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Multi-objective optimization design of hydrogen infrastructures simultaneously considering economic cost, safety and CO2 emission
Abstract
Recently increasing attention has been given to a hydrogen infrastructure (HI) including producing, transporting, and delivering H-2, the next generation alternative renewable energy source to users. This paper is concerned with designing the HI considering multiple perspectives of economic cost efficiency, safety and low CO2 emission simultaneously. An optimization modeling approach is thus proposed to address such multiple objectives of cost efficiency of H-2 supply, safety guarantee and cost efficiency of CO2 mitigation in the HI design. The proposed model employs fuzzy multiple objective programming to compute a compromising solution among multiple objectives. A case study of the future HI in Korea is presented to demonstrate the applicability of the proposed model with some comments. The proposed modeling work can be further utilized for developing systematic decision-making tools for policy makers to determine investment strategies for developing HIs.
... A study case was developed in China, and the results are consistent with the current conditions. Although the weighted-sum method and the ε-constraint method are the most used when solving multiobjective problems, it must be emphasized that assigning a set of compatible objectives, as cost efficiency and safety level, is difficult without knowledge of their possible values (Han et al., 2013), leading to a vague final objective and thus an invalid solution. To overcome this difficulty, fuzzy linear programming with multiple objectives constitutes an interesting alternative. ...
... In general, in a fuzzy set methodology, it is assumed that there may be a fuzzy goal for each of the objective functions (Sakawa, 2012). The fuzzy set concept can be adopted to provide a clearer theoretical analysis than the others methods (Han et al., 2013). The fuzzy set method consists of minimizing the distance between the ideal and the desired solutions. ...
... The fuzzy set method consists of minimizing the distance between the ideal and the desired solutions. Following this approach, Han et al. (2013) designed the HI (H 2 infrastructure) considering economic cost efficiency, safety, and low CO 2 emissions simultaneously. An optimization modelling approach is thus proposed to address such multiple objectives in the HI design. ...
... In contrast, considerable research has been conducted on the optimization of the hydrogen supply chain, predominantly focusing on the transport sector. Han et al. (2013) [18] utilized Mixed Integer Linear Programming (MILP) to ascertain the optimum number of hydrogen production plants, their locations, and technologies, considering the overall supply chain from hydrogen production to the end-user in the transport sector. Shamsi et al. (2021) [19], developed a MILP-based MOO model solved by GAMS (General Algebraic Modeling Software) to examine the optimal sizes and locations of hydrogen production plants and refuelling stations in Ontario, Canada. ...
... In contrast, considerable research has been conducted on the optimization of the hydrogen supply chain, predominantly focusing on the transport sector. Han et al. (2013) [18] utilized Mixed Integer Linear Programming (MILP) to ascertain the optimum number of hydrogen production plants, their locations, and technologies, considering the overall supply chain from hydrogen production to the end-user in the transport sector. Shamsi et al. (2021) [19], developed a MILP-based MOO model solved by GAMS (General Algebraic Modeling Software) to examine the optimal sizes and locations of hydrogen production plants and refuelling stations in Ontario, Canada. ...
... The former represent the majority of cases, and the objective is typically the minimization of the total network cost. Such objective is typically featured also in multi-objective models, in which the additional targets are generally related to the environmental impact [36][37][38][39][40][41][42][43] and/or to the safety risk [40,42,43]. A different approach is followed by Brey et al. [44], who introduced a second objective on the deviation from the energy targets set by the government. ...
... The former represent the majority of cases, and the objective is typically the minimization of the total network cost. Such objective is typically featured also in multi-objective models, in which the additional targets are generally related to the environmental impact [36][37][38][39][40][41][42][43] and/or to the safety risk [40,42,43]. A different approach is followed by Brey et al. [44], who introduced a second objective on the deviation from the energy targets set by the government. ...
Hydrogen deployment as an energy vector will play a crucial role in the decarbonization of the energy and industrial sectors. Its integration with the energy system requires the development of an adequate delivery infrastructure. The identification of an optimal design and operation strategy is complex due the variety of technological options in each stage of the hydrogen supply chain. This work develops a mixed-integer linear programming model to optimize the design and operation of a hydrogen infrastructure, comprising the entire supply chain from production to demand. A crucial novelty element is the combination of technical alternatives and modelling features. The proposed multi-modality formulation optimizes the transport technology at each stage, selecting between pipelines, compressed hydrogen trucks, and liquid hydrogen trucks. The pipeline and road networks are built through the model integration with a Geographic Information System, and the operation is tracked with a daily resolution, following the typical day approach. The model application looks at hydrogen employment for clean mobility in a long-term scenario in the Italian region of Sicily, assuming a demand of 1.1 million equivalent passenger cars (30% of today’s stock). The resulting cost-optimal infrastructure features an average cost of delivered hydrogen of 3.81 €/kg, in line with mobility targets. The supply chain relies on the concurrent use of all transport modalities, thus showing that the multiplicity of options is a key asset in the development of a hydrogen economy.
... Many works analyse a snapshot of the infrastructure, i.e., a representative steady-state condition with timeinvariant quantities [5], [6], [9]- [11], [15], [24], [26], [27], thus sizing the HSC according to the condition identified as the most stressful moment throughout the year, e.g., in terms of highest demand and/or lowest production. While this approach allows to reduce the computational complexity of the model, it fails to track the optimal design and operation of storage units, which is paramount when dealing with hydrogen production from intermittent renewable energy sources (RES). ...
... Since these are not alternative, but rather competing, it would be beneficial to optimize also the selection of the transport technologies for each stage of the supply chain in a multimodality formulation. However, since this approach significantly increases the model complexity and computational requirements, it is featured in a limited number of studies [7], [8], [10], [11], [14], [16], [19]- [21], [23], [24], which typically introduce other simplifying modelling assumptions, whereas the majority considers a single transport modality at a time in mono-modality formulations. ...
Hydrogen is recognized as a key element of future low-carbon energy systems. For proper integration, an adequate delivery infrastructure will be required, to be deployed in parallel to the electric grid and the gas network. This work adopts an optimization model to support the design of a future hydrogen delivery infrastructure, considering production, storage, and transport up to demand points. The model includes two production technologies, i.e., steam reforming with carbon capture and PV-fed electrolysis systems, and three transport modalities, i.e., pipelines, compressed hydrogen trucks, and liquid hydrogen trucks. This study compares a multi-modality formulation, in which the different transport technologies are simultaneously employed and their selection is optimized, with a mono-modality formulation, in which a single transport technology is considered. The assessment looks at the regional case study of Lombardy in Italy, considering a long-term scenario in which an extensive hydrogen supply chain is developed to supply hydrogen for clean mobility. Results show that the multi-modality infrastructure provides significant cost benefits, yielding an average cost of hydrogen that is up to 11% lower than a mono-modality configuration.
... In that context, the deployment of hydrogen supply chains (HSCs) for market penetration of FCVs has raised a lot of interest. A lot of studies have addressed several issues related to HSC design and deployment ( Agnolucci et al., 2013 ;Almansoori and Betancourt-Torcat, 2016 ;Almansoori and Shah, 2012 ;Almaraz et al., 2014 ;Gondal and Sahir, 2013 ;Guillén-Gosálbez et al., 2010 ;Han et al., 2013 ;Hugo et al., 2005 ;Kamarudin et al., 2009 ;Sabio et al., 2010 ;Samsatli et al., 2016 ;Woo et al., 2016 ) to find the most efficient HSC network taking into account several criteria, that are mainly based on techno-economic consideration, such as the levelized hydrogen cost and environmental assessment with Global Warming Potential (GWP) impact as a key indicator and, in a more systemic way with Life Cycle Assessment (LCA) Hugo et al., 2005 ) as well as a risk index Han et al., 2013 ;Sabio et al., 2010 ). ...
... In that context, the deployment of hydrogen supply chains (HSCs) for market penetration of FCVs has raised a lot of interest. A lot of studies have addressed several issues related to HSC design and deployment ( Agnolucci et al., 2013 ;Almansoori and Betancourt-Torcat, 2016 ;Almansoori and Shah, 2012 ;Almaraz et al., 2014 ;Gondal and Sahir, 2013 ;Guillén-Gosálbez et al., 2010 ;Han et al., 2013 ;Hugo et al., 2005 ;Kamarudin et al., 2009 ;Sabio et al., 2010 ;Samsatli et al., 2016 ;Woo et al., 2016 ) to find the most efficient HSC network taking into account several criteria, that are mainly based on techno-economic consideration, such as the levelized hydrogen cost and environmental assessment with Global Warming Potential (GWP) impact as a key indicator and, in a more systemic way with Life Cycle Assessment (LCA) Hugo et al., 2005 ) as well as a risk index Han et al., 2013 ;Sabio et al., 2010 ). ...
