Denmark

The results of a techno-economic model of distributed wind-hydrogen systems (WHS) located at each existing wind farm on the island of Ireland are presented in this paper. Hydrogen is produced by water electrolysis from wind energy and backed up by grid electricity compressed before temporarily stored then transported to the nearest injection location on the natural gas network. The model employs a novel correlation-based approach to select an optimum electrolyser capacity that generates a minimum levelised cost of hydrogen production (LCOH) for each WHS. Three scenarios of electrolyser operation are studied: (1) curtailed wind (2) available wind and (3) full capacity operations. Additionally two sets of input parameters are used: (1) current and (2) future techno-economic parameters. Additionally two electricity prices are considered: (1) low and (2) high prices. A closest facility algorithm in a geographic information system (GIS) package identifies the shortest routes from each WHS to its nearest injection point. By using current parameters results show that small wind farms are not suitable to run electrolysers under available wind operation. They must be run at full capacity to achieve sufficiently low LCOH. At full capacity the future average LCOH is 6–8 €/kg with total hydrogen production capacity of 49 kilotonnes per year or equivalent to nearly 3% of Irish natural gas consumption. This potential will increase significantly due to the projected expansion of installed wind capacity in Ireland from 5 GW in 2020 to 10 GW in 2030

Globally the accelerating use of renewable energy sources enabled by increased efficiencies and reduced costs and driven by the need to mitigate the effects of climate change has significantly increased research in the areas of renewable energy production storage distribution and end-use. Central to this discussion is the use of hydrogen as a clean efficient energy vector for energy storage. This review by experts of Task 32 “Hydrogen-based Energy Storage” of the International Energy Agency Hydrogen TCP reports on the development over the last 6 years of hydrogen storage materials methods and techniques including electrochemical and thermal storage systems. An overview is given on the background to the various methods the current state of development and the future prospects. The following areas are covered; porous materials liquid hydrogen carriers complex hydrides intermetallic hydrides electro-chemical storage of energy thermal energy storage hydrogen energy systems and an outlook is presented for future prospects and research on hydrogen-based energy storage

Hydrogen may play a key role in a future sustainable energy system as a carrier of renewable energy to replace hydrocarbons. This review describes the fundamental physical and chemical properties of hydrogen and basic theories of hydrogen sorption reactions followed by the emphasis on state-of-the-art of the hydrogen storage properties of selected interstitial metallic hydrides and magnesium hydride especially for stationary energy storage related utilizations. Finally new perspectives for utilization of metal hydrides in other applications will be reviewed.

Several manufacturers are developing heavy duty (HD) hydrogen stations and vehicles as zeroemissions alternatives to diesel and gasoline. In order to meet customer demands the new technology must be comparable to conventional approaches including safety reliability fueling times and final fill levels. For a large HD vehicle with a storage rated to 70 MPa nominal working pressure the goal to meet liquid fuel parity means providing 100 kg of hydrogen in 10 minutes. This paper summarizes the results to date of the PRHYDE project efforts to define the concepts of HD fueling which thereby lays the groundwork for the development of the safe and effective approach to filling these large vehicles. The project starts by evaluating the impact of several different assumptions such as the availability of static vehicle data (e.g. vehicle tank type and volume) and station data (e.g. expected station precooling capability) but also considers using real time dynamic data (e.g. vehicle tank gas temperature and pressure station gas temperature etc.) for optimisation to achieve safety and efficiency improvements. With this information the vehicle or station can develop multiple maps of fill time versus the hydrogen delivery temperature which are used to determine the speed of fueling. This will also allow the station or vehicle to adjust the rate of fueling as the station pre-cooling levels and other conditions change. The project also examines different steps for future protocol development such as communication of data between the vehicle and station and if the vehicle or station is controlling the fueling.

Alternative and especially renewable marine fuels are needed to reduce the environmental and climate impacts of the shipping sector. This paper investigates the business case for hydrogen as an alternative fuel in a new-built vessel utilizing fuel cells and liquefied hydrogen. A real option approach is used to model the optimal time and costs for investment as well as the value of deferring an investment as a result of uncertainty. This model is then used to assess the impact of a carbon tax on a ship owner’s investment decision. A low carbon tax results in ship owners deferring investments which then slows the uptake of the technology. We recommend that policymakers set a high carbon tax at an early stage in order to help hydrogen compete with fossil fuels. A clear and timely policy design promotes further investments and accelerates the uptake of new technologies that can fulfill decarbonization targets.

Green hydrogen is viewed as a promising energy carrier for sustainable development goals. However it has suffered from high costs hindering its implementation. For a stakeholder who considers both renewable energy and electrolysis units it is important to exploit the flexibility of such portfolios to maximize system operational revenues. To this end an electrolyser model that can characterize its dynamic behavior is required in both electric and thermal aspects. In this paper we develop a comprehensive alkaline electrolyser model that is capable of describing its hydrogen production properties temperature variations and state transitions (among production stand-by and off states). This model is further used to study the optimal dispatch of an electrolyser based on a real-world hybrid wind/electrolyser system. The results show the model can effectively capture the coupling between thermal–electric dynamics and on–off performance of an electrolyser. The flexible operation strategy based on this model is proven to significantly increase daily revenues under different spot price conditions for electricity. Comparing the model with the ones derived from conventional modeling methods reveals this model offers more operating details and highlights several operational features such as the preference for working at partial load conditions although at the expense of more computing resources. It is suggested to use this model in studies related to energy integration operation planning and control scheme development in which the multi-domain dynamic properties of electrolysers in electricity/gas/heat need to be properly characterized. A sensitivity analysis on key parameters of such electrolyser system is also introduced to connect the daily operation with long-term planning.

