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Weather forecasting for optimization of a hybrid solar-wind–powered reverse osmosis water desalination system using a novel optimizer approach

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  • Maleki, Akbar
  • Khajeh, Morteza Gholipour
  • Rosen, Marc A.

Abstract

The optimum design for a stand-alone hybrid desalination scheme, able to fulfill the fresh water demand of a remote area located in Davarzan, Khorasan, Iran, is determined and investigated. The scheme consists of a reverse-osmosis desalination unit powered by solar and wind electricity production systems with battery energy storage. To predict the energy production, data from many weather stations are required, and a new forecasting strategy is proposed for weather related parameters (solar irradiance, wind speed, and ambient temperature). The system is implemented and tested using real data from northeastern Iran. To determine the optimal values of parameters for the hybrid renewable energy system that satisfy the load in the most cost-effective way (minimizing the life cycle cost and not exceeding the maximum allowable loss of power supply probability), the use of harmony search and a combination of harmony search with chaotic search is proposed. As an efficient heuristic, harmony search is easy to implement and can escape from local optima. The decision variables (number of batteries, total swept area of the rotating turbine blades, and total area occupied by the set of photovoltaic panels) are optimized using a harmony search-based chaotic search for the most cost-effective system.

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  • Maleki, Akbar & Khajeh, Morteza Gholipour & Rosen, Marc A., 2016. "Weather forecasting for optimization of a hybrid solar-wind–powered reverse osmosis water desalination system using a novel optimizer approach," Energy, Elsevier, vol. 114(C), pages 1120-1134.
    • Handle: RePEc:eee:energy:v:114:y:2016:i:c:p:1120-1134
    DOI: 10.1016/j.energy.2016.06.134
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    Cited by:

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    5. Lee, Sangkeum & Cho, Hong-Yeon & Har, Dongsoo, 2018. "Operation optimization with jointly controlled modules powered by hybrid energy source: A case study of desalination," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 3070-3080.
    6. Zhang, Weiping & Maleki, Akbar, 2022. "Modeling and optimization of a stand-alone desalination plant powered by solar/wind energies based on back-up systems using a hybrid algorithm," Energy, Elsevier, vol. 254(PC).
    7. Schallenberg-Rodríguez, Julieta & Del Rio-Gamero, Beatriz & Melian-Martel, Noemi & Lis Alecio, Tyrone & González Herrera, Javier, 2020. "Energy supply of a large size desalination plant using wave energy. Practical case: North of Gran Canaria," Applied Energy, Elsevier, vol. 278(C).
    8. Mito, Mohamed T. & Ma, Xianghong & Albuflasa, Hanan & Davies, Philip A., 2019. "Reverse osmosis (RO) membrane desalination driven by wind and solar photovoltaic (PV) energy: State of the art and challenges for large-scale implementation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 669-685.
    9. Ewaoche John Okampo & Nnamdi Nwulu & Pitshou N. Bokoro, 2022. "Economic and Reliability Assessment of Hybrid PRO-RO Desalination Systems Using Brine for Salinity Gradient Energy Production," Sustainability, MDPI, vol. 14(6), pages 1-16, March.
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    12. Weinand, Jann Michael & Scheller, Fabian & McKenna, Russell, 2020. "Reviewing energy system modelling of decentralized energy autonomy," Energy, Elsevier, vol. 203(C).
    13. Okampo, Ewaoche John & Nwulu, Nnamdi, 2021. "Optimisation of renewable energy powered reverse osmosis desalination systems: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    14. Elena Sosnina & Andrey Dar’enkov & Andrey Kurkin & Ivan Lipuzhin & Andrey Mamonov, 2022. "Review of Efficiency Improvement Technologies of Wind Diesel Hybrid Systems for Decreasing Fuel Consumption," Energies, MDPI, vol. 16(1), pages 1-38, December.
    15. Duan, Jikai & Chang, Mingheng & Chen, Xiangyue & Wang, Wenpeng & Zuo, Hongchao & Bai, Yulong & Chen, Bolong, 2022. "A combined short-term wind speed forecasting model based on CNN–RNN and linear regression optimization considering error," Renewable Energy, Elsevier, vol. 200(C), pages 788-808.
    16. Sk. A. Shezan & Innocent Kamwa & Md. Fatin Ishraque & S. M. Muyeen & Kazi Nazmul Hasan & R. Saidur & Syed Muhammad Rizvi & Md Shafiullah & Fahad A. Al-Sulaiman, 2023. "Evaluation of Different Optimization Techniques and Control Strategies of Hybrid Microgrid: A Review," Energies, MDPI, vol. 16(4), pages 1-30, February.
    17. Obara, Shin'ya & Ito, Yuji & Okada, Masaki, 2018. "Optimization algorithm for power-source arrangement that levels the fluctuations in wide-area networks of renewable energy," Energy, Elsevier, vol. 142(C), pages 447-461.
    18. Ariana M. Pietrasanta & Mostafa F. Shaaban & Pio A. Aguirre & Sergio F. Mussati & Mohamed A. Hamouda, 2023. "Simulation and Optimization of Renewable Energy-Powered Desalination: A Bibliometric Analysis and Highlights of Recent Research," Sustainability, MDPI, vol. 15(12), pages 1-28, June.
    19. Alfonso Angel Medina-Santana & Leopoldo Eduardo Cárdenas-Barrón, 2022. "Optimal Design of Hybrid Renewable Energy Systems Considering Weather Forecasting Using Recurrent Neural Networks," Energies, MDPI, vol. 15(23), pages 1-28, November.
    20. Jahangir, Mohammad Hossein & Fakouriyan, Samaneh & Vaziri Rad, Mohammad Amin & Dehghan, Hassan, 2020. "Feasibility study of on/off grid large-scale PV/WT/WEC hybrid energy system in coastal cities: A case-based research," Renewable Energy, Elsevier, vol. 162(C), pages 2075-2095.

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