Hydrogen infrastructure strategic planning using multi-objective optimization

Hugo, A.; Rutter, Paul D.; Pistikopoulos, Stratos; Amorelli, Angelo; Zoia, Giorgio

doi:10.1016/j.ijhydene.2005.04.017

Cited by 167 publications

(68 citation statements)

References 8 publications

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“…Assuming that each driver represents one vehicle, the fleet of vehicles supported by the UCI station averaged 30. 4 respectively. This matches well to daily hydrogen consumption estimates used in the literature [13,17].…”

Section: Station Configurationmentioning

confidence: 98%

Quantitative analysis of a successful public hydrogen station

Brown

Stephens-Romero

Samuelsen

2012

International Journal of Hydrogen Energy

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IntroductionGlobal climate change, air quality concerns, and the geopolitical and economic instability associated with petroleum fuel are driving manufacturers, and society, to find alternatives to gasoline and diesel powered automobiles. Hydrogen powered fuel cell vehicles offer a potential solution to all three major problems because hydrogen can be generated and consumed with little or no carbon footprint, pollutant emissions, or oil usage. The California Hydrogen Highway was the first large-scale governmental foray into the provision of hydrogen infrastructure and provided the needed refueling capacity for early vehicle deployment programs [1]. Thanks in part to the efforts of California and the availability of fueling stations, automakers have made remarkable advances in fuel cell vehicle development and are projecting commercialization in the 2015 timeframe [2]. As this deadline approaches, attention turns to establish a sufficient refueling infrastructure for early consumers. This reality is reinforced by the California Energy Commission's allocation of $22 million for hydrogen station funding for 2010, and another $14 million designated for 2011 [3]. A significant and globally researched part of this potential infrastructure rollout is fueling station placement [4e7]. The initial California Hydrogen Highway plan envisioned wellspaced fueling stations positioned along major transportation corridors [1]. Current planning for initial commercialization focuses on a "cluster" approach whereby several stations are clustered around the geographic fuel cell vehicle deployment regions [8,9]. An early cluster is developing in Orange County, California centered on the existing University of California (UC) Irvine station that will include a Shell Hydrogen station in Newport Beach that is undergoing initial fueling trials as of December 2011, Available online at www.sciencedirect.com journal h om epa ge: www.elsev ier.com/locate/he i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 7 ( 2 0 1 2 ) 1 2 7 3 1 e1 2 7 4 0

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Section: Station Configurationmentioning

confidence: 98%

Quantitative analysis of a successful public hydrogen station

Brown

Stephens-Romero

Samuelsen

2012

International Journal of Hydrogen Energy

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“…In the second area, studies have been completed that employ complex optimization algorithms and scenario-based analyses to model infrastructure deployment in large regions [17][18][19][20][21][22]. However, these analyses generally use simplified spatial representations of hydrogen demand and distribution networks.…”

Section: Introductionmentioning

confidence: 99%

A GIS-based assessment of coal-based hydrogen infrastructure deployment in the state of Ohio

Johnson

Yang

Ogden

2008

International Journal of Hydrogen Energy

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“…This framework was later on applied to supply chain management in the context of process systems engineering in the seminar works by Mele et al (2005) and Hugo et al (2005). These first works in the area were followed by many others, which explored new applications and proposed some methodological advances.…”

Section: Incorporation Of Life Cycle Assessment (Lca)mentioning

confidence: 99%

Multi-objective Optimisation Incorporating Life Cycle Assessment. A Case Study of Biofuels Supply Chain Design

Páez

Guillén‐Gosálbez

2016

Alternative Energy Sources and Technologies

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This chapter describes how to optimise energy systems considering their economic and environmental performance simultaneously. To this end, we follow an approach that combines life cycle assessment with multi-objective optimisation. We illustrate how to apply such a framework to the strategic design and planning of biofuel supply chains. The problem is formulated in mathematical terms as a multi-objective mixed-integer linear programme. The aim of the design/planning task is to maximise the net present value while the environmental impact is minimised simultaneously. Eco-indicator 99 is the life cycle assessment methodology incorporated in the model to quantify the environmental damage. The implementation of the algorithm in a case study based on the Argentine industry reveals the conflictive trade-off between economic and environmental objectives. The proposed framework provides valuable insight into the incidence of key operational features in the optimal biofuel supply chain network.

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Hydrogen infrastructure strategic planning using multi-objective optimization

Cited by 167 publications

References 8 publications

Quantitative analysis of a successful public hydrogen station

Quantitative analysis of a successful public hydrogen station

A GIS-based assessment of coal-based hydrogen infrastructure deployment in the state of Ohio

Multi-objective Optimisation Incorporating Life Cycle Assessment. A Case Study of Biofuels Supply Chain Design

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