Review of water electrolysis technologies and design of renewable hydrogen production systems

An electric system based on renewable energy faces challenges concerning the storage and utilization of energy due to the intermittent and seasonal nature of renewable energy sources. Wind and solar photovoltaic power productions are variable and difficult to predict, and thus electricity storage will be needed in the case of basic power production. Hydrogen’s energetic potential lies in its ability and versatility to store chemical energy, to serve as an energy carrier and as feedstock for various industries. Hydrogen is also used e.g. in the production of biofuels. The amount of energy produced during hydrogen combustion is higher than any other fuel’s on a mass basis with a higher-heating-value of 39.4 kWh/kg. However, even though hydrogen is the most abundant element in the universe, on Earth most hydrogen exists in molecular forms such as water. Therefore, hydrogen must be produced and there are various methods to do so. Today, the majority hydrogen comes from fossil fuels, mainly from steam methane reforming, and only about 4 % of global hydrogen comes from water electrolysis. Combination of electrolytic production of hydrogen from water and supply of renewable energy is attracting more interest due to the sustainability and the increased flexibility of the resulting energy system. The preferred option for intermittent hydrogen storage is pressurization in tanks since at ambient conditions the volumetric energy density of hydrogen is low, and pressurized tanks are efficient and affordable when the cycling rate is high. Pressurized hydrogen enables energy storage in larger capacities compared to battery technologies and additionally the energy can be stored for longer periods of time, on a time scale of months. In this thesis, the thermodynamics and electrochemistry associated with water electrolysis are described. The main water electrolysis technologies are presented with state-of-the-art specifications. Finally, a Power-to-Hydrogen infrastructure design for Lappeenranta University of Technology is presented. Laboratory setup for water electrolysis is specified and factors affecting its commissioning in Finland are presented.

Activity-based life cycle costing model for cost estimation and monitoring – Case: manned and autonomous dry bulk carrier

Recent developments in automation, robotics and artificial intelligence have given a push to a wider usage of these technologies in recent years, and nowadays, driverless transport systems are already state-of-the-art on certain legs of transportation. This has given a push for the maritime industry to join the advancement. The case organisation, AAWA initiative, is a joint industry-academia research consortium with the objective of developing readiness for the first commercial autonomous solutions, exploiting state-of-the-art autonomous and remote technology. The initiative develops both autonomous and remote operation technology for navigation, machinery, and all on-board operating systems. The aim of this study is to develop a model with which to estimate and forecast the operational costs, and thus enable comparisons between manned and autonomous cargo vessels. The building process of the model is also described and discussed. Furthermore, the model’s aim is to track and identify the critical success factors of the chosen ship design, and to enable monitoring and tracking of the incurred operational costs as the life cycle of the vessel progresses. The study adopts the constructive research approach, as the aim is to develop a construct to meet the needs of a case organisation. Data has been collected through discussions and meeting with consortium members and researchers, as well as through written and internal communications material. The model itself is built using activity-based life cycle costing, which enables both realistic cost estimation and forecasting, as well as the identification of critical success factors due to the process-orientation adopted from activity-based costing and the statistical nature of Monte Carlo simulation techniques. As the model was able to meet the multiple aims set for it, and the case organisation was satisfied with it, it could be argued that activity-based life cycle costing is the method with which to conduct cost estimation and forecasting in the case of autonomous cargo vessels. The model was able to perform the cost analysis and forecasting, as well as to trace the critical success factors. Later on, it also enabled, albeit hypothetically, monitoring and tracking of the incurred costs. By collecting costs this way, it was argued that the activity-based LCC model is able facilitate learning from and continuous improvement of the autonomous vessel. As with the building process of the model, an individual approach was chosen, while still using the implementation and model building steps presented in existing literature. This was due to two factors: the nature of the model and – perhaps even more importantly – the nature of the case organisation. Furthermore, the loosely organised network structure means that knowing the case organisation and its aims is of great importance when conducting a constructive research.