A lot of recent studies have concluded that hydrogen could gradually become a much more significant component of the European energy mix for mobility and stationary fuel cell system applications. Yet, the challenge of developing a future commercial hydrogen economy still remains through the deployment of a viable hydrogen supply chain and an increasing fuel cell vehicle market share, which allows to narrow the existing cost difference regarding the conventional fossil fuel vehicle market. In this paper, the market penetration of hydrogen fuel cell vehicles, as substitutes for internal combustion engine vehicles has been evaluated from a social and a subsidy-policy perspective from 2020 to 2050. For this purpose, the best compromise hydrogen supply chain network configuration after the sequential application of an optimization strategy and a multi-criteria decision-making tool has been assessed through a Social Cost-Benefit Analysis (SCBA) to determine whether the hydrogen mobility deployment increases enough the social welfare. The scientific objective of this work is essentially based on the development of a methodological framework to quantify potential societal benefits of hydrogen fuel cell vehicles. The case study of the Occitania Region in France supports the analysis. The externality costs involve the abatement cost of CO2, noise and local pollution as well as platinum depletion. A subsidy policy scenario has also been implemented. For the case study considered, the results obtained that are not intended to be general, show that CO2 abatement dominates the externalities, platinum is the second largest externality, yet reducing the benefits obtained by the CO2 abatement. The positive externalities from air pollution and noise abatement almost reach to compensate for the negative costs caused by platinum depletion. The externalities have a positive effect from 2025. Using a societal cost accounting framework with externalities and subsidies, hydrogen transition timing is reduced by four years for the example considered.
... Solution) are applied to identify and verify the bi-optimal solution as described in the 330 following section [47]. 331 ...
... Thus, the Euclidian distance (EDi-) between each point 358 on the Pareto frontier and the nadir point can be determined as shown in Eq. 19. Then, 359 a new assessment (Yi) is defined as Eq. 20, thus the solution with maximum Yi is 360 considered as the most desired solution [47][48][49] ...
Combined cooling, heating and power system (CCHP) is an efficient alternative for building energy supply. Meanwhile, the advantages of high energy efficiency and low emission for solid oxide fuel cells (SOFCs) make the technology a promising prime mover for CCHP systems. In this study, a SOFC based CCHP system design and operation optimization model has been developed using the Mixed Integer Non-linear Programming (MINLP) approach. The model provides two capacity sizing options of the fixed size (user specified), and the optimal sizing. In the fixed size option, four dispatch strategies are considered, namely baseload, day/night, full-load, and electrical load following. In the optimal sizing option, the installed capacity of devices and the dispatch strategy are both optimized. Moreover, multi-objective optimizations are also conducted to optimize two conflicting objectives simultaneously by the Ɛ-constraint method. The optimal results are displayed by Pareto frontiers and the most desired solutions have been identified and verified by two decision-making approaches of LINMAP and TOPSIS. To make the model applicable to real world operation, novel constraints including part-load efficiency, equipment on/off, and numbers of start constraints are applied. Finally, the proposed model is applied to a case study of a hospital in Shanghai, China considering state-of-the-art technical specifications, time-of-use energy pricing, and emission factors. The results indicate environmental advantages of SOFC based CCHP system. Moreover, the levelized cost of energy (LCOE) identified by the proposed optimal design and dispatch model would be 0.17 $/kWh, which is lower than the conventional energy system.
... Hydrogen supply chain designs have been proposed by work done by Han et al. and de-León Almaraz et al. for South Korea and a Mid-Pyrenees region, respectively [18,19]. Both studies take a multi-objective optimization approach to carry out a comparative analysis between a centralized and a de-centralized production system based on their cost effectiveness, associated safety risks, and their environmental impact. ...
... Different probability distribution functions have been fitted to historical electricity pricing for a period of 10 years (2003-2013) in Ontario (Section 2.1). Taljan et al. and Han et al. [17,18] do not consider uncertainty and variability in hydrogen demand with respect to time in their respective studies. The uncertainty in hydrogen demand on an hourly basis has been accounted for through the development of five potential demand scenarios each hour (Section 2.2). ...
There is a need for energy storage to improve the efficiency and effectiveness of energy distribution with the increasing penetration of renewable energy sources. Among the various energy storage technologies being developed, ‘power-to-gas’ is one such concept which has gained interest due to its ability to provide long term energy storage and recover the energy stored through different energy recovery pathways. Incorporation of such systems within the energy infrastructure requires analysis of the key factors influencing the operation of electrolyzers and hydrogen storage. This study focusses on assessing the benefits power-to-gas energy storage while accounting for uncertainty in the following three key parameters that could influence the operation of the energy system: (1) hourly electricity price; (2) the number of fuel cell vehicles serviced; and (3) the amount of hydrogen refueled. An hourly time index is adopted to analyze how the energy hub should operate under uncertainty. The results show that there is a potential economic benefit for the power-to-gas system if it is modeled using the two-stage stochastic programming approach in comparison to a deterministic optimization study. The power-to-gas system also offers environmental benefits both from the perspective of the producer and end user of hydrogen.
... As an extension of the Mixed Integer Linear Programming (MILP) approach, Han et al. [42] elaborated fuzzy multiple objective programming to model the trade-offs between main objectives (total supply cost of H2, total risk, and total mitigation cost of CO2). Despite the proposed more complex approaches to solving the optimization problem, the problem of criteria matching and the problem of demand uncertainty remain the main drawbacks of MILP methods. ...
While there is a broad agreement in academia and the business community that hydrogen (H2) could significantly contribute to energy policy goals, there is no single shared vision of a sustainable hydrogen supply chain (HSC). The large number of sources for hydrogen production (various fossil fuels, biomass, water) and the different methods for extracting, distributing, and storing it make creating an efficient supply chain a challenge. The commonly used optimization techniques based on linear programming require a new mathematical problem to be formulated and solved for each case. Instead, this study aims to develop an innovative optimization approach for the hydrogen supply chain that does not require complete knowledge of the end-user hydrogen demand and applies to any region. Based on the Network Data Envelopment Analysis (NDEA) method, hybrid Life Cycle Analysis (LCA) and Value Sensitive Design (VSD) approach, the integral eco-efficiency indicator constructed by this approach is a weighted linear combination of economic parameters (CAPEX and OPEX) and environmental parameters (ecotoxicity, oxidation potential, eutrophication potential and climate change). The proposed approach has been tested on 22 different hydrogen supply chain options, confirming its efficiency and ability to inform national and international decision-making. For example, a pan-European decision support system could be based on continuously updated data from the EcoInvent database on environmental parameters
of hydrogen production, storage, and transport technologies, and updated data on economic parameters from the European Hydrogen Observatory
... The cost of carbon has been directly measured by expanding the cost definition to include carbon tax costs as well as the cost of emission trading schemes. Han et al. [60] explore the mitigation cost of implementing carbon emission trading schemes and installing carbon capture and storage within the HSC. In such a model, the decisions favor installing non-fossil-based hydrogen production or investing in a mitigation strategy that drives the mitigation costs down. ...
This paper reviews recent optimization models for hydrogen supply chains and production. Optimization is a central component of systematic methodologies to support hydrogen expansion. Hydrogen production is expected to evolve in the coming years to help replace fossil fuels; these high expectations arise from the potential to produce low-carbon hydrogen via electrolysis using electricity generated by renewable sources. However, hydrogen is currently mainly used in refinery and industrial operations; therefore, physical infrastructures for transmission, distribution, integration with other energy systems, and efficient hydrogen production processes are lacking. Given the potential of hydrogen, the greenfield state of infrastructures, and the variability of renewable sources, systematic methodologies are needed to reach competitive hydrogen prices, and design hydrogen supply chains. Future research topics are identified: 1) improved hydrogen demand projections, 2) integrated sector modeling, 3) improving temporal and spatial resolutions, 4) accounting for climate change, 5) new methods to address sophisticated models.
... Several studies have addressed issues related to the design and deployment of HSCs to find the most efficient HSC network by considering multiple criteria [31,33,45,48,56,[62][63][64][65][66][67][68]. They are primarily based on techno-economic considerations such as the hydrogen cost and on environmental assessment mostly involving Global Warming Potential (GWP) indicator and, in a more systemic way, a life cycle assessment methodology [31] with a recent contribution that includes the Planetary Boundaries [69] adding a set of biophysical limits critical for operating the planet safely to a MILP model. ...
This article presents a comprehensive approach to design hydrogen supply chains (HSCs) targeting industrial and mobility markets. Even if the inclusion of sustainability criteria is paramount, only a few studies simultaneously consider economic, environmental, and social aspects - the most difficult to measure. In this paper, the safety risk and the social cost-benefit (SCB) have been identified as quantifiable social criteria that would affect society and the end-users. The objectives of this research are (1) to design a sustainable HSC by using four objective functions, i.e., levelized cost of hydrogen, global warming potential, safety risk and social cost-benefit through a mixed-integer linear programming model; (2) to compare results from SCB and multiobjective optimisation. The integration of the SCB criterion at the optimisation stage is not a trivial task and is one of the main contributions of this work. It implies the minimisation of the total cost of ownership (TCO) for buses and trucks. The evolution of the HSC from 2030 to 2050 is studied through a multiobjective and multiperiod optimisation framework using the ε-constraint method. The methodology has been applied to a case study for Hungary with several scenarios to test the sensitivity of demand type and volume as well as the production technology. The results analysis highlights that (1) it is beneficial to have mixed demand (industry and mobility) and a gradual introduction/migration to electrolysis technology and fuel cell vehicles (FCVs) for a smooth transition. Liquid hydrogen produced via water electrolysis powered by nuclear and wind energy can result in an average levelized cost of $4.78 and 3.14 kg CO2-eq per kg H2; (2) the frameworks for multiobjective optimisation and SCB maximisation are complementary because they prioritise different aspects to design the HSC. Taxes and surcharges for H2 fuel will impact its final price at the refuelling station resulting in a higher TCO for FCVs compared to diesel buses and trucks in 2030 but the TCO becomes almost competitive for hydrogen trucks from 2035 when SCB is maximised. The SCB function can be refined and easily adapted to include additional externalities.
