Renewable hydrogen supply chains: A planning matrix and an agenda for future research

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

A Benders decomposition approach for the charging station location problem with plug-in hybrid electric vehicles

The flow refueling location problem (FRLP) locates p stations in order to maximize the flow volume that can be accommodated in a road network respecting the range limitations of the vehicles. This paper introduces the charging station location problem with plug-in hybrid electric vehicles (CSLP-PHEV) as a generalization of the FRLP. We consider not only the electric vehicles but also the plug-in hybrid electric vehicles when locating the stations. Furthermore, we accommodate multiple types of these vehicles with different ranges. Our objective is to maximize the vehicle-miles-traveled using electricity and thereby minimize the total cost of transportation under the existing cost structure between electricity and gasoline. This is also indirectly equivalent to maximizing the environmental benefits. We present an arc-cover formulation and a Benders decomposition algorithm as exact solution methodologies to solve the CSLP-PHEV. The decomposition algorithm is accelerated using Pareto-optimal cut generation schemes. The structure of the formulation allows us to construct the subproblem solutions, dual solutions and nondominated Pareto-optimal cuts as closed form expressions without having to solve any linear programs. This increases the efficiency of the decomposition algorithm by orders of magnitude and the results of the computational studies show that the proposed algorithm both accelerates the solution process and effectively handles instances of realistic size for both CSLP-PHEV and FRLP. © 2016 Elsevier Lt

TOOLS TO SUPPORT TRANSPORTATION EMISSIONS REDUCTION EFFORTS: A MULTIFACETED APPROACH

The transportation sector is a significant contributor to current global climatic problems, one of the most prominent problems that today's society faces. In this dissertation, three complementary problems are addressed to support emissions reduction efforts by providing tools to help reduce demand for fossil fuels. The first problem addresses alternative fuel vehicle (AFV) fleet operations considering limited infrastructure availability and vehicle characteristics that contribute to emission reduction efforts by: supporting alternative fuel use and reducing carbon-intensive freight activity. A Green Vehicle Routing Problem (G-VRP) is formulated and techniques are proposed for its solution. These techniques will aid organizations with AFV fleets in overcoming difficulties that exist as a result of limited refueling infrastructure and will allow companies considering conversion to a fleet of AFVs to understand the potential impact of their decision on daily operations and costs. The second problem is aimed at supporting SOV commute trip reduction efforts through alternative transportation options. This problem contributes to emission reduction efforts by supporting reduction of carbon-intensive travel activity. Following a descriptive analysis of commuter survey data obtained from the University of Maryland, College Park campus, ordered-response models were developed to investigate the market for vanpooling. The model results show that demand for vanpooling in the role of passenger and driver have differences and the factors affecting these demands are not necessarily the same. Factors considered include: status, willingness-to-pay, distance, residential location, commuting habits, demographics and service characteristics. The third problem focuses on providing essential input data, origin-destination (OD) demand, for analysis of various strategies, to address emission reduction by helping to improve system efficiency and reducing carbon-intensive travel activity. A two-stage subarea OD demand estimation procedure is proposed to construct and update important time-dependent OD demand input for subarea analysis in an effort to overcome the computational limits of Dynamic Traffic Assignment (DTA) methodologies. The proposed method in conjunction with path-based simulation-assignment systems can provide an evolving platform for integrating operational considerations in planning models for effective decision support for agencies that are considering strategies for transportation emissions reduction

Logística de la recarga de vehículos eléctricos

El concepte del vehicle elèctric, neix a principis del segle XIX, però no és fins la última dècada del segle XX que es comença a consolidar. Aquests vehicles, caracteritzats per no produir emissions ni fer soroll, són l’alternativa escollida pels fabricants de vehicles per fer front a fenòmens com el canvi climàtic, satisfent al mateix temps les necessitats dels usuaris. A més, moltes administracions i organismes supragovernamentals dediquen part dels seus esforços a la creació de polítiques per impulsar la penetració d’aquests vehicles al mercat. Dins aquest context, el present treball pretén aportar més coneixements a una de les principals problemàtiques a resoldre amb la implantació del vehicle elèctric, la baixa autonomia. A més, aprofitant l’aparició de nous sistemes de mobilitat com l’ús de vehicles compartits i el fort creixement que aquestes estratègies han tingut els últims temps, es pretén resoldre la problemàtica derivada del la mida que han de tenir les flotes de vehicles elèctrics compartits. Per resoldre la primera problemàtica referent a l’autonomia dels vehicles, s’enfocarà l’estudi a nivell logístic a partir de la creació d’un model amb l’objectiu de determinar el nombre de punts i estacions de recàrrega que hi ha d’haver en una àrea determinada, en funció de les característiques d’aquesta i de la demanda esperada, i a més es determinarà quina és la localització òptima d’aquestes. Pel que fa les flotes de vehicles elèctrics compartits, es proposa un model amb l’objectiu d’optimitzar la mida de les flotes de vehicles compartits a partir de les característiques d’aquests vehicles, i en funció de la demanda que es vulgui satisfer. A continuació s’han analitzat ambdós models, buscant per a quines variables els models resultes més sensibles. De l’anàlisi se n’extreu que per reduir els costos que suposa a l’actualitat el vehicle elèctric, les millores a aplicar són majoritàriament a nivell de vehicle o d’infraestructura de recàrrega d’aquests, i per tant són aplicables tant per el vehicle elèctric privat, com el d’ús compartit. Una variable estratègica a considerar per millorar l’acceptació d’aquests vehicles és el temps de recàrrega. La seva reducció, condueix a una disminució dels costos i per tant a una millora de la competitivitat d’aquests vehicles. Per fer-ho caldrà aplicar millores tecnològiques tant sobre la bateria del vehicle com sobre la infraestructura de recàrrega d’aquests; i a més, serà interessant la utilització de noves estratègies de recàrrega com la substitució de la bateria per una de carregada una vegada esgotada. A partir d’aquests anàlisis, també es conclou que per tal d’adaptar correctament els models a la realitat del lloc geogràfic on es volen implementar, serà necessari un estudi en profunditat tant del la zona com de la població a la que es vol servir, donada la rellevància que té el cost d’oportunitat sobre el resultat final. Finalment, es presenten possibles estratègies, així com oportunitats de negoci a desenvolupar a partir d’aquest nou mode de transport, i es proposen futures línies d’investigació

