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Imperial competitive algorithm optimization of fuzzy multi-objective design of a hybrid green power system with considerations for economics, reliability, and environmental emissions

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  • Gharavi, H.
  • Ardehali, M.M.
  • Ghanbari-Tichi, S.

Abstract

In addition to economics, reliability and environmental emissions are of great importance for designing a power generation system. The objective of this study is to optimally design an autonomous and non-autonomous hybrid green power system (HGPS) to supply a specific load demand with considerations for economics, reliability indices, and environmental emissions. The HGPS includes wind turbine (WT) units, photovoltaic (PV) arrays, electrolyzer and fuel cell (FC). The data used for simulation are actual annual solar irradiation and wind speed for the northwest region of Iran. For reliability analysis, it is assumed that WT, PV, DC/AC convertor, and electrical network can have failure in supplying power. Imperial competitive algorithm is utilized for optimization. To address different levels of importance for economics and environmental emission, fuzzy multi-objective problem formulation is used for non-autonomous HGPS. For the optimally designed non-autonomous HGPS, for maximum purchased power of 50 kW, based on current rates, the costs are 92.6% less than that of the autonomous HGPS, in exchange for 5778 tons of CO2 emissions. In general, it is determined that allowance for purchasing power results in lower overall efficiency of the non-autonomous HGPS.

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  • Gharavi, H. & Ardehali, M.M. & Ghanbari-Tichi, S., 2015. "Imperial competitive algorithm optimization of fuzzy multi-objective design of a hybrid green power system with considerations for economics, reliability, and environmental emissions," Renewable Energy, Elsevier, vol. 78(C), pages 427-437.
  • Handle: RePEc:eee:renene:v:78:y:2015:i:c:p:427-437
    DOI: 10.1016/j.renene.2015.01.029
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    1. Kashefi Kaviani, A. & Riahy, G.H. & Kouhsari, SH.M., 2009. "Optimal design of a reliable hydrogen-based stand-alone wind/PV generating system, considering component outages," Renewable Energy, Elsevier, vol. 34(11), pages 2380-2390.
    2. Lagorse, Jeremy & Paire, Damien & Miraoui, Abdellatif, 2009. "Sizing optimization of a stand-alone street lighting system powered by a hybrid system using fuel cell, PV and battery," Renewable Energy, Elsevier, vol. 34(3), pages 683-691.
    3. Garcia, Raquel S. & Weisser, Daniel, 2006. "A wind–diesel system with hydrogen storage: Joint optimisation of design and dispatch," Renewable Energy, Elsevier, vol. 31(14), pages 2296-2320.
    4. Elhadidy, M.a & Shaahid, S.M, 1999. "Optimal sizing of battery storage for hybrid (wind+diesel) power systems," Renewable Energy, Elsevier, vol. 18(1), pages 77-86.
    5. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa, 2010. "Optimization of capacity and operation for CCHP system by genetic algorithm," Applied Energy, Elsevier, vol. 87(4), pages 1325-1335, April.
    6. Ntziachristos, Leonidas & Kouridis, Chariton & Samaras, Zissis & Pattas, Konstantinos, 2005. "A wind-power fuel-cell hybrid system study on the non-interconnected Aegean islands grid," Renewable Energy, Elsevier, vol. 30(10), pages 1471-1487.
    7. Dihrab, Salwan S. & Sopian, K., 2010. "Electricity generation of hybrid PV/wind systems in Iraq," Renewable Energy, Elsevier, vol. 35(6), pages 1303-1307.
    8. Tichi, S.G. & Ardehali, M.M. & Nazari, M.E., 2010. "Examination of energy price policies in Iran for optimal configuration of CHP and CCHP systems based on particle swarm optimization algorithm," Energy Policy, Elsevier, vol. 38(10), pages 6240-6250, October.
    9. Nema, Pragya & Nema, R.K. & Rangnekar, Saroj, 2009. "A current and future state of art development of hybrid energy system using wind and PV-solar: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 2096-2103, October.
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