... To obtain the blend of the two objective functions, the emissions of , were introduced as a cost in the , (Equation (24)) by imposing a cost for tons of , emitted, i.e. a carbon tax, as the weight of the function . This is a strategy adopted by several authors in the energy field to evaluate the environmental impacts of energy systems, for example, by [27]. It should be noticed that in Italy no carbon tax is set yet, hence the value of was set to 50 €/tCO2,eq according to the average values for Europe and the 2030 projections for effective carbon rates in OECD countries [28,29]. ...
Green hydrogen is addressed as a promising solution to decarbonize industrial and mobility sectors. In this context, ports could play a key role not only as hydrogen users but also as suppliers for industrial plants with which they have strong commercial ties. The implementation of hydrogen technologies in ports has started to be addressed as a strategy for renewable energy transition but still requires a detailed evaluation of the involved costs, which cannot be separated from the correct design and operation of the plant. Hence, this study proposes the design and operation optimization of a hydrogen production and storage system in a typical Italian port. Multi-objective optimization is performed to determine the optimal levelized cost of hydrogen in environmental and techno-economic terms. A Polymer Electrolyte Membrane (PEM) electrolyzer powered by a grid-integrated photovoltaic (PV) plant, a compression station and two-pressure level storage systems are chosen to provide hydrogen to a hydrogen refueling station for a 20-car fleet and satisfy the demand of the hydrogen batch annealing in a steel plant. The results report that a 341 kWP PV plant, 89 kW electrolyzer and 17 kg hydrogen storage could provide hydrogen at 7.80 €/kgH2, potentially avoiding about 153 tCO2,eq/year (120 tCO2,eq/year only for the steel plant).
... An important aspect is how the time dependency of quantities is handled. The most common approach is to consider a snapshot, i.e., a representative steady-state condition in which quantities and demand are time-invariant [5], [6], [11], [16]- [32]. The studied condition is usually identified as the "worst moment" throughout the year in terms of high demand and/or low production, and the network components are sized according to what should be the most stressful situation. ...
This work addresses the infrastructural needs arising from the widespread deployment of hydrogen for clean mobility, by developing a model to optimize the design and operation of a hydrogen distribution infrastructure. The developed tool combines the use of detailed spatial data through a Geographic Information System to define the candidate networks' topologies and the resolution of a multi-modal transport optimization model to determine the cost-optimal infrastructure, considering a year-long time horizon with daily resolution. The analysis looks at a 2050 scenario with a 25% share of fuel cell electric vehicles among passenger cars, considering the Italian region of Lombardy as case study. Results show the advantages of infrastructural integration in terms of modalities and delivery areas. The resulting optimal infrastructure relies on the parallel use, with a specific mix, of all transport modalities (pipelines, compressed hydrogen trucks, and liquid hydrogen trucks), achieving an average cost of hydrogen production and delivery between 5 €/kg and 8 €/kg.
... Due to the rising awareness towards the environmental impact, several studies introduced this parameter in their existing optimization model as a cost function [Han et al., 2013, Hwangbo et al., 2018. For instance, the initial optimization study of hydrogen production from imported natural gas and from biomethane production transported using a pipeline system [Hwangbo et al., 2017] was extended to a multi-objective stochastic mixed-integer linear programming to optimize both annual cost and environmental cost [Hwangbo et al., 2018]. ...
Green hydrogen for mobility via fuel cell electric vehicles represent an alternative to conventional fuel to decarbonize transportation sector and develop a sustainable future energy system. Nevertheless, the physical and chemical properties of hydrogen make the transport and the storage of this energy carrier at its standard pressure and temperature conditions inefficient. Therefore, this thesis aims to investigate hydrogen transport technologies and to model the optimal infrastructure for different production and demand scenarios in France and Germany, coupled with geographical visualization of the distribution.For the framework considered and to allow the comparison between the two countries, wind power as an energy source was studied for hydrogen production using electrolyzer to meet the demand for fuel cell electric vehicles based on car park growth, population projection and different penetration scenarios. The network to transport hydrogen is restrained to the road infrastructure to investigate the impact of different state of aggregations on the hydrogen flow transported between different hydrogen production and distribution locations and capacities defined from 15 scenarios.First, several technologies for transporting and storing hydrogen at its liquid form as liquid hydrogen or as liquid organic hydrogen carrier, and as compressed gas at five different pressure levels are analyzed by calculating the energy requirements to deduce the costs of processing, storing and transporting hydrogen using trucks. Thus, compression work has been modelled using a multistage compressor and compared to 875 industrial compressors; Liquefaction work was calculated using the ideal work associated to a literature review on different liquefaction processes; While hydrogenation and de-hydrogenation process work has been simulated using ASPEN. As the hydrogen is transported using different tube and tank trucks, a technical assessment is performed to investigate the different storage options and define the parameters associated with truck transportation. Finally, the cost parameters chosen for investment and operating the different plants and trucks are estimated based on different literature reviews and cost assessments, in addition to energy, fuel and logistics costs.Then, these costs are formulated as annual levelized costs functions that include storage, road transport, liquefaction, compression, and de-hydrogenation costs based on the net present value methodology. Finally, to conclude to the share of the seven different technologies used to transport and store hydrogen between two locations, an optimization based on linear programming formulation was performed. This sub-model was then included in a more general cost flow optimization to link a set of production nodes to the distribution ones using the road network under capacities and flow constrains. This model allowed to conclude to the different cost of infrastructure deployment within the scope of the 15 different scenarios analyzed associated to a geographical visualization of the hydrogen flow transported in Germany and France.The sub-model results showed that in average compressed gas at a high-pressure level is mainly used at transport distance below 250 km in contrast to liquid hydrogen that has higher energy costs. Concerning early-stage infrastructure deployment, costs could be further minimized by substituting compressed gas at low to medium pressure levels by liquid organic hydrogen carrier. Finally, the analysis of the 15 scenarios showed a better geographical distribution of hydrogen in France, in contrast to the case of Germany that suffered from a disparity between production and eventual consumption locations.
... To obtain the blend of the two objective functions, the emissions of CO 2,eq were introduced as a cost in the f 1,2 (Equation (24)) by imposing a cost for tons of CO 2,eq emitted, i.e., a carbon tax, as the weight w 2 of the function f 2 . This is a strategy adopted by several authors in the energy field to evaluate the environmental impacts of energy systems, for example, by [27]. It should be noticed that in Italy no carbon tax is set yet, hence the value of w 2 was set to 50 €/t CO2,eq according to the average values for Europe and the 2030 projections for effective carbon rates in OECD countries [28,29]. ...
The exploitation of hydrogen as energy carrier is addressed as one of the most promising alternatives to decarbonize the industrial and mobility sectors. Green hydrogen produced via electrolysis from renewable sources could be directly used in the so called “hard-to-abate” sectors or provided as fuel for terrestrial and maritime vehicles. This study aims to design and optimize a green hydrogen hub in a port industrial area in the North-East of Italy. Hydrogen is produced using a polymer electrolyte membrane electrolyzer powered by a grid-integrated PhotoVoltaic (PV) plant. In particular, hydrogen production is meant to provide hydrogen to a Hydrogen Refuelling Station (HRS) for a fleet of 20 vehicles and to satisfy the demand of the hydrogen batch annealing in a steel production plant. A compression station, a two-level compressed gas storage system, and the HRS components (dispenser and chiller) are also included in the model of hydrogen production and storage plant.
A multi-objective approach has been adopted to optimize the design and operation of the proposed hydrogen hub, finding the levelized cost of hydrogen optimal in environmental and techno-economic terms. The analysis shows that for the hydrogen demand of both the annealing process and 20-car fleet, a 341 kWP PV plant coupled with an 89 kW electrolyzer is required, resulting in a hydrogen cost of 7.80 €/kgH2. The port area decarbonization through the development of such hydrogen hub could lead to a potential CO2,eq emission avoidance of about 153 tons/year, where 120 tons/year are avoided only by decarbonizing the annealing process. The approach used in the analysis could be further exploited for other industrial areas or other hydrogen uses.
... It is a demand-driven, steady-state model that integrates the main stages of HSC: production, storage, and transport. This model was then improved by taking into account aspects such as resource availability, demand variation over time, demand uncertainty, environmental impacts, and the progressive deployment of the chain by periods (Dayhim et al., 2014;De-León Almaraz et al., 2015;Han et al., 2013;Moreno-Benito et al., 2017;Nunes et al., 2015;Sabio et al., 2012Sabio et al., , 2010. The work presented in proposes an MILP model that can simultaneously determine the design and operation of any integrated multi-vector energy networks comprising technologies for conversion, storage, and transport. ...
