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Byline: I. A. Gondal and M. H. Sahir


Evolution of hydrogen economy is not only resource and technology dependant in the long-term, but also to a great extent on the deployment of the supporting infrastructure. This technical note outlines a skeleton framework, starting from the conversion of renewable resources up till its dispersion in the energy consumption centers. Feedback system through a Master Data Analyzer has been suggested, along with an identification of areas of optimization for economizing delivery to end user. This "Intelligent Just-in-time Power Generation System" (IJPGS) is an intelligent energy system that relies on live receipt and processing of Energy Data for an efficient Renewable Hydrogen Economy.

Key words: Hydrogen Economy, Renewable Energy, Infrastructure, Integrated Systems


Energy deficiency has become the single biggest challenge for most of the developing world. Long power outages not only have colossal GDP drawbacks but increased level of instability, giving rise not only to community unrest but also regional tensions. Environmental degradation causing Climate change is an added disadvantage carried by fossil fuels for the society. Ozone depletion and temperature rise being the major reasons. Renewable Hydrogen represent one of the clean energy sources, that although require long-term developments, yet have promising prospects as an alternate energy system. Fig 1 depicts Fossil fuel such as coal, shortfall of up to 15 Million TOE by the mid of next decade as given in the Annual Energy Review of US EIA 2009.

Hydrogen based energy system is purported to be the post-fossil era energy system. Such an energy system entails economically produced hydrogen which in turn requires delivery infrastructure that is well dispersed and evenly distributed for user ease. Several studies have contributed to this subject; however this paper describes a framework for the basis of Renewable Hydrogen Infrastructure with the Solar, Wind and Biomass in focus.

Hydrogen has been evaluated as a viable energy option (for Pakistan) and its potential has adequately been concluded to amount to 2746 kilo tonnes of solar generated hydrogen, while the wind generated hydrogen is estimated at 45 kilo tones from wind resources (Gondal and Sahir.,2010). These encouraging prospects require an accelerated course of action for Hydrogen integration in the energy economy.

The widespread introduction of hydrogen necessitates a comprehensive energy supply chain that is capable of producing, distributing, storing and dispensing hydrogen to end users. Most of the early hydrogen supply chain studies include fossil fuels in the evaluation of a competitive supply; however the eventual elimination of fossil fuels necessitates their preclusion. Hence only renewable resources have been considered in the present work. The model has been simplified to lay a fundamental structure upon which more detailed mathematical modeling can be based. This work is primarily related to Hydrogen Distribution and Delivery, and proposes a skeleton model for furthering initiatives in implementation. The subsequent writing briefly describes the various components of Hydrogen supply chain.

Renewable Hydrogen Production: Several pathways are available for hydrogen production from Renewable Energy resources as indicated in Fig 2 and have been described in detail by Gardener (2009) and Lipman et al., (2006). Economic viability, although equally significant yet evolving infrastructure deployments require parallel efforts, to enable timely implementation as and when the renewable conversion technologies become competitive.

Amongst others Solar, Wind and Biomass resources have fairly established technologies for energy generation. Wind potential in Pakistan is moderate with just 9% of the area with good to excellent wind availability, hence any Energy system based on Renewable resources have to bank on Solar resource as the main component. Commercial Solar options have been described briefly.

a. Solar Hydrogen

Solar energy can be utilized in a variety of ways namely:

i. Photovoltaic cells

ii. Solar thermal methods

iii. Solar photochemical methods

However in essence, the typical solar-hydrogen production can be depicted by Fig 3. Solar energy collector generates electric current that is fed to an electrolyser for producing hydrogen, which is than stored for use on demand either in vehicles or other fuel-cell applications. Alternately the generated DC output is fed through an inverter directly to the grid.

Various commercial projects have been completed or under process that indicate sustainable commercial solar hydrogen (Hagen, 2004). ABENGOASOLAR, Spain is presently operating 3 projects in Spain, while ABENGOA USA is working on four solar projects of significant nature (Bakos, 2005). Schematic process flow is exhibited in Fig 4. Internationally, 3 projects each in Algeria, Morocco and United Arab Emirates are underway. Similar SHEC (a US based company) have reported an output ranging from 10 megawatts (MW) to one giga watt (1,000 MW) range with different configurations for different applications (Geyer, 2009).

