21), 10805–10816 (2014)

    Article  Google Scholar 

  22. Eltamaly, A.M.; Mohamed, M.A.: Optimal sizing and designing of hybrid renewable energy systems in smart grid applications. In: Advances in Renewable Energies and Power Technologies, pp. 231–313. Elsevier (2018)

  23. Ismail, M.S.; Moghavvemi, M.; Mahlia, T.M.I.: Genetic algorithm based optimization on modeling and design of hybrid renewable energy systems. Energy Convers. Manag. 85, 120–130 (2014)

    Article  Google Scholar 

  24. Ko, M.J.; Kim, Y.S.; Chung, M.H.; Jeon, H.C.: Multi-objective optimization design for a hybrid energy system using the genetic algorithm. Energies 8(4), 2924–2949 (2015)

    Article  Google Scholar 

  25. Ekren, O.; Ekren, B.Y.: Size optimization of a PV/wind hybrid energy conversion system with battery storage using simulated annealing. Appl. Energy 87(2), 592–598 (2010)

    Article  Google Scholar 

  26. Yahiaoui, A.; Fodhil, F.; Benmansour, K.; Tadjine, M.; Cheggaga, N.: Grey wolf optimizer for optimal design of hybrid renewable energy system PV-Diesel Generator-Battery: application to the case of Djanet city of Algeria. Sol. Energy 158, 941–951 (2017)

    Article  Google Scholar 

  27. Abdelshafy, A.M.; Hassan, H.; Jurasz, J.: Optimal design of a grid-connected desalination plant powered by renewable energy resources using a hybrid PSO–GWO approach. Energy Convers. Manag. 173, 331–347 (2018)

    Article  Google Scholar 

  28. Yang, X.-S.: A new metaheuristic bat-inspired algorithm. In: Nature Inspired Cooperative Strategies for Optimization, pp. 65–74. Springer, Berlin, Heidelberg (2010)

  29. Eltamaly, A.M.; Al-Saud, M.S.; Abokhalil, A.G.: A novel bat algorithm strategy for maximum Power Point tracker of photovoltaic energy systems under dynamic partial shading. IEEE Access 8, 10048–10060 (2020)

    Article  Google Scholar 

  30. Eltamaly, A.M.; Al-Saud, M.S.; Abokhalil, A.G.: A novel scanning bat algorithm strategy for maximum power point tracker of partially shaded photovoltaic energy systems. Ain Shams Eng. J. 11(4), 1093–1103 (2020)

    Article  Google Scholar 

  31. Balochian, S.; Baloochian, H.: Social mimic optimization algorithm and engineering applications. Expert Syst. Appl. 134, 178–191 (2019)

    Article  Google Scholar 

  32. Eltamaly, A.M.; Alotaibi, M.A.; Alolah, A.I.; Ahmed, M.A.: A novel demand response strategy for sizing of hybrid energy system with smart grid concepts. IEEE Access 9, 20277–20294 (2021)

    Article  Google Scholar 

  33. Eltamaly, A.M.: Design and implementation of wind energy system in Saudi Arabia. Renew. Energy 60, 42–52 (2013)

    Article  Google Scholar 

  34. Stevens, M.J.M.; Smulders, P.T.: The estimation of the parameters of the Weibull wind speed distribution for wind energy utilization purposes. Wind Eng. 3, 132–145 (1979)

    Google Scholar 

  35. Eltamaly, A.M.: Pairing between sites and wind turbines for Saudi Arabia Sites. Arab. J. Sci. Eng. 39(8), 6225–6233 (2014)

    Article  Google Scholar 

  36. Skoplaki, E.; Boudouvis, A.G.; Palyvos, J.A.: A simple correlation for the operating temperature of photovoltaic modules of arbitrary mounting. Sol. Energy Mater. Sol. Cells 92(11), 1393–1402 (2008)

    Article  Google Scholar 

  37. Kaabeche, A.; Belhamel, M.; Ibtiouen, R.: Optimal sizing method for stand-alone hybrid PV/wind power generation system. Revue des Energies Renouvelables (SMEE'10) Bou Ismail Tipaza 205–213 (2010)@@