This paper presents a methodological design framework for Hydrogen and Methane Supply Chains (HMSC) based on Power-to-Gas (PtG) systems. The novelty of the work is twofold, first considering a specific demand for hydrogen for electromobility in addition to the hydrogen demand required as a feedstock to produce synthetic methane from the methanation process. and performing a bi-objective optimization of the HMSC to provide effective support for the study of deployment scenarios. The approach is based on a Mixed Integer Linear Programming (MILP) approach with augmented epsilon-constraint implemented in the GAMS environment according to a multi-period approach (2035-2050) with several available energy sources (wind, PV, hydro, national network) for hydrogen production. Carbon dioxide sources stem mainly from methanization and gasification processes. The objectives to be minimized simultaneously are the Total Annual Cost and the greenhouse gas emissions related to the whole HMSC over the entire period studied.
... Studies also included multi-objective optimization, e.g., for the case of the United Kingdom, the uncertainty related to the hydrogen demand was also included in the analysis based on liquid hydrogen as a transport carrier [18]. Other studies also introduced the environmental impact in their existing optimization model as a cost function [22,23]. ...
Green hydrogen for mobility represents an alternative to conventional fuel to decarbonize the transportation sector. Nevertheless, the thermodynamic properties make the transport and the storage of this energy carrier at standard conditions inefficient. Therefore, this study deploys a georeferenced optimal transport infrastructure for four base case scenarios in France and Germany that differs by production distribution based on wind power potential and demand capacities for the mobility sector at different penetration shares for 2030 and 2050. The restrained transport network to the road infrastructure allows focusing on the optimum combination of trucks operating at different states of aggregations and storage technologies and its impact on the annual cost and hydrogen flow using linear programming. Furthermore, four other scenarios with production cost investigate the impact of upstream supply chain cost, and eight scenarios with daily transport and storage optimization analyse the modeling method sensitivity. The results show that compressed hydrogen gas at a high presser level around 500 bar was, on average, a better option. However, at an early stage of hydrogen fuel penetration, substituting compressed gas at low to medium pressure levels by liquid organic hydrogen carrier minimizes the transport and storage costs. Finally, in France, hydrogen production matches population distribution, in contrast to Germany, which suffers from supply and demand disparity.
... Agnolucci et al. [23] × × Almansoori and Betancourt-Torcat [24] × × Almansoori and Shah [25] × × Almaraz et al. [26] × × Almaraz et al. [27] × × Almaraz et al. [28] × × Andre et al. [29] × × Andre et al. [30] × × Bique and Zondervan [31] × × Brey et al. [32] × × Cho et al. [33] × × Dagdougui et al. [34] × × Dayhim et al. [35] × × Gim et al. [36] × × Han et al. [37] × × Han et al. [38] × × He et al. [39] × × Honma and Kuby [40] × × Hwangbo et al. [41] × × Johnson and Ogden [42] × × Konda et al. [43] × × Krishnan et al. [44] × × Lahnaoui et al. [45] × × Lin et al. [22] × × Kim and Kim [46] × × Kim and Kim [47] × × Moreno-Benito et al. [48] × × Nunes et al. [49] × × Ogumerem et al. [50] × × Parker [51] × × Rosenberg et al. [52] × × Sabio et al. [53] × × Sabio et al. [54] × × Samsatli et al. [55] × × Stephens-Romero et al. [56] × × Sun et al. [57] × × Sun et al. [58] × × Won et al. [59] × × ...
The hydrogen economy refers to an economic and industrial structure that uses hydrogen as its main energy source, replacing traditional fossil-fuel-based energy systems. In particular, the widespread adoption of hydrogen fuel cell vehicles (HFCVs) is one of the key factors enabling a hydrogen economy, and aggressive investment in hydrogen refuelling infrastructure is essential to make large-scale adoption of HFCVs possible. In this study, we address the problem of effectively designing a hydrogen supply network for refuelling HFCVs in urban areas relatively far from a large hydrogen production site, such as a petrochemical complex. In these urban areas where mass supply of hydrogen is not possible, hydrogen can be supplied by reforming city gas. In this case, building distributed hydrogen production bases that extract large amounts of hydrogen from liquefied petroleum gas (LPG) or compressed natural gas (CNG) and then supply hydrogen to nearby hydrogen stations may be a cost-effective option for establishing a hydrogen refuelling infrastructure in the early stage of the hydrogen economy. Therefore, an optimization model is proposed for effectively deciding when and where to build hydrogen production bases and hydrogen refuelling stations in an urban area. Then, a case study of the southeastern area of Seoul, known as a commercial and residential center, is discussed. A variety of scenarios for the design parameters of the hydrogen supply network are analyzed based on the target of the adoption of HFCVs in Seoul by 2030. The proposed optimization model can be effectively used for determining the time and sites for building hydrogen production bases and hydrogen refuelling stations.
... At the same time, the environmental objective has been considered in many previous related studies to achieve the clean and environmentally friendly production. Aiming at the optimal design of hydrogen infrastructure, which is responsible for the production, transportation, and delivery of hydrogen, Han et al. (2013) proposed an optimization modeling approach with the objectives of costs, safety and CO 2 emission considered at the same time and used the fuzzy multiple objective programming method to solve the model. For the design optimization of crude oil supply chain, in which the pipeline serves as the main way of transportation, Azadeh et al. (2017) took the total profits and environmental indicators as the bi-objectives. ...
With the increasing demand of refined products and growing concern about carbon emissions, the planned multi-product pipelines, serving as the primary way of refined products transportation, should be designed reasonably, economically, and low carbon-oriented so that the sustainable and environmentally friendly production and the rational construction of downstream oil supply chain can be achieved. Aiming at this issue, a multi-objective mixed-integer linear programming (MILP) model is proposed to minimize the total economic costs and CO2 emission simultaneously. Various actual process and technical constraints including pipeline construction, pump stations layout, pipeline hydraulic and pumps configurations are considered in the model. Based on the augmented ε-constraint method, the conflicting objectives are dealt with and the Pareto front can be get. Finally, based on a predicted future scenario of regional refined products demand, the proposed model was successfully applied to a real-word planned multi-product pipeline in China. Two cases are given to demonstrate the model’s applicability and the influence of CO2 emission objective on the pipeline design scheme determination. Meanwhile, the trade-off between the two objectives was analyzed in detail.
... Finally, the hydrogen production costs vary between 3.95 and 10.56 $ per kg for all 4 cases. Centralized hydrogen production guarantees more financial benefits with less safe and environmental friendly construction unlike decentralized production ( Han et al., 2013 ). ...
This work presents a strategy for the design of a hydrogen supply chain network for minimum daily sup- ply costs, minimum mitigation costs of CO2, and maximum network safety. The aim is to identify the best hydrogen infrastructure pathways while taking into account local factors such as the location of the hydrogen supply and demand, and distribution between the hydrogen production location and hydrogen demand points. The proposed model is a mixed integer linear program that is solved with AIMMS. The model is solved as a multi-criterion decision making problem, where three objectives (costs, safety, and environmental impact) are balanced. A three dimensional Pareto front is created using the epsilon con- straint method. Utopia point analysis is used to make trade-offdecisions in the Pareto front. Compared to the current internal combustion vehicle fuel with an average cost of 0.0645 per km, proofs the potential for a hydrogen economy. Implementation of decentralized hydrogen production plant based on water electrolysis may compete with coal-based dominant technology.
... post-, pre-, or oxyfuel-combustion matching the carbon-capture technology stage) there are 3 4 (81) possible paths to be considered. In this line, other aspects need to be included, such as risk and design constraints, multiperiod planning and scheduling perspectives [24], and capital rationing considerations. ...
The present study provides a viable route to solar syngas production and conversion to fine chemicals using renewable energy sources and rendering CO2 a valuable reactant instead of a waste. It uses existing facilities and on-going breakthrough technological advancements from CO2 transportation to H2O/CO2 solar co-splitting for syngas formation to further conversion to either methanol or Fischer-Tropsch (FT) products. A full scale simulation of the overall chemical process is established, considering its subsections with respect to all relevant cost elements and operating expenses using appropriate cost correlations. Eight spanning routes of the CO2 superstructure are assessed for a real case of transporting compressed pure or mixtures of CO2 with a 130 kg/s capacity over a distance of 120 km from a power plant in Ptolemaida, Greece, operating with either natural gas or coal, and combining with water from an existing wastewater treatment facility in Thessaloniki, Greece. It is estimated that the choice of producing methanol requires an investment of ˜€7B and ˜€430 M/y to operate, while for FT-related plants it would cost >€3B to build and ˜€190 M/y to operate. Applying a standard feed-in tariff (FIT) value in terms of subsidization of the energy consumed by renewable sources boosts the expenditure resulting for the best case to a yearly net profit of ˜€500 M or ˜€100 M, for methanol or FT products, respectively. Other scenarios are also considered, including the best spanning route for the minimum FIT revenues by the break-even method, or the required carbon price without any subsidization of the proposed schemes.