Over the years considerable interest in Wind turbines have led to a worldwide capacity of 159,213 MW after a 31.7% increase of 38,310 MW between 2008 and 2009 as shown in Although wind resource availability is limited as compared to solar energy however the power of wind can adequately be estimated from the potential and growth prospects based on its installed history since 1998. Several wind-to-electricity projects are in function around the world, while certain commercial as well as research oriented projects such as NREL's Wind to H2 is in progress in collaboration with "Excel Energy" in USA. Certain demonstration projects are also in process such as the UNIDO-ICHET (United Nations Industrial Development Organization- International Centre for Hydrogen Energy Technologies) supported Bozca Island Wind Hydrogen Project in Turkey and Tarfaya Sahara Wind Hydrogen Project in Morocco.

Schematic diagram for Wind hydrogen is illustrated in Fig 6. Wind turbines convert the mechanical power of wind to electrical power. The generated current is fed to an electrolyser for producing hydrogen. Compressed hydrogen is fed to an engine for producing AC power which feeds the local, regional or national grid.

Above examples ably demonstrate that the technologies are developed to an extent that their practical application to real world requirements are validated. Basing on this, the need arises for allied approaches to enable economized availability of non fossil based energy resources, which includes introduction of cheap technology as well as optimization techniques to economize the distribution and delivery infrastructure.

Renewable resources as elsewhere are wide spread in Pakistan as well. Potential of availability of this resource has been assessed in various studies including one that estimates Hydrogen generation from Renewable resources. Solar Energy is found in abundance in this part of the world and is estimated at an average of 5-7 kWh/m2/day all over the country (Gondal, 2010), similarly wind potential has also been termed as fair-to- moderate and wind corridors have been identified for prospective wind farming.

Hydrogen Distribution and Delivery: Hydrogen Infrastructure deployment has been studied with static as well as dynamic models. These studies have indicated that as market penetration progresses, centralized production is more preferred as compared to distributed production. It has also been noted that in order to cater for long-term hydrogen demands, building larger infrastructure would inevitably result into disproportionate cost of hydrogen. Thus building of infrastructure must be in consonance with hydrogen demand, to justify its construction and operation.

Hydrogen supply chains require hydrogen delivery based on supply of Hydrogen from a large-scale plant. The conclusions drawn from cost models of Yang and Ogden (2008) indicate, as shown in Fig 7 are:

A Quantities of hydrogen and delivery distance are the main factors determining the lowest cost of H2.

A Trucks are preferable mode for small quantities and short distances. Initial investments are low however as flow increases the economies of scale do not follow suit.

A Liquid hydrogen carriers are most suited for medium quantities over larger distances. Here the major cost components are the liquefaction equipment and electricity required for liquefaction.

A Pipeline infrastructure is best recommended for large amounts of hydrogen. Cost of pipeline is the single largest factor; however the same increase with flow rate as well as distance.

Hydrogen Storage: Storage of hydrogen forms an important if not critical part of the Hydrogen infrastructure, which in turn affect the cost depending upon the form and material used. Other factors affecting the storage aspects of infrastructure are the flow rate, system design as well as delivery mode and geographical terrain.

For a wider penetrated hydrogen economy where hydrogen fuel is utilized in a significantly major portion of the transport sector, pipelines offer the most economical delivery costs. As the use increases, the capital cost of pipeline and land become relatively insignificant while storage becomes an important concern. Thus quantity of flow and infrastructure design contributes significantly in delivery costs. Commercial storage options are discussed briefly in the preceding writing.

Liquefied hydrogen is transported using a cryogenic tank truck (Fig 8), whereas tube trailers are employed for transportation of hydrogen gas in compressed form. Compressed hydrogen gas is expensive to store as compared to liquid hydrogen because of the lower energy density of gas relative to liquid hydrogen. To cater for storage of high pressure gas, pressurized containers are used but these are expensive and safety concerns are also to be addressed.

Transportation of compressed hydrogen costs about eight times higher than that of liquefied hydrogen. The main reason behind this high cost is the quantity of hydrogen that can be transported per trip by any of the transportation modes. Tank truck has ten times higher capacity as compared to tube trailer. Therefore, it results in an increase in labor cost, trucks and their fuel.