  38. Yang, H.; Zhou, W.; Lu, L.; Fang, Z.: Optimal sizing method for stand-alone hybrid solar–wind system with LPSP technology by using genetic algorithm. Sol. Energy 82(4), 354–367 (2008)

    Article  Google Scholar 

  39. Dashtpour, R.; Al-Zubaidy, S.N.: Energy efficient reverse osmosis desalination process. Int. J. Environ. Sci. Dev. 3(4), 339 (2012)

    Google Scholar 

  40. Eltamaly, A.M.; Mohamed, M.A.: A novel design and optimization software for autonomous PV/wind/battery hybrid power systems. Math. Probl. Eng. 2014, 16 (2014)

    Article  Google Scholar 

  41. Awan, A.B.; Zubair, M.; Sidhu, G.A.S.; Bhatti, A.R.; Abo-Khalil, A.G.: Performance analysis of various hybrid renewable energy systems using battery, hydrogen, and pumped hydro-based storage units. Int. J. Energy Res. 43(12), 6296–6321 (2019)

    Article  Google Scholar 

  42. Zhang, W.; Maleki, A.; Rosen, M.A.; Liu, J.: Sizing a stand-alone solar-wind-hydrogen energy system using weather forecasting and a hybrid search optimization algorithm. Energy Convers. Manag. 180, 609–621 (2019)

    Article  Google Scholar 

  43. Monforti Ferrario, A.; Vivas, F.J.; Segura Manzano, F.; Andújar, J.M.; Bocci, E.; Martirano, L.: Hydrogen vs. battery in the long-term operation. A comparative between energy management strategies for hybrid renewable microgrids. Electronics 9(4), 698 (2020)

    Article  Google Scholar 

  44. Lazou, A.A.; Papatsoris, A.D.: The economics of photovoltaic stand-alone residential households: a case study for various European and Mediterranean locations. Sol. Energy Mater. Sol. Cells 62(4), 411–427 (2000)

    Article  Google Scholar 

  45. Diaf, S.; Belhamel, M.; Haddadi, M.; Louche, A.: Technical and economic assessment of hybrid photovoltaic/wind system with battery storage in Corsica island. Energy Policy 36(2), 743–754 (2008)

    Article  Google Scholar 

  46. Bazyar, R.; Valipoor, Kh.; Javadi, M.R.; Valizade, M.; Kord, H.: Optimal design and energy management of stand-alone wind/PV/diesel/battery using bacterial foraging algorithm. In: 8th International Energy Conference, vol. 1, pp. 1–14 (2011)

  47. Eltamaly, A.M.: New software for matching between wind sites and wind turbines. In: Control and Operation of Grid-Connected Wind Energy Systems, pp. 275–317 (2021)

  48. Eltamaly, A.M.; Mohamed, A.M.: A novel software for design and optimization of hybrid power systems. J. Braz. Soc. Mech. Sci. Eng. 38(4), 1299–1315 (2016)

    Article  Google Scholar 

  49. Kennedy, J.; Eberhart, R.: Particle swarm optimization. In: Proceedings of ICNN'95-International Conference on Neural Networks, vol. 4, pp. 1942–1948. IEEE (1995)

  50. Jakubcová, M.; Máca, P.; Pech, P.: A comparison of selected modifications of the particle swarm optimization algorithm. J. Appl. Math. 2014, 1–10 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  51. Eltamaly, A.M.: A novel strategy for optimal PSO control parameters determination for PV energy systems. Sustainability 13(2), 1008 (2021)

    Article  Google Scholar 

  52. Ramli, M.A.; Twaha, S.; Al-Hamouz, Z.: Analyzing the potential and progress of distributed generation applications in Saudi Arabia: the case of solar and wind resources. Renew. Sustain. Energy Rev. 70, 287–297 (2017)

