Publications

This study explores the integration and optimization of battery energy storage systems (BESSs) and hydrogen energy storage systems (HESSs) within an energy management system (EMS) using Kangwon National University’s Samcheok campus as a case study. This research focuses on designing BESSs and HESSs with specific technical specifications such as energy capacities and power ratings and their integration into the EMS. By employing MATLAB-based simulations this study analyzes energy dynamics grid interactions and load management strategies under various operational scenarios. Real-time data from the campus are utilized to examine energy consumption renewable energy generation grid power fluctuations and pricing dynamics providing key insights for system optimization. This study finds that a BESS manages energy fluctuations between 0.5 kWh and 3.7 kWh over a 24 h period with battery power remaining close to 4 W for extended periods. Grid power fluctuates between −5 kW and 75 kW while grid prices range from 75 to 120 USD/kWh peaking at 111 USD/kWh. Hydrogen energy storage varies from 1 kWh to 8 kWh with hydrogen power ranging from −40 kW to 40 kW. Load management keeps power stable at around 35 kW and PV power integration peaks at 48 kW by the 10th h. The findings highlight that BESSs and HESSs effectively manage energy distribution and storage improving system efficiency reducing energy costs by approximately 15% and enhancing grid stability by 20%. This study underscores the potential of BESSs and HESSs in stabilizing grid operations and integrating renewable energy. Future directions include advancements in storage technologies enhanced EMS capabilities through artificial intelligence and machine learning and the development of smart grid infrastructures. Policy recommendations stress the importance of regulatory support and stakeholder collaboration to drive innovation and scale deployment ensuring a sustainable energy future.

The road transport sector is one of the major contributors to greenhouse gas emissions as it still largely relies on traditional powertrain solutions. While some progress has been made in the passenger car sector with the diffusion of battery electric vehicles heavy-duty transport remains predominantly dependent on diesel internal combustion engines. This research aims to evaluate and compare three potential solutions for the decarbonisation of heavy-duty freight transport from an economic perspective: Battery Electric Trucks (BETs) Fuel Cell Electric Trucks (FCETs) and Hydrogen-fuelled Internal Combustion Engine Trucks (H2ICETs). The study focuses on the Finnish market and road network where affordable and low-carbon electricity creates an ideal environment for the development of alternative powertrain vehicles. The analysis employs the Total Cost of Ownership (TCO) method which allows for a comprehensive assessment of all cost components associated with the vehicles throughout their entire lifecycle encompassing both initial expenses and operational costs. Among the several factors affecting the results the impact of the three powertrain technologies on the admissible payloads has been taken into account. The study specifically focuses on the costs directly incurred by the truck owner. Additionally to evaluate the cost effectiveness of the proposed powertrain technologies under different scenarios a sensitivity analysis on electricity and hydrogen prices is conducted. The outcomes of this study reveal that no single powertrain solution emerges as universally optimal as the most cost-effective choice depends strongly on the truck type and its use (i.e. daily mileage). For relatively small trucks (18 t) covering short driving distances (approximately 100 to 200 km/day) BETs prove to be the best solution due to their higher efficiency and lower vehicle costs compared to FCETs. Conversely for larger trucks (42 and 76 t) engaged in longer hauls (>300 km/day) H2ICETs exhibit larger cost benefits due to their lower vehicle costs among the three options under investigation. Finally for small trucks (18 t) travelling long distances (200 km/day or more) FCETs represent a competitive choice due to their high efficiency and costeffective energy storage system. Considering future advancements in FCETs and BETs in terms of improved performance and reduced investment cost the fuel cell-based solution is expected to emerge as the best option across various combinations of truck sizes and daily mileages.

In this study the Bald Eagle Search Algorithm performed hydrogen consumption and battery cycle optimization of a fuel cell electric vehicle. To save time and cost the digital vehicle model created in Matlab/Simulink and validated with real-world driving data is the main platform of the optimization study. The digital vehicle model was run with the minimum and maximum battery charge states determined by the Bald Eagle Search Algorithm and hydrogen consumption and battery cycle values were obtained. By using the algorithm and digital vehicle model together hydrogen consumption was minimized and range was increased. It was aimed to extend the life of the parts by considering the battery cycle. At the same time the number of battery packs was included in the optimization and its effect on consumption was investigated. According to the study results the total hydrogen consumption of the fuel cell electric vehicle decreased by 57.8% in the hybrid driving condition 23.3% with two battery packs and 36.27% with three battery packs in the constant speed driving condition.