... Samsatli Applied Energy 233-234 (2019) researchers. For example: Almaraz and co-workers used a simplified version of the snapshot model and applied the risk methodology of Kim and Moon [10] to optimise hydrogen networks in Great Britain [11] and a region in France [12]; Dayhim et al. [13] considered demand uncertainties in a study for New Jersey, USA; Han et al. applied the snapshot model to a study in South Korea [14] and also added a fuzzyset approach for multi-objective optimisation [15]; Kim and Moon [10] applied multi-objective optimisation to the snapshot model; Konda et al. [16] applied the model to the Netherlands; Moreno-Benito et al. [17] extended it to include hydrogen pipelines, CCS and CO 2 pipelines; Sabio et al. [18] applied the model to a multi-objective optimisation study for Spain, considering a number of lifecycle assessment impacts and post-processing the results using principal component analysis; and Nunes et al. [19] extended the model to consider uncertainty in hydrogen demands. There are a number of important limitations to these types of model, including: ...
Demands for space and water heating constitute a significant proportion of the total energy demands in Great Britain and are predominantly satisfied through natural gas, which makes the heat sector a large emitter of carbon dioxide. Renewable hydrogen, which can be injected into the gas grid or used directly in processes for generating heat and/or electricity, is being considered as a low-carbon alternative energy carrier to natural gas because of its suitability for large-scale, long- and short-term storage and low transportation losses, all of which help to overcome the intermittency and seasonal variations in renewables. This requires new infrastructures for production, storage, transport and utilisation of renewable hydrogen – a hydrogen value chain – the design of which involves many interdependent decisions, such as: where to locate wind turbines; where to locate electrolysers, close to wind generation or close to demands; whether to transport energy as electricity or hydrogen, and how; where to locate storage facilities; etc.
This paper presents the Value Web Model, a novel and comprehensive spatio-temporal mixed-integer linear programming model that can simultaneously optimise the design, planning and operation of integrated energy value chains, accounting for short-term dynamics, inter-seasonal storage and investments out to 2050. It was coupled with GIS modelling to identify candidate sites for wind generation and used to optimise a number of scenarios for the production of hydrogen, from onshore and offshore wind turbines, in order to satisfy heat demands. The results show that over a wide range of scenarios, the optimal pathway to heat is roughly 20% hydrogen and 80% electricity. Hydrogen storage, both in underground caverns and pressurised tanks, is a key enabling technology.
... • Supply chain [38][39][40][41][42][43][44][45][46]. Discuss the different alternatives for production, storage and distribution to end user considering cost, scale (H 2 use) and efficiency, but focused only on hydrogen. ...
Hydrogen represents a versatile energy carrier with net zero end use emissions. Power-to-Liquid (PtL) includes the combination of hydrogen with CO2 to produce liquid fuels and satisfy mostly transport demand. This study assesses the role of these pathways across scenarios that achieve 80-95% CO2 reduction by 2050 (vs. 1990) using the JRC-EU-TIMES model. The gaps in the literature covered in this study include a broader spatial coverage (EU28+) and hydrogen use in all sectors (beyond transport). The large uncertainty in the possible evolution of the energy system has been tackled with an extensive sensitivity analysis. 15 parameters were varied to produce more than 50 scenarios. Results indicate that parameters with the largest influence are the CO 2 target, the availability of CO2 underground storage and the biomass potential. Hydrogen demand increases from 7 mtpa today to 20-120 mtpa (2.4-14.4 EJ/yr), mainly used for PtL (up to 70 mtpa), transport (up to 40 mtpa) and industry (25 mtpa). Only when CO2 storage was not possible due to a political ban or social acceptance issues, was electrolysis the main hydrogen production route (90% share) and CO 2 use for PtL became attractive. Otherwise, hydrogen was produced through gas reforming with CO2 capture and the preferred CO2 sink was underground. Hydrogen and PtL contribute to energy security and independence allowing to reduce energy related import cost from 420 bln€/yr today to 350 or 50 bln€/yr for 95% CO2 reduction with and without CO2 storage. Development of electrolyzers, fuel cells and fuel synthesis should continue to ensure these technologies are ready when needed. Results from this study should be complemented with studies with higher spatial and temporal resolution. Scenarios with global trading of hydrogen and potential import to the EU were not included .
... For example, in the model presented by Almansoori and Shah [7][8][9] for hydrogen supply chains, on which many energy supply chain models are based (e.g. [10][11][12][13][14][15][16][17][18][19][20][21][22]), the resources from the production plants will always have to go to the storage facilities and cannot be transported to other regions or distributed directly to the customers. Also, the reverse pathways cannot be handled by the multi-echelon formulation and adding a technology (e.g. ...
A multi-objective optimisation model, based on mixed integer linear programming, is presented that can simultaneously determine the design and operation of any integrated multi-vector energy networks. It can answer variants of the following questions:
What is the most effective way, in terms of cost, value/profit and/or emissions, of designing and operating the integrated multi-vector energy networks that utilise a variety of primary energy sources to deliver different energy services, such as heat, electricity and mobility, given the availability of primary resources and the levels of demands and their distribution across space and time? When to invest in technologies, where to locate them; what resources should be used, where, when and how to convert them to the energy services required; how to transport the resources and manage inventory?
Scenarios for Great Britain were examined involving different primary energy sources, such as natural gas, biomass and wind power, in order to satisfy demands for heat, electricity and mobility via various energy vectors such as electricity, natural gas, hydrogen and syngas. Different objectives were considered, such as minimising cost, maximising profit, minimising emissions and maximising renewable energy production, subject to the availability of suitable land for biomass and wind turbines as well as the maximum local production and import rates for natural gas.
Results suggest that if significant mobility demands are met by hydrogen-powered fuel cell vehicles, then hydrogen is the preferred energy vector, over natural gas, for satisfying heat demands. If natural gas is not used and energy can only be generated from wind power and biomass, electricity and syngas are the preferred energy carriers for satisfying electricity and heat demands.
... Recently, Mishra and Khasnabis (2011) proposed an optimization procedure for optimal safety alternatives allocation to minimize accidents at urban intersections subject to budgetary constraints. Han et al. (2013) designed a multi-objective optimization framework for economic-safety-emission optimization of a hydrogen infrastructure using a fuzzy optimization programming. Aven and Hiriart (2013) Although recently many research studies have been devoted to the issue of multi-objective safety-economic concurrent optimizations in different studies (see e.g., Riauke and Bartlett, 2009;Torres-Echeverría et al., 2012;Hoffenson et al., 2014) yet, to the best of the authors' knowledge, no similar model has been proposed yet for the specific case of surface mining operations, and in particular, the off-road-related-accidents in the US surface mine industry. ...
Off-road-truck-related accidents are a major cause of considerable losses in the US surface mining industry. Though the rates of fatalities, permanent disabilities and other injuries have shown decreasing trends in the past decade, the associated lost lives and working days are far from a “zero work place accident policy” in this industry. After identification of the root cause(s) of off-road truck related accidents, the major task is to decide on the implementation of appropriate safety measures. In cases that there are several alternatives, an optimal decision should be taken in order to choose the most effective alternative(s) which incur minimum costs while achieving maximum improvements. The three major objectives are defined, in this study, as (i) maximization of loss prevention, (ii) minimization of costs, and (iii) maximization of reliability of safety measures. A multi-objective three-function-two-variable mathematical framework for optimization of the decision is proposed. The framework is examined in a generic mining situation to demonstrate its applicability. The genetic algorithm method was used to solve the multi-objective decision problem. The results identified the most effective safety measures and the optimal time interval that each one should be employed to achieve the best results.
Shifting from fossil fuels to clean alternative fuel options such as hydrogen is an essential step in decarbonising the road freight transport sector and facilitating an efficient transition towards zero-emissions goods distribution of the future. Designing an economically viable and competitive Hydrogen Supply Chain (HSC) to support and accelerate the widespread adoption of hydrogen powered Heavy Goods Vehicles (H2-HGVs) is, however, significantly hindered by the lack of the infrastructure required for producing, storing, transporting and distributing the required hydrogen. This paper focuses on a bespoke design of a hydrogen supply chain and distribution network for the long-haul road freight transportation in the UK and develops an improved end-to-end and spatially-explicit optimisation tool to perform scenario analysis and provide important first-hand managerial and policy making insights. The proposed methodology improves over existing grid-based methodologies by incorporating spatially-explicit locations of Hydrogen Refuelling Stations (HRSs) and allowing further flexibility and accuracy. Another distinctive feature of the method and the analyses carried out in the paper pertains to the inclusion of bulk geographically agnostic, as well as geological underground hydrogen storage options, and reporting on significant cost saving opportunities. Finally, the curve for H2-HGVs penetration levels, safety stock period decisions, and the transport mode capacity against hydrogen levelized cost at pump have been generated as important policy making tools to provide decision support and insights into cost, resilience and reliability of the HSC.