RESILIENT AND STRUCTURALLY CONTROLLABLE DESIGN OF MULTI-LEVEL INFRASTRUCTURE NETWORKS UNDER DISRUPTIONS

An infrastructure network comprises of different entities that are connected by the flow of materials, products, information or electricity. Disruptions could occur at any section of the network for a wide variety of reasons. Some examples include: company mergers (e.g., Halliburton’s impending purchase of Baker Hughes), labor union strikes (e.g., labor strike on the west coast of the United States in 2002), sanctions imposed or lifted (e.g., economic sanctions against Iran being lifted by the UN in July 2015), plantations being destroyed (banana plantations were destroyed by Hurricane Mitch in 1998), air traffic being suspended due to weather or terrorism, main suppliers put out of commission by natural disasters (e.g., the 1999 earthquake in Taiwan disrupted semiconductor fabrication facilities), etc. A resilient infrastructure network is one that has the ability to recover quickly from disruptions and ensure customers are minimally affected, while the simultaneous design of operational and strategic decisions in all levels of the network structure are considered. It becomes very important to design a resilient multi-level infrastructure network in order to manage disruptions using appropriate pre-disruption and post-disruption restoration strategies. The capability of structural controllability can help in recovering a disrupted infrastructure network and increasing its resilience before, during and after the occurrence of disruptions. In this dissertation, the problem of applying structural controllability in order to design a resilient multi-level infrastructure network under disruptions with the selection of appropriate restoration strategies and consideration of the trade-off between effectiveness and redundancy in the resilience analysis is considered. The aforementioned problem has four aspects worth of consideration: a) multi-level network structures, b) restorations strategies, c) resilience analysis, and d) structural controllability. In this regard, the primary research question is defined as: What methods are required for designing a resilient infrastructure network under disruptions through selecting appropriate restoration strategies in a manner of applying structural controllability? The primary research question is broken into four secondary questions in respect to each four aspects of the considered problem as follows. - What is a method to design a multi-level infrastructure network (e.g., node-level and network-level structures) considering both operational and strategic decisions? - What is a method to design a resilient infrastructure network through selecting appropriate pre-disruption (e.g., facility fortification, backup inventory) and post-disruption (e.g., reconfiguration, flexible production and inventory capacity) restoration strategies? - What is a method to evaluate network resilience as a function of time considering effectiveness and redundancy measures (e.g., service level and transportation time as effectiveness measures and control cost as redundancy measure)? - What is a method to determine the minimum number of driver nodes (i.e., driver nodes or controllers are required for controlling networks) to get structurally controllable infrastructure networks? In response to the primary research question, two methods are proposed in this dissertation. The first method is the multi-level infrastructure network (MLIN) method which refers to the first aspect of the problem. The second method is the resilient and structurally controllable infrastructure network (RCIN) method which refers to the second, third and last aspects of the problem. Based on these two proposed methods, the main created new knowledge in this dissertation is in tailoring and incorporating the structural controllability theory in the resilience analysis of disrupted infrastructure networks. The proposed MLIN and RCIN methods are verified and validated using two examples from the energy industry in the context of the validation square. An example of a network of electric charging stations for plug-in hybrid electric vehicles using renewable energy and power grid as sources of energy is used to demonstrate and validate the MLIN method. An example of a network of a multi-product European petroleum industry is used to demonstrate and validate the RCIN method. Although the proposed methods are solved for the two examples, both of them are generalizable to be applicable to any network-based complex engineered systems under disruptions