Fuel cell electric vehicles (FCEVs) have received significant attention in recent times due to various advantageous features such as high energy efficiency zero emissions and extended driving range. However FCEVs have some drawbacks including high production costs; limited hydrogen refueling infrastructure; and the complexity of converters controllers and method execution. To address these challenges smart energy management involving appropriate converters controllers intelligent algorithms and optimizations is essential for enhancing the effectiveness of FCEVs towards sustainable transportation. Therefore this paper presents emerging energy management strategies for FCEVs to improve energy efficiency system reliability and overall performance. In this context a comprehensive analytical assessment is conducted to examine several factors including research trends types of publications citation analysis keyword occurrences collaborations influential authors and the countries conducting research in this area. Moreover emerging energy management schemes are investigated with a focus on intelligent algorithms optimization techniques and control strategies highlighting contributions key findings issues and research gaps. Furthermore the state-of-the-art research domains of FCEVs are thoroughly discussed in order to explore various research domains relevant outcomes and existing challenges. Additionally this paper addresses open issues and challenges and offers valuable future research opportunities for advancing FCEVs emphasizing the importance of suitable algorithms controllers and optimization techniques to enhance their performance. The outcomes and key findings of this review will be helpful for researchers and automotive engineers in developing advanced methods control schemes and optimization strategies for FCEVs towards greener transportation.

Hydrogen is a promising fuel because it has good capabilities to operate gas turbines. Due to its ignition speed which exceeds the ignition of traditional fuel it achieves a higher thermal efficiency while the resulting emissions are low. So it was used as a clean and sustainable energy source. This paper reviews the most important research that was concerned with studying the characteristics of hydrogen combustion within incinerators and power generation equipment where hydrogen was used as a fuel mixed with traditional fuel in the combustion chambers of gas turbines. It also includes an evaluation of the combustion processes and flame formation resulting from the enrichment of gaseous fuels with hydrogen and partial oxidation. A large amount of theoretical and experimental work in this field has been reviewed. This review summarizes the predictive and experimental results of various research interests in the field of hydrogen combustion and also production.

This article presents a 3D model of a yellow hydrogen generation system that uses the electricity produced by a photovoltaic carport. The 3D models of all key system components were collected and their characteristics were described. Based on the design of the 3D model of the photovoltaic carport the amount of energy produced monthly was determined. These quantities were then applied to determine the production of low-emission hydrogen. In order to increase the amount of low-emission hydrogen produced the usage of a stationary energy storage facility was proposed. The Metalog family of probability distributions was adopted to develop a strategic model for low-emission hydrogen production. The hydrogen economy of a company that uses small amounts of hydrogen can be based on such a model. The 3D modeling and calculations show that it is possible to design a compact low-emission hydrogen generation system using rapid prototyping tools including the photovoltaic carport with an electrolyzer placed in the container and an energy storage facility. This is an effective solution for the climate and energy transition of companies with low hydrogen demand. In the analytical part the Metalog probability distribution family was employed to determine the amount of monthly energy produced by 6.3 kWp photovoltaic systems located in two European countries: Poland and Italy. Calculating the probability of producing specific amounts of hydrogen in two European countries is an answer to a frequently asked question: In which European countries will the production of low-emission hydrogen from photovoltaic systems be the most profitable? As a result of the calculations for the analyzed year 2023 in Poland and Italy specific answers were obtained regarding the probability of monthly energy generation and monthly hydrogen production. Many companies from Poland and Italy are taking part in the European competition to create hydrogen banks. Only those that offer low-emission hydrogen at the lowest prices will receive EU funding.

