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Optimal sizing and energy management of stand-alone hybrid photovoltaic/wind system based on hydrogen storage considering LOEE and LOLE reliability indices using flower pollination algorithm

机译:基于花粉传粉算法的LOEE和LOLE可靠性指标的基于储氢的独立混合光伏/风能系统的最佳尺寸和能量管理

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摘要

In this paper, the optimal design and energy management of the hybrid systems including the photovoltaic (PV) panels, wind turbine (WT) and fuel cell (FC) based on hydrogen storage (HS) (PWFHS) are presented to minimize the total net present cost (TNPC) of northwest region of Iran using intelligent flower pollination algorithm (FPA). The reliability indices that are considered simultaneously as technical constraints are the loss of energy expected (LOEE) and the loss of load expected (LOLE). The FPA performance is compared with well-known optimization methods such as teaching-learning based optimization (TLBO), particle swarm optimization (PSO) and also last researches in hybrid renewable energy designing. The simulation results are presented including decision variables, TNPC, LOEE, LOLE, energy management of generation units in different LOLEmax and LOEEmax and different combination of PWFHS. The results show that the proposed methodology finds the optimal decision variables easily with fast convergence, lower cost and better reliability values in different reliability indices and different PWFHS in comparison to TLBO and PSO. (C) 2018 Elsevier Ltd. All rights reserved.
机译:在本文中,提出了基于氢存储(HS)(PWFHS)的包括光伏(PV)面板,风力涡轮机(WT)和燃料电池(FC)在内的混合系统的优化设计和能量管理,以最大程度地减少总净发电量。使用智能花授粉算法(FPA)的伊朗西北地区的当前成本(TNPC)。同时被视为技术约束的可靠性指标是预期的能量损失(LOEE)和预期的负载损失(LOLE)。将FPA的性能与著名的优化方法(例如基于教学的优化(TLBO),粒子群优化(PSO))以及混合可再生能源设计的最新研究进行了比较。给出了仿真结果,包括决策变量,TNPC,LOEE,LOLE,不同LOLEmax和LOEEmax中的发电单元的能量管理以及PWFHS的不同组合。结果表明,与TLBO和PSO相比,在不同的可靠性指标和不同的PWFHS下,所提出的方法易于找到收敛速度更快,成本更低,可靠性更高的最优决策变量。 (C)2018 Elsevier Ltd.保留所有权利。

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