Worldwide, energy systems are experiencing a transition to more sustainable systems. According to the Hydrogen Roadmap Europe (FCH EU, 2019), hydrogen will play an important role in future energy systems due to its ability to support sustainability goals and will account for approximately 13% of the total energy mix in the coming future. Correct hydrogen supply chain (HSC) planning is therefore vital to enable a sustainable transition, in particular when hydrogen is produced by water electrolysis using electricity from renewable sources (renewable hydrogen). However, due to the operational characteristics of the renewable HSC, its planning is complicated. Renewable hydrogen supply can be diverse: Hydrogen can be produced de-centrally with renewables, such as wind and solar energy, or centrally by using electricity generated from a hydro power plant with a large volume. Similarly, demand for hydrogen can also be diverse, with many new applications, such as fuels for fuel cell electrical vehicles and electricity generation, feedstocks in industrial processes, and heating for buildings. The HSC consists of various stages (production, storage, distribution, and applications) in different forms, with strong interdependencies, which further increase HSC complexity. Finally, planning of an HSC depends on the status of hydrogen adoption and market development, and on how mature technologies are, and both factors are characterised by high uncertainties. Directly adapting the traditional approaches of supply chain (SC) planning for HSCs is insufficient. Therefore, in this study we develop a planning matrix with related planning tasks, leveraging a systematic literature review to cope with the characteristics of HSCs. We focus only on renewable hydrogen due to its relevance to the future low-carbon economy. Furthermore, we outline an agenda for future research, from the supply chain management perspective, in order to support renewable HSC development, considering the different phases of renewable HSCs adoption and market development.
Worldwide, energy systems are experiencing a transition to more sustainable systems. According to the Hydrogen Roadmap Europe (FCH EU, 2019), hydrogen will play an important role in future energy systems due to its ability to support sustainability goals and will account for approximately 13% of the total energy mix in the coming future. Correct hydrogen supply chain (HSC) planning is therefore vital to enable a sustainable transition, in particular when hydrogen is produced by water electrolysis using electricity from renewable sources (renewable hydrogen). However, due to the operational characteristics of the renewable HSC, its planning is complicated. Renewable hydrogen supply can be diverse: Hydrogen can be produced de-centrally with renewables, such as wind and solar energy, or centrally by using electricity generated from a hydro power plant with a large volume. Similarly, demand for hydrogen can also be diverse, with many new applications, such as fuels for fuel cell electrical vehicles and electricity generation, feedstocks in industrial processes, and heating for buildings. The HSC consists of various stages (production, storage, distribution, and applications) in different forms, with strong interdependencies, which further increase HSC complexity. Finally, planning of an HSC depends on the status of hydrogen adoption and market development, and on how mature technologies are, and both factors are characterised by high uncertainties. Directly adapting the traditional approaches of supply chain (SC) planning for HSCs is insufficient. Therefore, in this study we develop a planning matrix with related planning tasks, leveraging a systematic literature review to cope with the characteristics of HSCs. We focus only on renewable hydrogen due to its relevance to the future low-carbon economy. Furthermore, we outline an agenda for future research, from the supply chain management perspective, in order to support renewable HSC development, considering the different phases of renewable HSCs adoption and market development.
Hydrogen management in an uncertain environment is an important aspect considering environmental and economic perspectives. In this paper, a novel framework and analysis for minimizing compression work in hydrogen allocation network (HAN) with parametric uncertainties are presented which includes stochastic and robust optimization approaches. The applicability of the proposed approaches is applied to a case study in a HAN of the refinery. In stochastic approaches, uncertainty can be converted into deterministic equivalents. The resultant deterministic problem is solved through pinch analysis. In normal distribution rise of 29% in resource requirement and almost 4% in energy, the requirement is calculated. Further, applying Chebyshev's one-sided inequality to the case study 120% more resource requirement and 12% increase in energy requirement is calculated. In robust optimization, three different robust optimization approaches are adapted to deal with bounded and known uncertainty. From the simulated result, it can be concluded that Bertsimas and Sim's approach is the most appropriate approach for such a problem because it provides a range of solutions i. e. least conservative to worst-case, and also the main benefit of this approach over the other two approaches that it preserves the linearity and provides a mechanism to control the degree of conservatism.
Hydrogen is central to meeting the challenge of climate change. The lack of infrastructure to produce, store, and deliver hydrogen is a significant obstacle to transitioning toward a hydrogen economy. For two decades, researchers have been interested in modeling the hydrogen supply chain network to provide managerial insights for decision-makers. We contribute to this research domain by introducing the life cycle optimization (LCO) modeling framework into the hydrogen supply chain network design (HSCND). Specifically, the life cycle costing (LCC) methodology and the life cycle assessment (LCA) approach are integrated through a bi-objective optimization. The two objectives are levelized cost of hydrogen (LCOH) and global warming potential (GWP) intensity. The problem is solved by implementing an ε-constraint method. The developed LCO framework is applied to a case study in Franche-Comté, France. Results obtained suggest that the introduction of LCC has a major impact on capital costs. The LCA, especially the life cycle inventory (LCI) approach, enables the LCO model to estimate emissions reasonably. The Pareto front obtained by solving the bi-objective model provides a holistic view of turning points. It is concluded that the modeling framework proposed in the paper can provide decision-makers with (i) comprehensive reflection of hydrogen supply network costs; (ii) a detailed description of hydrogen supply chain network-related emissions; and (iii) the quantification and visualization of the trade-off between costs and emissions.
Hydrogen is becoming an important candidate for replacing fossil fuels in the future energy economy. As such, efficient hydrogen supply chain system planning and the
promotion of its large-scale civilian and commercial application are needed. To identify research gaps in the field, this study reviews models and methods for planning hydrogen supply chain systems that have been employed over the past 15 years. Significant decision aspects and objectives in the hydrogen supply system are presented. Thereafter, problem types, modelling techniques and solution methods are analyzed and classified based on their individual characteristics. Finally, potential directions promoted by economic factors are recommended for future research.
Fossil fuels are the primary energy sources and meet the global energy demands. However, environmental and health problems related with these sources boosted the demand for renewable energy sources. Hydrogen, as an energy carrier has a growing potential for solving these problems. In this article, a mathematical programming model that integrates the production, storage and transportation, safety, location, and staff assignment decisions is presented considering minimization of costs. Although most of the studies focus on location, distribution, storage decisions of hydrogen energy networks, the article also includes production, safety and staff assignment decisions to make this problem more practical. Furthermore, we also investigate the set covering constraint will ensure that each region is covered by minimum number of the hydrogen facilities. The developed model ensures a balance between location, distribution, storage, production, safety and staff decisions by installing two production facilities by assigning total 9 warehouses, 22 tank trucks, 12100 km pipeline, 35 staffs under distance constraint 2000 km in regions 1 and 5. The computational results indicate that the proposed model produces effective solutions for the coverage to all region and minimum total cost for real-case situations.
Fossil fuels are the primary energy sources and meet the global energy demands. However, environmental and health problems related with these sources boosted the demand for renewable energy sources. Hydrogen, as an energy carrier has a growing potential for solving these problems. In this article, a mathematical programming model that integrates the production, storage and transportation, safety, location, and staff assignment decisions is presented considering minimization of costs. Although most of the studies focus on location, distribution, storage decisions of hydrogen energy networks , the article also includes production, safety and staff assignment decisions to make this problem more practical. Furthermore, we also investigate the set covering constraint will ensure that each region is covered by minimum number of the hydrogen facilities. The developed model ensures a balance between location, distribution, storage, production, safety and staff decisions by installing two production facilities by assigning total 9 warehouses, 22 tank trucks, 12100 km pipeline, 35 staffs under distance constraint 2000 km in regions 1 and 5. The computational results indicate that the proposed model produces effective solutions for the coverage to all region and minimum total cost for real-case situations. ARTICLE HISTORY
British Columbia is well positioned to capitalize on its natural resources and its carbon policies towards the development of a hydrogen fueling network. A multi-period optimization model was developed to design a hydrogen fuel supply chain based on a mixed integer linear programming formulation. The model was applied to the light duty passenger vehicle sector in British Columbia under three hydrogen demand scenarios. As part of the objective function, the model incorporated the current provincial emissions mitigation policies, i.e., a carbon tax and a low-carbon fuel standard (LCFS). Based on cost, our model indicates that steam methane reforming (SMR) is the least costly hydrogen production technology even with carbon policies in place. However, SMR would result in higher emissions (compared to other pathways). Coupling the carbon tax with the LCFS can be a suitable policy option when hydrogen price and GHG emissions are weighted equally.
This study reviews the papers that pertain to the hydrogen supply chain network design (HSCND) models published in scientific journals. A few drawbacks (e.g., the treatment of uncertainty and feedstock problems) and missing aspects (e.g., the intertemporal integration planning) in the literature are identified, thus motivating the development of a comprehensive HSCND methodology. Key components of the hydrogen supply chain are presented; thereafter, the models are analyzed and classified based on their decisions, performance measures, uncertainties, solution methodologies, and other model features. Moreover, an effort was made to complete the critical pre-optimization preparation works, which are essential but have been overlooked in previous reviews. Finally, a list of potential problems for future research directions is recommended.