A proton exchange membrane electrolyzer can effectively utilize the electricity generated by intermittent solar power. Different methods of generating electricity may have different efficiencies and hydrogen production rates. Two coupled systems namely PV/T- and CPV/T-coupling PEMEC respectively are presented and compared in this study. A maximum power point tracking algorithm for the photovoltaic system is employed and simulations are conducted based on the solar irradiation intensity and ambient temperature of a specific location on a particular day. The simulation results indicate that the hydrogen production is relatively high between 11:00 and 16:00 with a peak between 12:00 and 13:00. The maximum hydrogen production rate is 99.11 g/s and 29.02 g/s for the CPV/T-PEM and PV/T-PEM systems. The maximum energy efficiency of hydrogen production in CPV/T-PEM and PV/T-PEM systems is 66.7% and 70.6%. Under conditions of high solar irradiation intensity and ambient temperature the system demonstrates higher total efficiency and greater hydrogen production. The CPV/T-PEM system achieves a maximum hydrogen production rate of 2240.41 kg/d with a standard coal saving rate of 15.5 tons/day and a CO2 reduction rate of 38.0 tons/day. Compared to the PV/T-PEM system the CPV/T-PEM system exhibits a higher hydrogen production rate. These findings provide valuable insights into the engineering application of photovoltaic/thermal-coupled hydrogen production technology and contribute to the advancement of this field.

The transition from traditional petrol-based combustion engines to hydrogen-powered systems represents a promising advancement in sustainable and clean energy solutions. This review paper explores the intricacies of converting a conventional internal combustion engine to operate on hydrogen gas. Key topics include the performance limitations of hydrogen engines the role of water injection in combustion modulation and the investigation of direct injection and port injection systems. This review also examines challenges associated with lean and rich mixtures risks of backfire and pre-ignition and the conversion’s overall impact on engine performance and longevity. Additionally this paper discusses hydrogen lubrication to prevent mechanical wear and addresses emission-related considerations.

Hydrogen has emerged as a promising alternative to meet the growing demand for sustainable and renewable energy sources. Underground hydrogen storage (UHS) in depleted gas reservoirs holds significant potential for large-scale energy storage and the seamless integration of intermittent renewable energy sources due to its capacity to address challenges associated with the intermittent nature of renewable energy sources ensuring a steady and reliable energy supply. Leveraging the existing infrastructure and well-characterized geological formations depleted gas reservoirs offer an attractive option for large-scale hydrogen storage implementation. However significant knowledge gaps regarding storage performance hinder the commercialization of UHS operation. Hydrogen deliverability hydrogen trapping and the equation of state are key areas with limited understanding. This literature review critically analyzes and synthesizes existing research on hydrogen storage performance during underground storage in depleted gas reservoirs; it then provides a high-level risk assessment and an overview of the techno-economics of UHS. The significance of this review lies in its consolidation of current knowledge highlighting unresolved issues and proposing areas for future research. Addressing these gaps will advance hydrogen-based energy systems and support the transition to a sustainable energy landscape. Facilitating efficient and safe deployment of UHS in depleted gas reservoirs will assist in unlocking hydrogen’s full potential as a clean and renewable energy carrier. In addition this review aids policymakers and the scientific community in making informed decisions regarding hydrogen storage technologies.

Hydrogen production and storage in hybrid systems is a promising solution for sustainable energy transition decoupling the energy generation from its end use and boosting the deployment of renewable energy. Nonetheless the optimal and cost-effective design of hybrid hydrogen-based systems is crucial to tackle existing limitations in diffusion of these systems. The present study explores net-zero energy management via a multi-objective optimization algorithm for an outdoor test facility equipped with a hydrogen-based hybrid energy production system. Aimed at enabling efficient integration of hydrogen fuel cell system the proposed solution attempts to maximize the renewable factor (RF) and carbon mitigation in the hybrid system as well as to minimize the grid dependency and the life cycle cost (LCC) of the system. In this context the techno-enviroeconomic optimization of the hybrid system is conducted by employing a statistical approach to identify optimal design variables and conflictive objective functions. To examine interactions in components of the hybrid system a series of dynamic simulations are carried out by developing a TRNSYS code coupled with the OpenStudio/EnergyPlus plugin. The obtained results indicate a striking disparity in the monthly RF values as well as the hydrogen production rate and therefore in the level of grid dependency. It is shown that the difference in LCC between optimization scenarios suggested by design of experiments could reach $15780 corresponding to 57% of the mean initial cost. The LCOE value yielded for optimum scenarios varies between 0.389 and 0.537 $/kWh. The scenario with net-zero target demonstrates the lowest LCOE value and the highest carbon mitigation i.e. 828 kg CO2/yr with respect to the grid supply case. However the LCC in this scenario exceeds $57370 which is the highest among all optimum scenarios. Furthermore it was revealed that the lowest RF in optimal scenarios is equal to 66.2% and belongs to the most economical solution.