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Optimization of a hybrid diesel-wind generation plant with operational options

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  • Hu, Yu
  • Solana, Pablo

Abstract

Hybrid diesel-wind power generation systems have a great potential in the application of providing energy supply for remote communities and facilities. Compared to the traditional diesel system, hybrid power plants can offer many advantages such as additional capacity, being more environmentally friendly, potential reduction of cost, etc. One of the problems for the hybrid system is the uncertain profit due to the uncertain nature of the wind. In this paper a general model is presented based on real option theory for valuating a hybrid diesel-wind generation plant. A dynamic programming method is used to generate the optimum operational option by maximizing the net cash flow of the plant. Results show that operational options can provide additional value to the hybrid power system when this operational flexibility is correctly utilized. The optimal scale of wind turbines generators (WTGs) can be calculated as a consequence of the limitation of demand and local wind power density. This paper also provides a framework to find the optimal operating decision at each time step based on the real option model.

Suggested Citation

  • Hu, Yu & Solana, Pablo, 2013. "Optimization of a hybrid diesel-wind generation plant with operational options," Renewable Energy, Elsevier, vol. 51(C), pages 364-372.
    • Handle: RePEc:eee:renene:v:51:y:2013:i:c:p:364-372
    DOI: 10.1016/j.renene.2012.10.005
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    5. Kusakana, Kanzumba, 2014. "Techno-economic analysis of off-grid hydrokinetic-based hybrid energy systems for onshore/remote area in South Africa," Energy, Elsevier, vol. 68(C), pages 947-957.
    6. Kusakana, Kanzumba, 2015. "Operation cost minimization of photovoltaic–diesel–battery hybrid systems," Energy, Elsevier, vol. 85(C), pages 645-653.
    7. González, Arnau & Riba, Jordi-Roger & Rius, Antoni & Puig, Rita, 2015. "Optimal sizing of a hybrid grid-connected photovoltaic and wind power system," Applied Energy, Elsevier, vol. 154(C), pages 752-762.
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    9. Abdelkader, Abbassi & Rabeh, Abbassi & Mohamed Ali, Dami & Mohamed, Jemli, 2018. "Multi-objective genetic algorithm based sizing optimization of a stand-alone wind/PV power supply system with enhanced battery/supercapacitor hybrid energy storage," Energy, Elsevier, vol. 163(C), pages 351-363.
    10. Vu, Ba Hau & Chung, Il-Yop, 2022. "Optimal generation scheduling and operating reserve management for PV generation using RNN-based forecasting models for stand-alone microgrids," Renewable Energy, Elsevier, vol. 195(C), pages 1137-1154.
    11. Nunes, Luis Eduardo & Lima, Marcus Vinicius Andrade de & Davison, Matthew & Leite, André Luis da Silva, 2021. "Switch and defer option in renewable energy projects: Evidences from Brazil," Energy, Elsevier, vol. 231(C).
    12. Mohamed, Mohamed A. & Eltamaly, Ali M. & Alolah, Abdulrahman I., 2017. "Swarm intelligence-based optimization of grid-dependent hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 515-524.
    13. Rahimi, Ehsan & Rabiee, Abdorreza & Aghaei, Jamshid & Muttaqi, Kashem M. & Esmaeel Nezhad, Ali, 2013. "On the management of wind power intermittency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 643-653.
    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. Rediske, G. & Burin, H.P. & Rigo, P.D. & Rosa, C.B. & Michels, L. & Siluk, J.C.M., 2021. "Wind power plant site selection: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
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