Transmission, Distribution & Storage

Self-sufficiency of buildings with carbon emission reduction can be obtained thanks to the introduction of Photovoltaics systems coupled with Hydrogen seasonal storage. To be self-sufficient over the year the electricity converted to hydrogen by electrolysis during the sunny season can be re-used with the help of fuel cells during the winter season. This article is dealing with the dimensioning methodology of a solar PV hydrogen-electrochemical system for self-sufficient buildings. We introduce the case study of the first private building in western Switzerland that will be equipped with solar hydrogen storage. Calculation results of the dimensioning of the PV system with storage will be presented. The life cycle assessment and the calculations of the environmental indicators GWP and CED will be introduced.

With increasing attention to climate change the penetration level of renewable energy sources (RES) in the electricity network is increasing. Due to the intermittency of RES gas‐fired power plants could play a significant role in backing up the RES in order to maintain the supply– demand balance. As a result the interaction between gas and power networks are significantly in‐ creasing. On the other hand due to the increase in peak demand (e.g. electrification of heat) net‐ work operators are willing to execute demand response programs (DRPs) to improve congestion management and reduce costs. In this context modeling and optimal implementation of DRPs in proportion to the demand is one of the main issues for gas and power network operators. In this paper an emergency demand response program (EDRP) is implemented locally to reduce the con‐ gestion of transmission lines and gas pipelines more efficiently. Additionally the effects of optimal implementation of local emergency demand response program (LEDRP) in gas and power networks using linear and non‐linear economic models (power exponential and logarithmic) for EDRP in terms of cost and line congestion and risk of unserved demand are investigated. The most reliable demand response model is the approach that has the least difference between the estimated demand and the actual demand. Furthermore the role of the LEDRP in the case of hydrogen injection instead of natural gas in the gas infrastructure is investigated. The optimal incentives for each bus or node are determined based on the power transfer distribution factor gas transfer distribution factor available electricity or gas transmission capability and combination of unit commitment with the LEDRP in the integrated operation of these networks. According to the results implementing the LEDRP in gas and power networks reduces the total operation cost up to 11% and could facilitate hydrogen injection to the network. The proposed hybrid model is implemented on a 24‐bus IEEE electricity network and a 15‐bus gas network to quantify the role and value of different LEDRP models.

Hydrogen can be stored and distributed by injecting into existing natural grids then at the user site separated and used in different applications. The conventional technology for hydrogen separation is pressure swing adsorption (PSA). The recent NREL study showed the extraction cost for separating hydrogen from a 10% H2 stream with a recovery of 80% is around 3.3e8.3 US$/kg. In this document new system configurations for low hydrogen concentration separation from the natural gas grid by combining novel membrane-based hybrid technologies will be described in detail. The focus of the manuscript will be on the description of different configurations for the direct hydrogen separation which comprises a membrane module a vacuum pump and an electrochemical hydrogen compressor. These technological combinations bring substantial synergy effect of one another while improving the total hydrogen recovery purity and total cost of hydrogen. Simulation has been carried out for 17 different configurations; according to the results a configuration of two-stage membrane modules (in series) with a vacuum pump and an electrochemical hydrogen compressor (EHC) shows highest hydrogen purity (99.9997%) for 25 kg/day of hydrogen production for low-pressure grid. However this configuration shows a higher electric consumption (configuration B) due to the additional mechanical compressor between the two-stage membrane modules and the EHC. Whereas when the compressor is excluded and a double skin Pd membrane (PdDS) module is used in a single stage while connected to a vacuum pump (configuration A5) the hydrogen purity (99.92%) slightly decreases yet the power consumption considerably improves (1.53 times lower). Besides to these two complementary configurations the combination of a single membrane module a vacuum pump and the electrochemical compressor has been also carried out (configuration A) and results show that relatively higher purity can be achieved. Based on four master configurations this document presents a different novel hybrid system by integrating two to three technologies for hydrogen purification combined in a way that enhances the strengths of each of them.

In this study four energy storage systems (Power-to-Gas-to-Power) were analysed that allow electrolysis products to be fully utilized immediately after they are produced. For each option the electrolysis process was supplied with electricity from a wind farm during the off-peak demand periods. In the first two variants the produced hydrogen was directed to a natural gas pipeline while the third and fourth options assumed the use of hydrogen for synthetic natural gas production. All four variants assumed the use of a gas expander powered by high-temperature exhaust gases generated during gas combustion. In the first two options gas was supplied from a natural gas network while synthetic natural gas produced during methanation was used in the other two options. A characteristic feature of all systems was the combustion of gaseous fuels within a ballast-free oxidant atmosphere without nitrogen which is the fundamental component of air in conventional systems. The fifth variant was a reference for the systems equipped with gas expanders and assumed the use of fuel cells for power generation. To evaluate the individual variants the energy storage efficiency was defined and determined and the calculated overall efficiency ranged from 17.08 to 23.79% which may be comparable to fuel cells.

From an environment perspective the increased penetration of wind and solar generation in power systems is remarkable. However as the intermittent renewable generation briskly grows electrical grids are experiencing significant discrepancies between supply and demand as a result of limited system flexibility. This paper investigates the optimal sizing and control of the hydrogen energy storage system for increased utilization of renewable generation. Using a Finnish case study a mathematical model is presented to investigate the optimal storage capacity in a renewable power system. In addition the impact of demand response for domestic storage space heating in terms of the optimal sizing of energy storage is discussed. Finally sensitivity analyses are conducted to observe the impact of a small share of controllable baseload production as well as the oversizing of renewable generation in terms of required hydrogen storage size.

