2020
DOI: 10.3390/en13051295
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Cost Optimization of a Stand-Alone Hybrid Energy System with Fuel Cell and PV

Abstract: Renewable energy has become very popular in recent years. The amount of renewable generation has increased in both grid-connected and stand-alone systems. This is because it can provide clean energy in a cost-effective and environmentally friendly fashion. Among all varieties, photovoltaic (PV) is the ultimate rising star. Integration of other technologies with solar is enhancing the efficiency and reliability of the system. In this paper a fuel cell–solar photovoltaic (FC-PV)-based hybrid energy system has be… Show more

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Cited by 71 publications
(15 citation statements)
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References 24 publications
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“…In [25], the authors carried out a cost analysis of the PV-El-FC system using the HOMER tool. The study was done by analyzing the impact of the dimensions of individual elements of the system, e.g., electrolyzer and PV installation, on the LCOE (levelized cost of electricity) cost index.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In [25], the authors carried out a cost analysis of the PV-El-FC system using the HOMER tool. The study was done by analyzing the impact of the dimensions of individual elements of the system, e.g., electrolyzer and PV installation, on the LCOE (levelized cost of electricity) cost index.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In case of excess of power, batteries can store energy and distribute energy in the event of an oversupply of energy demand. The battery or wind driven system can be integrated with the hybrid system [7], [8]. The hybrid system removes the fluctuation in supply, deficient in production by primary sources.…”
Section: Introductionmentioning
confidence: 99%
“…Nature-inspired optimization algorithms have become popular for solving different control and stability issues caused by increased renewable use [6]. These include frequency stability [7,8], cost optimization [9], energy management [10] and storage optimization [11,12]. Following this trend, reference [13] presents an adaptive artificial neural network-based modified particle swarm optimization (PSO) algorithm to optimize the real-time congestion control in a power system.…”
Section: Introductionmentioning
confidence: 99%