Dynamic operation and feasibility study of a self-sustainable hydrogen fueling station using renewable energy sources

Li, Zhao; Brouwer, Jacob

doi:10.1016/j.ijhydene.2015.01.044

Cited by 91 publications

(17 citation statements)

References 36 publications

(65 reference statements)

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“…3 that when selecting t=(0.25 ÷ 2.5) ms the maximum value of a mismatch error for the AFC of a hydrogen generator does not exceed 1.4 %, and for a mismatch error for PFC does not exceed 1.7 %. Such error values in the formation of source data to assess the technical condition of hydrogen generators do not exceed permissible values, which in practice are about 5-6 % [12].…”

Section: Dq0=p1mentioning

confidence: 96%

“…These characteristics are not used to assess the technical condition of the device. A similar approach is taken in paper [12], in which, for the case of an electrolyzer with a proton-exchange membrane, the dynamic characteristics of the hydrogen storage and supply system are determined. The industrial samples of hydrogen generators typically employ control over one or two parameters of the hydrogen generation process [13].…”

Section: Determining the Source Data To Form A Control Algorithm For mentioning

confidence: 99%

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Determining the source data to form a control algorithm for hydrogen generators

Abramov¹,

Basmanov²,

Kryvtsova³

et al. 2019

EEJET

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При формуваннi алгоритму контролю технiчного стану генераторiв водню в якостi вихiдних даних використовуються їх амплiтудно-частотнi та фазово-частотнi характеристики. При використаннi класичного методу визначення таких характеристик мають мiсце декiлька недолiкiв. Одним iз суттєвих недолiкiв є великий час, який необхiдний для формування масиву вихiдних даних. Для скорочення цього часу визначення частотних характеристик генератора водню здiйснюється за результатами вимiрювань його перехiдної функцiї в дискретнi моменти часу. В цi моменти часу перехiдна функцiя апроксимується функцiями Хевiсайда. Такий пiдхiд дозволяє скоротити час визначення частотних характеристик генератора водню на 1-2 порядки. Використання теореми Котельнiкова-Найквиста-Шеннона для визначення цих дискретних моментiв часу пов'язано iз невизначенiстю стосовно максимальної частоти спектру тест-сигналу. Для зняття цiєї невизначеностi вибiр дискретних моментiв часу для вимiру перехiдної функцiї генератора водню здiйснюється за умови допустимої похибки її апроксимацiї. Похибка апроксимацiї визначається за результатом розв'язання тест-задачi, в якiй в якостi еталону частотних характеристик використовуються модельнi характеристики. Показано, що при iнтервалi дискретностi (0,252,5) мс величина такої похибки не перевищує 1,7 %. Враховано iнерцiйнi властивостi пристрою для формування тест-впливу. Показано, що доцiльнiсть використання такої процедури має мiсце, якщо еквiвалентна постiйна часу такого пристрою перевищує величини постiйних часу генератора водню. Iнерцiйнi властивостi врахованi шляхом введення додаткового множника, який мiстить еквiвалентну постiйну часу пристрою, в аналiтичних виразах для частотних характеристик генератора водню Ключевi слова: генератор водню, вихiднi данi, частотнi характеристики, тест-задача, похибка апроксимацiї

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Section: Dq0=p1mentioning

confidence: 96%

Section: Determining the Source Data To Form A Control Algorithm For mentioning

confidence: 99%

Determining the source data to form a control algorithm for hydrogen generators

Abramov¹,

Basmanov²,

Kryvtsova³

et al. 2019

EEJET

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“…Building a large centralised electrolyser could reduce the cost of hydrogen production, but on the other hand, the cost of transportation would increase [32]. There are three main forms of hydrogen transportation, which are:…”