This paper addresses a hydrogen supply chain network problem (HSCNP) with two transportation modes and replenishment cycles. For determining an optimal hydrogen supply chain network (HSCN), a mixed integer non-linear programming (MINLP) model is developed. Due to the intractability caused by non-linear terms of the MINLP model, a genetic algorithm-based matheuristic (GAM) is proposed by including a mixed integer linear programming (MILP) combined within the procedure of genetic algorithm (GA). The performance of GAM is compared with two GAs by using randomly generated instances. Then, several sensitivity analyses of demand, transportation cost, and inventory carrying cost are conducted to evaluate an effect on a configuration of HSCN. Finally, optimal network configurations and selection of transportation modes are estimated under different future demand scenarios of Jeju Island, South Korea.
In this work we present a multi-objective, multi-period, mixed integer, linear optimization formulation to analyze a hydrogen supply chain network. The objectives of the optimization problem are: (i) the maximization of the net present value (NPV) and (ii) the minimization of the greenhouse gas (GHG) emissions, while determining: (i) the locations of the hydrogen facilities, (ii) the production technology, (iii) the size of each facility (iv) transportation unit and (v) the distribution route. The model was deployed for the state of Texas and two scenarios were investigated: (i) oxygen co-produced with hydrogen from electrolysis is discarded and (ii) oxygen co-produced form the electrolysis is further processed and sold to generate revenue. A Pareto curve of twenty efficient points is developed and the extreme points on the curve are used to test the aforementioned scenarios. We found that further processing of produced oxygen for sell instead of discarding it made electrolysis an economically viable technology option for the production of hydrogen.
This paper aims to propose a new optimization-based approach to design and operate an integrated renewable energy sources (RES)-based energy system. In achieving the goal, we first generate the RES-based energy superstructure, which includes different sources (wind, solar, biomass and carbon dioxide), different energy conversion technologies, and different energy demands (electricity, hydrogen and fuels). We then develop a network optimization model using mixed integer linear programming (MILP) to design and analyze the energy supply system to the transportation sector. In this model, we set minimizing total cost as an objective function subject to various constraints including resource availability, demand satisfaction, energy flow conservation, and the limited capacity of technologies. Finally, we construct different scenarios of future demand portfolios in the transportation sector. We illustrate the applicability of the suggested model through the design problem of a complex renewable energy systems in Jeju Island, Korea. As a result, the total annual cost was estimated to range from 46 to 76 M$/year according to the demand scenarios. Through sensitivity study, we also analyzed the effect of demand structure, in particular the share of liquid fuels, to the configuration and economics of the examined system.
The synthesis of hydrogen distribution networks has been an active area of research over the last two decades. The concept of hydrogen management based on an economic cost-driven analysis appeared late in the 1990s and was followed up by numerous insight-based and mathematical optimisation approaches in the 2000s. More recently, several superstructure-based optimisation methods have been proposed to accommodate pressure restrictions, additional equipment and other practical constraints when finding the optimal flowsheet configuration. This paper provides a state-of-the-art review of different process integration technologies adopted for the assessment of hydrogen resources in refineries and petrochemical plants, published from late in the 1990s to the present time. Both targeting and design methods are reviewed. An effective hydrogen management strategy can only be achieved by combining different insight-based approaches with detailed mathematical programming.
This work studies the development of a sustainable hydrogen infrastructure that supports the transition towards a low-carbon transport system in the United Kingdom (UK). The future hydrogen demand is forecasted over time using a logistic diffusion model, which reaches 50% of the market share by 2070. The problem is solved using an extension of SHIPMod, an optimisation-based framework that consists of a multi-period spatially-explicit mixed-integer linear programming (MILP) formulation. The optimisation model combines the infrastructure elements required throughout the different phases of the transition, namely economies of scale, road and pipeline transportation modes and carbon capture and storage (CCS) technologies, in order to minimise the present value of the total infrastructure cost using a discounted cash-flow analysis. The results show that the combination of all these elements in the mathematical formulation renders optimal solutions with the gradual infrastructure investments over time required for the transition towards a sustainable hydrogen economy.
This paper presents a framework for the design and assessment of a renewable energy sources (RES)-based hydrogen supply system. We generate an integrated renewable hydrogen supply (IRHS) system that includes various types of RES and hydrogen technologies such as production, storage, and transportation. We then develop a multi-period deterministic optimization model for the IRHS system by using a mixed integer linear programming (MILP) technique. The proposed model optimizes the configuration and operational strategy of the IRHS system. The capability of the proposed model is demonstrated through its application to the design problem of Korea's future hydrogen economy. We perform an economic evaluation to identify the major parameters for the required cost of the energy system infrastructure.
Inter-city high-speed passenger transport, mainly aviation and high-speed railway, has been increasing around the world, in accordance with economic development and penetration of high-speed transport technologies. The energy consumption over the lifetime of transport infrastructure and operation is a significant factor at the planning stage. In this paper, we present a superstructure modelling and optimization framework of inter-city high-speed transport systems, accounting energy consumption during infrastructure construction and during subsequent operation, to optimize connections between large population centers and between modes of transport. Energy consumption during infrastructure construction is obtained from investment cost using lifecycle assessment. The first two cases considered differences between infrastructure construction and lifetime operation while the second case narrowed the study scope. Sensitivity analysis in the third case compared impacts of both transport means on system design. Model results have implications for actual high-speed transport technology development and infrastructure layout.
The design of a future hydrogen supply chain (HSC) network is challenging due to the: (1) involvement of many echelons in the supply chain network, (2) high level of interactions between the supply chain components and sub-systems, and (3) uncertainty in hydrogen demand. Most of the early attempts to design the future HSC failed to incorporate all these challenges in a single generic optimization framework using mathematical modeling approach. Building on our previous multiperiod MILP model, the model presented in this paper is expanded to take into account uncertainty arising from long-term variation in hydrogen demand using a scenario-based approach. The model also adds another echelon: fueling stations and local distribution of hydrogen. Our results show that the future HSC network is somewhat similar to the existing petroleum infrastructure in terms of production, distribution, and storage. In both situations, the most feasible solution is centralized production plants with truck and rail delivery and small-to-large storage facilities. The main difference is that the future hydrogen supply has the benefits of using distributed forecourt production of hydrogen at local fueling stations via several production technologies. Finally, the performance of the studied models was evaluated using sensitivity and risk analyses.
A fuzzy multiple objective decision making approach is proposed based on the desirable features of compromise programming and the fuzzy set theory. The proposed two-phase approach guarantees both nondominated and balanced solutions for solving both the crisp and the fuzzy multiple objective decision making problems. Furthermore, it is shown that the original compromise programming does not guarantee nondominated solutions if the distance parameter is assumed to be infinite and the resulting programming problem's solution is not unique.
The bicriterion formation of the two problems and the epsilon- constraint formulation viewing the identification problem as a constraint to the optimization problem are introduced. The equivalence theorem relating these two formulations is presented and proved.
Much of the early research in the hydrogen supply chain area was focused on individual technologies of the supply chain, such as production, storage, or distribution, rather than dealing with the supply chain as a whole. The motivation behind this paper is the need to: (1) design a hydrogen supply chain that integrates the previously mentioned components within a single framework, (2) understand the important trade-offs in such a supply chain, and (3) have a full understanding of the data requirements and uncertainties in such an exercise. Optimization techniques were implemented to develop the hydrogen supply chain for the transport sector, therefore, determining the optimum infrastructural and operational costs. Of course, cost is not likely to be the sole determinant of performance in practice. The network of interest was formulated as a mixed-integer linear programming (MILP) problem. Also, the network is presented as a steady state ‘snapshot’ problem using Great Britain as a backdrop. The model and assumptions presented in this paper reveal that the optimum future hydrogen supply chain might consist of medium-to-large, centralized methane steam reforming plants. The hydrogen produced from these plants will then be delivered as a liquid via tanker trucks and stored in centralized storage facilities.
The infrastructure of hydrogen presents many challenges and defies that need to be overcome for a successful transition to a future hydrogen economy. These challenges are mainly due to the existence of many technological options for the production, storage, transportation and end users. Given this main reason, it is essential to understand and analyze the hydrogen supply chain (HSC) in advance, in order to detect the important factors that may play increasing role in obtaining the optimal configuration. The objective of this paper is to review the current state of the available approaches for the planning and modeling of the hydrogen infrastructure. The decision support systems for the HSC may vary from paper to paper. In this paper, a classification of models and approaches has been done, and which includes mathematical optimization methods, decision support system based on geographic information system (GIS) and assessment plans to a better transition to HSC. The paper also highlights future challenges for the introduction of hydrogen. Overcoming these challenges may solve problems related to the transition to the future hydrogen economy.
Increasing scarcity of fossil fuels makes the deployment of hydrogen in combination with renewable energy sources, nuclear energy or the utilization of electricity from full time operation of existing power stations an interesting alternative. A pre-requisite is, however, that the safety of the required infrastructure is investigated and that its design is made such that the associated risk is at least not higher than that of existing supplies. Therefore, a risk analysis considering its most important objects such as storage tanks, filling stations, vehicles as well as heating and electricity supplies for residential buildings was carried out. The latter are considered as representative of the entire infrastructure. The study is based on fault and event tree analyses, wherever required, and consequence calculations using the PHAST code. The procedure for evaluating the risk and corresponding results are presented taking one of the objects as an example.