Hydrogen-based energy storage has the potential to compensate for the volatility of renewable power generation in energy systems with a high renewable penetration. The operation of these storage facilities can be optimized using automated energy management systems. This work presents a Reinforcement Learning-based energy management approach in the context of CO2-neutral hydrogen production and storage for an industrial combined heat and power application. The economic performance of the presented approach is compared to a rule-based energy management strategy as a lower benchmark and a Dynamic Programming-based unit commitment as an upper benchmark. The comparative analysis highlights both the potential benefits and drawbacks of the implemented Reinforcement Learning approach. The simulation results indicate a promising potential of Reinforcement Learning-based algorithms for hydrogen production planning outperforming the lower benchmark. Furthermore a novel approach in the scientific literature demonstrates that including energy and price forecasts in the Reinforcement Learning observation space significantly improves optimization results and allows the algorithm to take variable prices into account. An unresolved challenge however is balancing multiple conflicting objectives in a setting with few degrees of freedom. As a result no parameterization of the reward function could be found that fully satisfied all predefined targets highlighting one of the major challenges for Reinforcement Learning -based energy management algorithms to overcome.

For our first episode of 2022 we invited Jørn Helge Dahl Global Director of Sales&Marketing at Hexagon Purus to talk about hydrogen storage with the EAH podcast and to explain the types of solutions available today Hexagon's history and plans for the future alongside some commentary on US hydrogen strategy from the gang.

The podcast can be found on their website

Subsurface geological formations can be utilized to safely store large-scale (TWh) renewable energy in the form of green gases such as hydrogen. Successful implementation of this technology involves estimating feasible storage sites including rigorous mechanical safety analyses. Geological formations are often highly heterogeneous and entail complex nonlinear inelastic rock deformation physics when utilized for cyclic energy storage. In this work we present a novel scalable computational framework to analyse the impact of nonlinear deformation of porous reservoirs under cyclic loading. The proposed methodology includes three diferent time-dependent nonlinear constitutive models to appropriately describe the behavior of sandstone shale rock and salt rock. These constitutive models are studied and benchmarked against both numerical and experimental results in the literature. An implicit time-integration scheme is developed to preserve the stability of the simulation. In order to ensure its scalability the numerical strategy adopts a multiscale fnite element formulation in which coarse scale systems with locally-computed basis functions are constructed and solved. Further the efect of heterogeneity on the results and estimation of deformation is analyzed. Lastly the Bergermeer test case—an active Dutch natural gas storage feld—is studied to investigate the infuence of inelastic deformation on the uplift caused by cyclic injection and production of gas. The present study shows acceptable subsidence predictions in this feld-scale test once the properties of the fnite element representative elementary volumes are tuned with the experimental data.

This study discusses and thermodynamically analyzes several energy storage systems namely; pumped hydro compressed air hot water storage molten salt thermal storage hydrogen ammonia lithium-ion battery Zn-air battery redox flow battery reversible fuel cells supercapacitors and superconducting magnetic storage through the first and second law of thermodynamics. By fixing an electrical output of 100 kW for all systems the energy efficiencies obtained for the considered energy storage methods vary between 10.9% and 74.6% whereas the exergy efficiencies range between 23.1% and 71.9%. The exergy destruction rates are also calculated for each system ranging from 1.640 kW to 356 kW. The highest destruction rate is obtained for the solar-driven molten salt thermal energy storage system since it includes thermal energy conversion via the heliostat field. Furthermore the roundtrip efficiencies for the electrochemical and electromagnetic storage systems are compared with the analyzed systems ranging from 58% to 94%. Renewable sources (solar wind ocean current biomass and geothermal) energy conversion efficiencies are also considered for the final round-trip performances. The molten salt and hot water systems are applicable to solar geothermal and biomass. The highest source-to-electricity efficiency is obtained for the super magnetic storage with 37.6% when using wind ocean current and biomass sources.

The use of low-carbon hydrogen is being considered to help decarbonize several jurisdictions around the world. There may be opportunities for energy-exporting countries to supply energy-importing countries with a secure source of low-carbon hydrogen. The study objective is to assess the delivered cost of gaseous hydrogen export from Canada (a fossil-resource rich country) to the Asia-Pacific Europe and inland destinations in North America. There is a data gap on the feasibility of inter-continental export of hydrogen from an energy-producing jurisdiction to energy-consuming jurisdictions. This study is aimed at addressing this gap and includes an assessment of opportunities across the Pacific Ocean and the Atlantic Ocean based on fundamental engineering-based models. Techno-economics were used to determine the delivered cost of hydrogen to these destinations. The modelling considers energy material and capacity-sizing requirements for a five-stage supply chain comprising hydrogen production with carbon capture and storage hydrogen pipeline transportation liquefaction shipping and regasification at the destinations. The results show that the delivered cost of hydrogen to inland destinations in North America is between CAD$4.81/kg and CAD$6.03/kg to the Asia-Pacific from CAD$6.65/kg to CAD$6.99/kg and at least CAD$8.14/kg for exports to Europe. Delivering hydrogen by blending in existing long-distance natural gas pipelines reduced the delivered cost to inland destinations by 17%. Exporting ammonia to the Asia-Pacific provides cost savings of 28% compared to shipping liquified hydrogen. The developed information may be helpful to policymakers in government and the industry in making informed decisions about international trade of low-carbon hydrogen in both energy-exporting and energy-importing jurisdictions globally.