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Promotion strategy of clean technologies in distributed generation expansion planning

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  • Zangeneh, Ali
  • Jadid, Shahram
  • Rahimi-Kian, Ashkan

Abstract

Distributed generation expansion planning (DGEP) has been frequently reported in the literature around the world. In this scope, renewable technologies which are considered as a kind of distributed generations are developing due to their environmental benefits. However, only a few renewable energies have proven to be competitive so far, while their economic viability is also limited to certain regions of the world. In this paper, an encouraging mechanism is proposed in favor of clean technologies in the planning process. This mechanism is defined based on a grant function of emission not polluted which is paid to DG owners to promote renewable and clean technologies. In the planning process, a multi-objective optimization algorithm is applied to produce a Pareto set of optimal planning schemes by taking into account different objective functions (cost and grant functions). The best planning scheme among the Pareto set is chosen based on a composite utility which are obtained through a Monte Carlo simulation of uncertain situations. Distributed generation technologies which are considered in this paper are conventional and renewable technologies, namely photovoltaic (PV), wind turbine (WT), fuel cell (FC), micro turbine (MT), gas turbine (GT), and reciprocal engine (RE). To assess the ability of the proposed method, a typical distribution system is used for expansion planning under two environmental scenarios.

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  • Zangeneh, Ali & Jadid, Shahram & Rahimi-Kian, Ashkan, 2009. "Promotion strategy of clean technologies in distributed generation expansion planning," Renewable Energy, Elsevier, vol. 34(12), pages 2765-2773.
    • Handle: RePEc:eee:renene:v:34:y:2009:i:12:p:2765-2773
    DOI: 10.1016/j.renene.2009.06.018
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    6. Xiangyu Kong & Jingtao Yao & Zhijun E & Xin Wang, 2019. "Generation Expansion Planning Based on Dynamic Bayesian Network Considering the Uncertainty of Renewable Energy Resources," Energies, MDPI, vol. 12(13), pages 1-20, June.
    7. Zangeneh, Ali & Jadid, Shahram & Rahimi-Kian, Ashkan, 2011. "A fuzzy environmental-technical-economic model for distributed generation planning," Energy, Elsevier, vol. 36(5), pages 3437-3445.
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    10. Alarcon-Rodriguez, Arturo & Ault, Graham & Galloway, Stuart, 2010. "Multi-objective planning of distributed energy resources: A review of the state-of-the-art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(5), pages 1353-1366, June.
    11. Ho, W.S. & Hashim, H. & Hassim, M.H. & Muis, Z.A. & Shamsuddin, N.L.M., 2012. "Design of distributed energy system through Electric System Cascade Analysis (ESCA)," Applied Energy, Elsevier, vol. 99(C), pages 309-315.
    12. Ramirez-Rosado, Ignacio J. & Fernandez-Jimenez, L. Alfredo & Monteiro, Claudio & Garcia-Garrido, Eduardo & Zorzano-Santamaria, Pedro, 2011. "Spatial long-term forecasting of small power photovoltaic systems expansion," Renewable Energy, Elsevier, vol. 36(12), pages 3499-3506.
    13. Quiroga, Daniela & Sauma, Enzo & Pozo, David, 2019. "Power system expansion planning under global and local emission mitigation policies," Applied Energy, Elsevier, vol. 239(C), pages 1250-1264.
    14. Li, Tianxiao & Li, Zheng & Li, Weiqi, 2020. "Scenarios analysis on the cross-region integrating of renewable power based on a long-period cost-optimization power planning model," Renewable Energy, Elsevier, vol. 156(C), pages 851-863.
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    16. Soroudi, Alireza & Ehsan, Mehdi & Zareipour, Hamidreza, 2011. "A practical eco-environmental distribution network planning model including fuel cells and non-renewable distributed energy resources," Renewable Energy, Elsevier, vol. 36(1), pages 179-188.
    17. Rabiee, Abdorreza & Sadeghi, Mohammad & Aghaeic, Jamshid & Heidari, Alireza, 2016. "Optimal operation of microgrids through simultaneous scheduling of electrical vehicles and responsive loads considering wind and PV units uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 721-739.
    18. Abdmouleh, Zeineb & Gastli, Adel & Ben-Brahim, Lazhar & Haouari, Mohamed & Al-Emadi, Nasser Ahmed, 2017. "Review of optimization techniques applied for the integration of distributed generation from renewable energy sources," Renewable Energy, Elsevier, vol. 113(C), pages 266-280.
    19. Juroszek, Zbigniew & Kudelko, Mariusz, 2016. "A model of optimization for local energy infrastructure development," Energy, Elsevier, vol. 96(C), pages 625-643.
    20. Zangiabadi, Mansoureh & Feuillet, Rene & Lesani, Hamid & Hadj-Said, Nouredine & Kvaløy, Jan T., 2011. "Assessing the performance and benefits of customer distributed generation developers under uncertainties," Energy, Elsevier, vol. 36(3), pages 1703-1712.

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