This article is a study and includes a review of Hydrogen production methods keeping in view the availability of Renewable resources, specifically Solar and Wind energy. Potential of Hydrogen generation from these resources have already been estimated by Gondal and Sahir (2010). Basing on this potential a mathematical model has been developed. Further a skeleton framework for evolving a Hydrogen production, storage and delivery has been suggested, indicating the areas for optimization that economizes end-user cost.

Model Development: For the purpose of application, Pakistan is taken as a case study. The country is divided into 101 grids as shown in Fig.10 to match the longitude/latitude for simplicity.

Variables are listed below for Mathematical formulation

a. Renewable resources available in each grid square and resultant hydrogen output from each method is represented as:

Rs for Solar

Rw for wind

Rb for Biomass

b. Yield of hydrogen from each grid square

Transportation factor between each production plant and point of use (energy consumption centers)

i. fT1-for pipeline

ii. fT2-for truck

iii. fT3-for trailer

A portion of the hydrogen product may be used in Fuel-cell applications directly as Hydrogen gas (or liquefied form) and transported to Energy consumption centers. The remaining is converted to Electricity and connected to Main Grid for distribution [Fig 10].

Hydrogen output from each grid is represented by

H o = [?]n=1 (Rsn x f s + Rwn x f w + Rbn x fb)


Rsn=Product of area of grid available for solar energy and average solar radiation for the region.

Rwn= Product of area of grid available for wind energy and average wind density for the region.

Rbn=Product of area of grid available for biomass and average extraction for the region.

fs=Solar factor defined by the Solar technology

fw=Wind technology factor

fb=Biomass conversion factor

n=number of grids

if p=Percentage of Hydrogen used for Fuel-cell use:

H f = p[?]n=1 (Rsn x f s + Rwn x f w + Rbn x fb)

Hydrogen for conversion into electric power

H e = 1 [?] p[?]n=1 (Rsn x f s + Rwn x f w + Rbn x fb)

Hydrogen which is to be used in "fuel cells" in compressed form or liquid hydrogen is to be transported to energy consumption centers. Various options are available for its transportation, which include pipeline, truck and trailer.

Cost of hydrogen transportation to various cities depends not only upon distance, but also a factor that is peculiar to each mode, defined by fT.

f = Terrain factor depending upon the ground conditions i.e. plain area, desert, mountainous area etc.

This study presents hydrogen supply chain network that is based on "Renewable Energy Database" at the back end (see Appendix A, B and C). Solar and wind resource availability has been assessed in detail by Gondal and Sahir (2010).

Hydrogen Demand is determined based on population and per capita energy requirement:

H d = Ereq x Pg

Where Pg = population of grid

This also requires identification of geographically dense areas in terms of population as well s the industrialized areas. Excess hydrogen (H a x) from each grid can be transported to the next grid or point of demand.

Infrastructural Framework: Various elements of the framework are illustrated in Fig 11. Hydrogen production from each grid, "Ho" of complete area under-study is fed into the Master Data Analyzer (MDA). MDA in turn forms the decision support tool for the IJPGS (Intelligent Just-in-time Power Generation System). The system decides the proportionate distribution of hydrogen and, that for conversion to electricity. Electrical output is fed to the main grid and onward to power distribution companies (indicated as IESCO, GESCO, FESCO etc). Liquefied or compressed hydrogen is transported via trucks, trailer or pipelines depending upon the distance, quantity and population density of the target users, as discussed in Para 3 above. Increase in cost of transportation with distance and mode is illustrated in the magnifier (Fig 11). Excess hydrogen from each grid is notified to MDA and directed to the grid with deficiency. Feedback cycle of IJPGS is shown in Fig 12.

In this suggested distribution system (Fig 14), energy consumption centers form the (proposed) focal point for distribution of hydrogen. Import and export of hydrogen from the particular grid, is dependent on the availability of excess hydrogen product in the adjoining grids. The scenario can be compared with a vessel with multiple pressure sensitive valves in its perimeter. Thus if any excess hydrogen is available in any of the adjacent grids, flow of hydrogen takes place towards that grid. Flow is optimized at this stage as depicted by O2 in Figure 13.This can be referred to as an Intelligent Just-in- time power generation (IJPGS) system. However the intelligence has to be derived from the Master Data Analyzer as illustrated in Fig 11, which is again e.