    Article  Google Scholar 

  53. https://re.jrc.ec.europa.eu/pvg_tools/en/tools.html#TMY

  54. https://en.wind-turbine-models.com/turbines/1026-ae-italia-stoma-st-k60-d21

  55. https://en.wind-turbine-models.com/turbines/812-ades-ades-60

  56. https://en.wind-turbine-models.com/turbines/1682-hummer-h25.0-100kw

  57. http://www.neicjapan.com/smallwindmill/Aeolos-H%20100kW%20Brochure.pdf

  58. https://www.norvento.com/en/for-large-companies/

  59. https://en.wind-turbine-models.com/turbines/859-aircon-10s

  60. https://en.wind-turbine-models.com/turbines/1829-aeolia-windtech-d2cf-200

  61. https://en.wind-turbine-models.com/turbines/956-air-19-100

  62. https://en.wind-turbine-models.com/turbines/144-allgaier-stgw-34

  63. https://en.wind-turbine-models.com/turbines/1876-dencon-tornado-200-26

  64. Maleki, A.; Pourfayaz, F.; Rosen, M.A.: A novel framework for optimal design of hybrid renewable energy-based autonomous energy systems: a case study for Namin, Iran. Energy 98, 168–180 (2016)

    Article  Google Scholar 

  65. Askarzadeh, A.; dos Santos Coelho, L.: A novel framework for optimization of a grid independent hybrid renewable energy system: a case study of Iran. Sol. Energy 112, 383–396 (2015)

    Article  Google Scholar 

  66. Maleki, A.; Pourfayaz, F.; Ahmadi, M.H.: Design of a cost-effective wind/photovoltaic/hydrogen energy system for supplying a desalination unit by a heuristic approach. Sol. Energy 139, 666–675 (2016)

    Article  Google Scholar 

  67. Caldera, U.; Bogdanov, D.; Breyer, C.: Local cost of seawater RO desalination based on solar PV and wind energy: a global estimate. Desalination 385, 207–216 (2016)

    Article  Google Scholar 

  68. Mukhtaruddin, R.N.S.R.; Rahman, H.A.; Hassan, M.Y.; Jamian, J.J.: Optimal hybrid renewable energy design in autonomous system using Iterative-Pareto-Fuzzy technique. Int. J. Electr. Power Energy Syst. 64, 242–249 (2015)

    Article  Google Scholar 

  69. Maleki, A.; Khajeh, M.G.; Rosen, M.A.: Weather forecasting for optimization of a hybrid solar-wind–powered reverse osmosis water desalination system using a novel optimizer approach. Energy 114, 1120–1134 (2016)

    Article  Google Scholar 

  70. Sanchez, V.M.; Chavez-Ramirez, A.U.; Duron-Torres, S.M.; Hernandez, J.; Arriaga, L.G.; Ramirez, J.M.: Techno-economical optimization based on swarm intelligence algorithm for a stand-alone wind-photovoltaic-hydrogen power system at south-east region of Mexico. Int. J. Hydrogen Energy 39(29), 16646–16655 (2014)

    Article  Google Scholar 

  71. Xu, D.; Acker, T.; Zhang, X.: Size optimization of a hybrid PV/wind/diesel/battery power system for reverse osmosis desalination. J. Water Reuse Desalin. 9(4), 405–422 (2019)

    Article  Google Scholar 

  72. Esfahani, I.J.; Yoo, C.: An optimization algorithm-based pinch analysis and GA for an off-grid batteryless photovoltaic-powered reverse osmosis desalination system. Renew. Energy 91, 233–248 (2016)

    Article  Google Scholar 

  73. Atallah, M.O.; Farahat, M.A.; Lotfy, M.E.; Senjyu, T.: Operation of conventional and unconventional energy sources to drive a reverse osmosis desalination plant in Sinai Peninsula, Egypt. Renew. Energy 145, 141–152 (2020)

    Article  Google Scholar 

Download references

Acknowledgements

This study was funded by the National Plan for Science, Technology, and Innovation (MAARIFAH), King Abdulaziz City for Science and Technology, Kingdom of Saudi Arabia (13-WAT907-02).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ali M. Eltamaly.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Eltamaly, A.M., Ali, E., Bumazza, M. et al. Optimal Design of Hybrid Renewable Energy System for a Reverse Osmosis Desalination System in Arar, Saudi Arabia. Arab J Sci Eng 46, 9879–9897 (2021). https://doi.org/10.1007/s13369-021-05645-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13369-021-05645-0

Keywords

Navigation