Section: Hydrogen Production Overviewmentioning

confidence: 99%

Dispatchable Hydrogen Production at the Forecourt for Electricity Demand Shaping

Rahil

Gammon

2017

Sustainability

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Environmental issues and concerns about depletion of fossil fuels have driven rapid growth in the generation of renewable energy (RE) and its use in electricity grids. Similarly, the need for an alternative to hydrocarbon fuels means that the number of fuel cell vehicles is also expected to increase. The ability of electricity networks to balance supply and demand is greatly affected by the variable, intermittent output of RE generators; however, this could be relieved using energy storage and demand-side response (DSR) techniques. One option would be production of hydrogen by electrolysis powered from wind and solar sources. The use of tariff structures would provide an incentive to operate electrolysers as dispatchable loads. The aim of this paper is to compare the cost of hydrogen production by electrolysis at garage forecourts in Libya, for both dispatchable and continuous operation, without interruption of fuel supply to vehicles. The coastal city of Derna was chosen as a case study, with the renewable energy being produced via a wind turbine farm. Wind speed was analysed in order to determine a suitable turbine, then the capacity was calculated to estimate how many turbines would be needed to meet demand. Finally, the excess power was calculated, based on the discrepancy between supply and demand. The study looked at a hydrogen refueling station in both dispatchable and continuous operation, using an optimisation algorithm. The following three scenarios were considered to determine whether the cost of electrolytic hydrogen could be reduced by a lower off-peak electricity price. These scenarios are: Standard Continuous, in which the electrolyser operates continuously on a standard tariff of 12 p/kWh; Off-peak Only, in which the electrolyser operates only during off-peak periods at the lower price of 5 p/kWh; and 2-Tier Continuous, in which the electrolyser operates continuously on a low tariff at off-peak times and a high tariff at other times. The results indicate that Scenario 2 produced the cheapest electricity at £2.90 per kg of hydrogen, followed by Scenario 3 at £3.80 per kg, and the most expensive was Scenario 1 at £6.90 per kg.

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“…The growth of renewable but intermittent energy sources will increase the need for larger, more flexible and more diversified storage possibilities for electricity. Bio‐P2M converting electricity to hydrogen, and then hydrogen and CO 2 to CH 4 , offers the possibility to store electricity from renewable sources in the form of methane . Storage of electricity in the form of methane is an option that warrants consideration.…”

Section: Introductionmentioning

confidence: 99%

“…Bio-P2M converting electricity to hydrogen, and then hydrogen and CO 2 to CH 4 , offers the possibility to store electricity from renewable sources in the form of methane. 18,19 Storage of electricity in the form of methane is an option that warrants consideration.…”

Section: Introductionmentioning

confidence: 99%

Farm‐scale bio‐power‐to‐methane: Comparative analyses of economic and environmental feasibility

et al. 2019

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Summary Power‐to‐gas technologies are considered to be part of the future energy system, but their viability and applicability need to be assessed. Therefore, models for the viability of farm‐scale bio‐power‐to‐methane supply chains to produce green gas were analysed in terms of levelised cost of energy, energy efficiency and saving of greenhouse gas emission. In bio‐power‐to‐methane, hydrogen from electrolysis driven by surplus renewable electricity and carbon dioxide from biogas are converted to methane by microbes in an ex situ trickle‐bed reactor. Such bio‐methanation could replace the current upgrading of biogas to green gas with membrane technology. Four scenarios were compared: a reference scenario without bio‐methanation (A), bio‐methanation (B), bio‐methanation combined with membrane upgrading (C) and the latter with use of renewable energy only (all‐green; D). The reference scenario (A) has the lowest costs for green gas production, but the bio‐methanation scenarios (B‐D) have higher energy efficiencies and environmental benefits. The higher costs of the bio‐methanation scenarios are largely due to electrolysis, whereas the environmental benefits are due to the use of renewable electricity. Only the all‐green scenario (D) meets the 2026 EU goal of 80% reduction of greenhouse gas emissions, but it would require a CO2 price of 200 € t−1 to achieve the levelised cost of energy of 65 €ct Nm−3 of the reference scenario. Inclusion of the intermittency of renewable energy in the scenarios substantially increases the costs. Further greening of the bio‐methanation supply chain and how intermittency is best taken into account need further investigation.

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Dynamic operation and feasibility study of a self-sustainable hydrogen fueling station using renewable energy sources

Cited by 91 publications

References 36 publications

Determining the source data to form a control algorithm for hydrogen generators

Determining the source data to form a control algorithm for hydrogen generators

Dispatchable Hydrogen Production at the Forecourt for Electricity Demand Shaping

Farm‐scale bio‐power‐to‐methane: Comparative analyses of economic and environmental feasibility

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