dependant on the "Resource Data Bank" that has live feedback, schematically shown in Fig 12. Block diagram (Fig 14) indicates the grids as the boundaries (although not a real life assumption) that are connected with a flow path from grid-to-grid. Pathways are controlled and operated by the IJPG system. Excess and deficient Hydrogen in each grid is represented by "+" and "- "symbols respectively. Arrows are indicative of the flow of hydrogen from an "excess holding" grid to one that is deficient.

c. Optimization: (O3 for R3)

Three stage optimization results in an optimal cost proposal for an integrated renewable hydrogen system (thus named as O3 for R3). Fig 13 shows the three points of application of optimization described as following:


As the world crosses over the "Oil Peak" and enters the post-fossil era, research work and studies are increasingly focusing on alternative means of energy sources. While various options are available such as Nuclear, Hydro, Tidal, Geothermal and Renewable to name a few, the single biggest challenge remains "Sustainability". Climate change, environmental degradation and effects on Ecological footprints are some of the phenomena affecting the human health, well being and livability. Thus any study must preclude the fossil fuels in any future Energy Systems. A number of studies have been carried out on the evolution of the Hydrogen Supply Chain, nevertheless most if not all initiate with fossilized feed stocks of Hydrocarbons. Keeping in view the effects indicated very briefly, the study has been made which layouts the framework for development of Hydrogen Economy.

Wind conversion technologies are not only widely researched but are also one of the technologies most rapidly penetrating in the world energy systems (World Wind Energy Report., 2009). Pakistan's wind potential is moderate however the generation capacity can play an effective role in the power structure of Pakistan. Pakistan's Solar resources are excellent and the harnessing technology is also well developed, as discussed in paragraph 2 above. Hydrogen just like electricity is an energy vector, and can be used as fuel in internal combustion (IC) engines or converted into electricity on demand or fed into fuel-cell applications. Proposed framework indicates that Hydrogen can be produced all over the country, which can either be fed to the National Grid through the Power Distribution companies or transported as liquefied/gaseous Hydrogen in Tankers/trailers (Fig 11).

The mathematical model evaluates the amount of Hydrogen production capacity available in each grid, which can either be consumed or exported depending upon the local requirement, as elaborated in Fig 14. The IJPGS controls the entire Energy system through the Master Data Analyzer as part of the feedback loop exhibited at Fig 12.

Various pathways have been identified in different regions to initiate and accelerate the deployment of Hydrogen Economy. Accordingly infrastructural requirements are being worked out for ease and user- friendly supply of fuel. This study demonstrates the integration of renewable resources in the production of hydrogen, the management of resources through an intelligent system termed as the Master Data Analyzer and then identifies the optimization areas. A comprehensive database of Solar/Wind and other Renewable resources (Biomass/Hydel/Waste etc.) is foremost for the implementation of any transition to a fully sustainable and Renewable-based Energy System. Just-in-Time System also has to have a live feed back of the fluctuating demand and supply scenarios of the region under study. The application of Solar/Wind data as evaluated by Gondal and Sahir (2010) to a specific grid/region presents satisfactory results.

The same can be extrapolated for application to a regional or national level, and trials are required to be carried out to assess the feasibility of the proposed systems. Delivery systems are also under development, pipelines are considered to be the most economic way of transporting Hydrogen over long distances in a full-fledged Hydrogen Economy (Yang and Ogden, 2008). Similarly for Low-pressure Distribution i.e. within the cities, patterns as exhibited in Fig 13 are to be followed depending upon the population/user density as well as the distances. Extensive simulations and real-life situations would lead to a practicable method that can address the "Energy question".

Future Work: Data for the renewable resources may be integrated with the Master Data Analyzer, which has to be interpreted through special software primarily designed for the purpose of processing the data according to pre-defined criteria. Optimization techniques such as Lingo may be employed to determine the economical pathway for a region, which can then be applied to the whole area or country. Similarly the distribution networks are to be analyzed for suitability depending upon the cities.


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I. A. Gondal and M. H. Sahir

Department of Mechanical Engineering, University of Engineering and Technology, Taxila, Pakistan, Corressponding author:
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Author:Gondal, I.A.; Sahir, M.H.
Publication:Pakistan Journal of Science
Article Type:Report
Geographic Code:9PAKI
Date:Dec 31, 2011

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