As the EU energy system transitions to low carbon the technology choices should consider a broader set of criteria. The use of Life Cycle Assessment (LCA) prevents burden shift across life cycle stages or impact categories while the use of Energy System Models (ESM) allows evaluating alternative policies capacity evolution and covering all the sectors. This study does an ex-post LCA analysis of results from JRC-EU-TIMES and estimates the environmental impact indicators across 18 categories in scenarios that achieve 80–95% CO₂ emission reduction by 2050. Results indicate that indirect CO₂ emissions can be as large as direct ones for an 80% CO₂ reduction target and up to three times as large for 95% CO₂ reduction. Impact across most categories decreases by 20–40% as the CO₂ emission target becomes stricter. However toxicity related impacts can become 35–100% higher. The integrated framework was also used to evaluate the Power-to-Methane (PtM) system to relate the electricity mix and various CO₂ sources to the PtM environmental impact. To be more attractive than natural gas the climate change impact of the electricity used for PtM should be 123–181 gCO₂eq/kWh when the CO₂ comes from air or biogenic sources and 4–62 gCO₂eq/kWh if the CO₂ is from fossil fuels. PtM can have an impact up to 10 times larger for impact categories other than climate change. A system without PtM results in ~4% higher climate change impact and 9% higher fossil depletion while having 5–15% lower impact for most of the other categories. This is based on a scenario where 9 parameters favor PtM deployment and establishes the upper bound of the environmental impact PtM can have. Further studies should work towards integrating LCA feedback into ESM and standardizing the methodology.

Nowadays the integration of multi-energy carriers is one of the most critical matters in smart energy systems with the aim of meeting sustainable energy development indicators. Hydrogen is referred to as one of the main energy carriers in the future energy industry but its integration into the energy system faces different open challenges which have not yet been comprehensively studied. In this paper a novel day-ahead scheduling is presented to reach the optimal operation of a hydrogen-based energy hub based on a stochastic multi-attribute decision-making approach. In this way the energy hub model is first developed by providing a detailed model of Power-to-Hydrogen (P2H) facilities. Then a new multi-objective problem is given by considering the prosumer’s role in the proposed energy hub model as well as the integrated demand response program (IDRP). The proposed model introduces a comprehensive approach from the analysis of the historical data to the final decision-making with the aim of minimizing the system operation cost and carbon emission. Moreover to deal with system uncertainty the scenario-based method is applied to model the renewable energy resources fluctuation. The proposed problem is defined as mixed-integer non-linear programming (MINLP) and to solve this problem a simple augmented e-constrained (SAUGMECON) method is employed. Finally the simulation of the proposed model is performed on a case study and the obtained results show the effectiveness and benefits of the proposed scheme.

This review presents methanol as a potential renewable alternative to fossil fuels in the fight against climate change. It explores the renewable ways of obtaining methanol and its use in efficient energy systems for a net zero-emission carbon cycle with a special focus on fuel cells. It investigates the different parts of the carbon cycle from a methanol and fuel cell perspective. In recent years the potential for a methanol economy has been shown and there has been significant technological advancement of its renewable production and utilization. Even though its full adoption will require further development it can be produced from renewable electricity and biomass or CO2 capture and can be used in several industrial sectors which make it an excellent liquid electrofuel for the transition to a sustainable economy. By converting CO2 into liquid fuels the harmful effects of CO2 emissions from existing industries that still rely on fossil fuels are reduced. The methanol can then be used both in the energy sector and the chemical industry and become an all-around substitute for petroleum. The scope of this review is to put together the different aspects of methanol as an energy carrier of the future with particular focus on its renewable production and its use in high-temperature polymer electrolyte fuel cells (HT-PEMFCs) via methanol steam reforming.

This paper focuses on developing a fast-solving open-source model for dynamic power-to-X plant techno-economic analysis and analysing the method bias that occurs when using other state-of-the-art power-to-X cost calculation methods. The model is a least-cost optimisation of investments and operation-costs taking as input techno-economic data varying power profiles and hourly grid prices. The fuel analysed is ammonia synthesised from electrolytic hydrogen produced with electricity from photovoltaics wind turbines or the grid. Various weather profiles and electrolyser technologies are compared. The calculated costs are compared with those derived using methods and assumptions prevailing in most literature. Optimisation results show that a semi-islanded set-up is the cheapest option and can reduce the costs up to 23% compared to off-grid systems but leads to e-fuels GHG emissions similar to fossil fuels with today’s electricity blend. For off-grid systems estimating costs using solar or wind levelized cost of electricity and capacity factors to derive operating hours leads to costs overestimation up to 30%. The cheapest off-grid configuration reaches production costs of 842 e/t3 . For comparison the "grey" ammonia price was 250 e/t3 in January 2021 and 1500 e/t3 in April 2022 (Western Europe). The optimal power mix is found to always include photovoltaic with 1-axis tracking and sometimes different types of onshore wind turbines at the same site. For systems fully grid connected approximating a highly fluctuating electricity price by a yearly average and assuming a constant operation leads to a small cost.