In this article, we address the design of hydrogen supply chains for vehicle use with economic and environmental concerns. Given a set of available technologies to produce, store, and deliver hydrogen, the problem consists of determining the optimal design of the production-distribution network capable of satisfying a predefined hydrogen demand. The design task is formulated as a bi-criterion mixed-integer linear programming (MILP) problem, which simultaneously accounts for the minimization of cost and environmental impact. The environmental impact is measured through the contribution to climate change made by the hydrogen network operation. The emissions considered in the analysis are those associated with the entire life cycle of the process, and are quantified according to the principles of Life Cycle Assessment (LCA). To expedite the search of the Pareto solutions of the problem, we introduce a bi-level algorithm that exploits its specific structure. A case study that addresses the optimal design of the hydrogen infrastructure needed to fulfill the expected hydrogen demand in Great Britain is introduced to illustrate the capabilities of the proposed approach. © 2009 American Institute of Chemical Engineers AIChE J, 2010
The thermal decomposition of natural gas forms the basis for the production of hydrogen with reduced CO2 emission. The hydrogen can be used to reduce CO2 from coal-fired power plants to produce methanol which can be used as an efficient automotive fuel. The kinetics of methane decomposition is studied in a one inch diameter tubular reactor at temperatures between 700 and 900 °C and at pressures between 28 and 56 atm. The Arrhenius activation energy is found to be 31.3kcal/mol of CH4. The rate increases with higher pressures and appears to be catalyzed by the presence of carbon particles formed. The conversion increases with temperature and is equilibrium limited. A thermodynamic study indicates that hydrogen produced by methane decomposition while sequestering the carbon produced requires the least amount of process energy with zero CO2 emission. Application to methanol synthesis by reacting the hydrogen with CO2 recovered from coal burning power plant stack gases can significantly reduce CO2 from both the utility and transportation sectors. Published by Elsevier Science Ltd on behalf of the International Association for Hydrogen Energy.
A novel consequence-based approach was applied to the inherent safety assessment of the envisaged hydrogen production, distribution and utilization systems, in the perspective of the widespread hydrogen utilization as a vehicle fuel. Alternative scenarios were assessed for the hydrogen system chain from large scale production to final utilization. Hydrogen transportation and delivery was included in the analysis. The inherent safety fingerprint of each system was quantified by a set of Key Performance Indicators (KPIs). Rules for KPIs aggregation were considered for the overall assessment of the system chains. The final utilization stage resulted by large the more important for the overall expected safety performance of the system. Thus, comparison was carried out with technologies proposed for the use of other low emission fuels, as LPG and natural gas. The hazards of compressed hydrogen-fueled vehicles resulted comparable, while reference innovative hydrogen technologies evidenced a potentially higher safety performance. Thus, switching to the inherently safer technologies currently under development may play an important role in the safety enhancement of hydrogen vehicles, resulting in a relevant improvement of the overall safety performance of the entire hydrogen system.
If fuel cells are introduced for vehicular applications, hydrogen might become an energy carrier for transport applications. Manufacture via steam-reforming of natural gas is a low-cost option for hydrogen production. This study deals with the feasibility of combining the production of hydrogen from natural gas with CO2 removal. When hydrogen is produced from natural gas, a concentrated stream of CO2 is generated as a by-product. If manufacture is carried out near a depleted natural gas field, the separated CO2 can be compressed and injected into the field and securely sequestered there. The incremental cost of the produced hydrogen (for CO2 compression plus transport, injection and storage) would typically be about 7% relative to the case where the separated CO2 is vented. Moreover, CO2 injection leads to enhanced natural gas recovery as a result of reservoir repressurization. Though the extra natural gas is somewhat contaminated with CO2, it is a suitable feedstock for hydrogen production. Taking credit for enhanced natural gas recovery reduces the penalty for sequestration to a net incremental cost of typically 2%. These cost penalties are much lower than those typical of CO2 removal schemes associated with electricity production. Attention is required for optimum plant siting in order to keep CO2 transport costs low.
This study presents a method for the design of a hydrogen infrastructure system including production, storage and transportation of hydrogen. We developed a generic optimization-based model to support the decision-making process for the design of the hydrogen supply chain. The network design problem is formulated as a mixed integer linear programming (MILP) problem to identify the optimal supply chain configurations from various alternatives. The objective is to consider not only cost efficiency, but also safety. Since there is a trade-off between these two objectives, formal multiobjective optimization techniques are required to establish the optimal Pareto solutions that can then be used for decision-making purposes. With the model, the effects of demand uncertainty can be also analyzed by comparing the deterministic and the stochastic solutions. The features and capabilities of the model are illustrated through the application of future hydrogen infrastructure of Korea. The optimal Pareto solutions utilize both cost-oriented and safety-oriented strategies.
Infrastructure issues pose more challenges and uncertainties for hydrogen than other alternative “fuels” such as biofuels and electricity. A key challenge of developing a future commercial hydrogen economy is how the infrastructure will be best designed and operated as time progresses, given that numerous technological options exist and are still in development for hydrogen production, storage, distribution and dispensing. This paper presents a generic optimization-based model for the strategic dynamic investment planning and design of future hydrogen supply chains. The features and capabilities of the model are illustrated through a detailed case study of China. It is shown how the proposed methodology can provide policy-makers with new tools for hydrogen development strategies.
Increasingly, hydrogen is being promoted as an alternative energy carrier for a sustainable future. Many argue that its use as a transportation fuel in fuel cell vehicles offers a number of attractive advantages over existing energy sources, especially in terms of well-to-wheel greenhouse gas emissions. Following this interest, several of the leading energy companies, like BP, have started investigating strategies for its introduction. The challenge of developing a future commercial hydrogen economy clearly still remains, though: what are the energy efficient, environmentally benign and cost effective pathways to deliver hydrogen to the consumer? Establishing what these “best” pathways may be is not trivial, given that a large number of technological options exist and are still in development for its manufacturing, storage, distribution and dispensing. Cost, operability, reliability, environmental impacts, safety and social implications are all performance measures that should be considered when assessing the different pathways as viable long-term alternatives. To aid this decision-making process, we present a generic optimization-based model for the strategic long-range investment planning and design of future hydrogen supply chains. By utilizing Mixed Integer Linear Programming (MILP) techniques, the model is capable of identifying optimal investment strategies and integrated supply chain configurations from the many alternatives. Realizing also that multiple performance criteria are of interest, the optimization is conducted in terms of both investment and environmental criteria, with the ultimate outcome being a set of optimal trade-off solutions representing conflicting infrastructure pathways. Since many agree that there is no one single template strategy for investing in a hydrogen infrastructure across the globe, emphasis is placed on developing a generic model such that it can be readily applied to different scenarios, geographical regions and case studies. As such, the model supports BP's strategic hydrogen infrastructure planning using high-level optimization programming, and is coined bpIC-H2. The features and capabilities of the model are illustrated through the application to a case study.
This study addresses the design problem of the hydrogen supply chain consisting of various activities such as production, storage and transportation. The purpose of this study is to (1) develop a stochastic model to take into account the effect of the uncertainty in the hydrogen activities and (2) examine the total network costs of various configurations of a hydrogen supply chain in an uncertain environment for hydrogen demand. A deterministic optimization model was first improved from previously existed model. A stochastic formulation based on the two-stage programming approach was then proposed to assure more realistic results. Uncertainty was introduced in the hydrogen demand of each region, which is estimated with an energy economy model and statistic data. This model was applied to evaluate the future hydrogen supply chain of Korea. Results include not only the investment strategy for the optimal supply chain configuration but also the effect of uncertain demands.
In this paper, we address the integration of production planning and reactive scheduling for the optimization of a hydrogen supply network consisting of five plants, four inter-connected pipelines and 20 customers. We present multiperiod mixed integer nonlinear programming (MINLP) models for both the planning and scheduling levels. The planning model includes complex pricing functions resulting from deregulation, with a simplified pipeline description and determines feed and energy prices, as well as production levels, for a monthly horizon divided into 12-h time periods. Prices are fixed on the scheduling level, while a detailed pipeline model is included, to determine the on/off status and load steps of compressors on an hourly basis, in order to satisfy the actual demands as they become known while adhering to pressure constraints. In addition, we propose a solution methodology where the demand forecast is updated and the planning model is rerun every 12 h, while the scheduling model is run every hour and information is passed between the two levels to facilitate integration. We show that the planning model quickly becomes intractable and propose a heuristic solution method for this level based on Lagrangean decomposition. Results show that the proposed Lagrangean decomposition heuristic reduces the computational effort for solving the planning model by more than an order of magnitude compared to the commercial MINLP solver DICOPT++. It is also shown that for the majority of the plants, the power consumption and hydrogen production from the scheduling level agrees with the planning level. In some cases, however, the integration is hampered by the presence of nonlinearities, especially on the scheduling level, that lead to suboptimal or infeasible solutions. These nonlinearities need to be further addressed before the proposed methodology can be implemented in practice.