Optimization of hydrogen based hybrid renewable energy system using HOMER, BB-BC and GAMBIT

Khare, Vikas; Nema, Savita; Baredar, Prashant

doi:10.1016/j.ijhydene.2016.06.228

Cited by 86 publications

(12 citation statements)

References 21 publications

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“…Capital cost for the hydrogen tank was based on the mass production of the system. The economic assumptions for electrolyser, hydrogen tank, and fuel Cell have been taken from recently published reports by other researchers [47,[61][62][63]. However, the cost for hydrogen storage may further decrease in years to come, and particularly in storage applications as large as that considered for this case study.…”

Section: Hybrid Battery-hydrogen Storage Systemmentioning

confidence: 99%

Hydrogen as a Long-Term Large-Scale Energy Storage Solution to Support Renewables

2018

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This paper presents a case study of using hydrogen for large-scale long-term storage application to support the current electricity generation mix of South Australia state in Australia, which primarily includes gas, wind and solar. For this purpose two cases of battery energy storage and hybrid battery-hydrogen storage systems to support solar and wind energy inputs were compared from a techno-economical point of view. Hybrid battery-hydrogen storage system was found to be more cost competitive with unit cost of electricity at $0.626/kWh (US dollar) compared to battery-only energy storage systems with a $2.68/kWh unit cost of electricity. This research also found that the excess stored hydrogen can be further utilised to generate extra electricity. Further utilisation of generated electricity can be incorporated to meet the load demand by either decreasing the base load supply from gas in the present scenario or exporting it to neighbouring states to enhance economic viability of the system. The use of excess stored hydrogen to generate extra electricity further reduced the cost to $0.494/kWh.

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Section: Hybrid Battery-hydrogen Storage Systemmentioning

confidence: 99%

Hydrogen as a Long-Term Large-Scale Energy Storage Solution to Support Renewables

2018

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“…Khare et al applied HOMER, BIG BANG CRUNCH and game theory in a renewable energy system. They found that replacing conventional energy sources by solar-wind-fuel cell-hydrogen tank energy system was an effective method for distributing electric power [42]. In order to develop a reliable decision support system, a two-side multi-agent based modeling framework using a hybrid simulation approach of game theory and Particle Swarm Optimization was put forward in [43].…”

Section: Application Of Game Theory In Hybrid Power System Planningmentioning

confidence: 99%

Profit Allocation of Hybrid Power System Planning in Energy Internet: A Cooperative Game Study

Liu

2018

Sustainability

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Abstract:The rapid development of Energy Internet (EI) has prompted numbers of generators to participate, leading to a hybrid power system. Hence, how to plan the hybrid power system and allocate its profit becomes necessary. In this paper, the cooperative game theory is introduced to discuss this problem. We first design the basic structure of EI, and point out the object of this study-coal power plant-wind farm-photovoltaic power station-energy storage provider (CWPE) alliance. Subsequently, average allocation strategy (AAS), capacity-based allocation strategy (CAS) and Shapley value allocation strategy (SAS) are proposed, and then the modified disruption propensity (MDP) index is constructed to judge the advantages and disadvantages of the three schemes. Thirdly, taking a certain area of A Province as an example, the profits of CWPE under three strategies are calculated respectively. Finally, by analyzing individual rationality and collective rationality of cooperative game and the MDP index of the three profit allocation schemes, we find that SAS is the most stable.

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“…Several cost functions are defined in the literature: energy cost (COE) [5], total net system cost (TNPC or NPC) [6], levelized cost of energy (LCOE) [4], annualized cost of the system (ACS) [2]. Among these cost functions, the cost of energy (COE) and total net cost (TNPC) are the most effective indicators of profitability in the economic analysis [7].…”

Section: Introductionmentioning

confidence: 99%

Sizing Optimization of a Charging Station Based on the Multi-scale Current Profile and Particle Swarm Optimization: Application to Power-assisted Bikes

Nkounga

Ndiaye²,

Ndiaye³

et al. 2021

2021 Sixteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)

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The development of power-assisted bikes (ebike) is of growing interest because of their economic and environmental advantages. The present work deals with the sizing optimization of a charging station for ebike based on particle swarm optimization. It is based on the consumption profile of ebike batteries, solar and wind power, installation, replacement and maintenance costs of components. In a first step, the consumption profile of the ebike batteries is determined using the second order non-linear electrothermal model. Then, the solar and wind data over one year are used to determine the availability of energy at the implementation site of the charging station. Finally, the cost is defined as an objective function, taking into account the constraints on the number of solar photovoltaic panels, the number of wind turbines, the number of storage batteries and the annual charging demand. The context of a charging station to be implemented in the Polytech Annecy campus in France is studied. The results show that the particle swarm optimization allows a cost reduction of around 56.04% compared to a sizing without optimization.

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Optimization of hydrogen based hybrid renewable energy system using HOMER, BB-BC and GAMBIT

Cited by 86 publications

References 21 publications

Hydrogen as a Long-Term Large-Scale Energy Storage Solution to Support Renewables

Hydrogen as a Long-Term Large-Scale Energy Storage Solution to Support Renewables

Profit Allocation of Hybrid Power System Planning in Energy Internet: A Cooperative Game Study

Sizing Optimization of a Charging Station Based on the Multi-scale Current Profile and Particle Swarm Optimization: Application to Power-assisted Bikes

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