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The chances of a global hydrogen economy becoming a reality have increased significantly since the COVID pandemic and the war in Ukraine, and for net zero carbon emissions. However, intercontinental hydrogen transport is still a major issue. This study suggests transporting hydrogen as a gas at atmospheric pressure in balloons using the natural flow of wind to carry the balloon to its destination. We investigate the average wind speeds, atmospheric pressure, and temperature at different altitudes for this purpose. The ideal altitudes to transport hydrogen with balloons are 10 km or lower, and hydrogen pressures in the balloon vary from 0.25 to 1 bar. Transporting hydrogen from North America to Europe at a maximum 4 km altitude would take around 4.8 days on average. Hydrogen balloon transportation cost is estimated at 0.08 USD/kg of hydrogen, which is around 12 times smaller than the cost of transporting liquified hydrogen from the USA to Europe. Due to its reduced energy consumption and capital cost, in some locations, hydrogen balloon transportation might be a viable option for shipping hydrogen compared to liquefied hydrogen and other transport technologies. [Display omitted] • A new approach to transporting hydrogen with balloons. • Possible paths for hydrogen balloon transportation. • Estimation of the optimum altitude to transport hydrogen in balloons. • The global potential for hydrogen balloon transportation is accessed. [ABSTRACT FROM AUTHOR]

There is a significant energy transition in progress globally. This is mainly driven by the insertion of variable sources of energy, such as wind and solar power. To guarantee that the supply of energy meets its demand, energy storage technologies will play an important role in integrating these intermittent energy sources. Daily energy storage can be provided by batteries. However, there is still no technology that can provide weekly, monthly and seasonal energy storage services where pumped hydro storage is not a viable solution. Herein, we introduce an innovative energy storage proposal based on isothermal air compression/decompression and storage of the compressed air in the deep sea. Isothermal deep ocean compressed air energy storage (IDO-CAES) is estimated to cost from 1500 to 3000 USD/kW for installed capacity and 1 to 10 USD/kWh for energy storage. IDO-CAES should complement batteries, providing weekly, monthly and seasonal energy storage cycles in future sustainable energy grids, particularly in coastal areas, islands and offshore and floating wind power plants, as well as deep-sea mining activities. [ABSTRACT FROM AUTHOR]

Low-carbon energy transitions taking place worldwide are primarily driven by the integration of renewable energy sources such as wind and solar power. These variable renewable energy (VRE) sources require energy storage options to match energy demand reliably at different time scales. This article suggests using a gravitational-based energy storage method by making use of decommissioned underground mines as storage reservoirs, using a vertical shaft and electric motor/generators for lifting and dumping large volumes of sand. The proposed technology, called Underground Gravity Energy Storage (UGES), can discharge electricity by lowering large volumes of sand into an underground mine through the mine shaft. When there is excess electrical energy in the grid, UGES can store electricity by elevating sand from the mine and depositing it in upper storage sites on top of the mine. Unlike battery energy storage, the energy storage medium of UGES is sand, which means the self-discharge rate of the system is zero, enabling ultra-long energy storage times. Furthermore, the use of sand as storage media alleviates any risk for contaminating underground water resources as opposed to an underground pumped hydro storage alternative. UGES offers weekly to pluriannual energy storage cycles with energy storage investment costs of about 1 to 10 USD/kWh. The technology is estimated to have a global energy storage potential of 7 to 70 TWh and can support sustainable development, mainly by providing seasonal energy storage services. [ABSTRACT FROM AUTHOR]

The global transition to renewable energy is driven by the fight against climate change. Wind power plays a crucial role in reducing dependence on fossil fuels and greenhouse gas emissions. Therefore, addressing uncertainties in wind speed variations requires innovative solutions. This study proposes a Bayesian-based approach using a Dynamic Factor Model to generate synthetic monthly average wind speed series. The Dynamic Factor Model framework captures temporal and spatial correlations, improving wind resource representation in operational planning models. The model's autoregressive configuration with common factors, prior distributions, and Bayesian inference techniques enhances predictive capabilities. Validation exercises confirm the model's reliability, accurately capturing seasonal oscillations and spatial correlations across eight wind farms. The study highlights the usefulness of the Dynamic Factor Model in evaluating wind projects and optimizing energy generation strategies, effectively mitigating wind uncertainty, and facilitating renewable energy integration in Brazil's power mix. [ABSTRACT FROM AUTHOR]