Applications & Pathways

The shipping industry aims to achieve full decarbonization at the European Union (EU) level by mid-century. Over the past decade various alternative fuels have been explored to address this goal. However challenges such as insufficient bunkering infrastructure technological immaturity and high costs have made shipowners hesitant to invest in“clean” propulsion systems. This study conducts a bibliometric analysis supported by a systematic literature review to map and critically synthesize current knowledge on alternative fuels for ferry decarbonization and their alignment with emissions reduction policies. Using the Greek ferry fleet as a representative case study the paper evaluates the regulatory framework and technical characteristics of various fuel options and examines their compatibility with different vessel categories. A qualitative comparative framework is introduced to link policy types with alternative fuel pathways offering original insights into policy—fuel alignment. The findings highlight methanol and green electricity (battery-electric systems) as highly promising solutions especially if battery technologies further advance in the coming years. Hydrogen also presents significant potential but is currently limited by high production costs and infrastructure requirements. Rather than presenting a quantitative decision-making model this review establishes the conceptual basis for such a framework in future research. This paper also offers innovative proposals to accelerate the adoption of zero-emission fuels addresses key gaps in existing research and provides insights for advancing ferry decarbonization.

Hydrogen-rich gas (HRG) injection is a promising low-carbon solution for blast furnace ironmaking. This study conducted numerical simulations in the lower part of a blast furnace to analyze the combustion behavior of coinjected coke oven gas (COG) and pulverized coal (PC) within the raceway and the associated thermal load on the tuyere. A three-dimensional computational fluid dynamics model incorporating fluid–thermal–solid coupling and the GRI-Mech 3.0 chemical kinetic mechanism (validated for 300–2500 K) was established to simulate the lance–blowpipe–tuyere–raceway region. The simulation results revealed that moderate COG injection accelerated volatile release from PC and enlarged the high-temperature zone (>2000 K). However excessive COG injection intensified oxygen competition and shortened the residence time of PC ultimately decreasing the burnout rate. Notably although COG has high reactivity its injection did not cause an increase in tuyere temperature. By contrast the presence of an unburned gas layer near the upper wall of the tuyere and the existence of a strong convective cooling effect contributed to a reduction in tuyere temperature. An optimized cooling water channel was designed to enhance flow distribution and effectively suppress localized overheating. The findings of this study offer valuable technical insights for ensuring safe COG injection and advancing low-carbon steelmaking practices.

Reliable operation of proton exchange membrane fuel cells (PEMFCs) is crucial for their widespread commercialization and accurate fault diagnosis is the key to ensuring their long-term stable operation. However traditional fault diagnosis methods not only lack sufficient interpretability making it difficult for users to trust their diagnostic decisions but also one-dimensional (1D) feature extraction methods highly rely on manual experience to design and extract features which are easily affected by noise. This paper proposes a new interpretable fault diagnosis algorithm that integrates Gramian angular field (GAF) transform convolutional neural network (CNN) and gradient-weighted class activation mapping (Grad-CAM) for enhanced fault diagnosis and analysis of proton exchange membrane fuel cells. The algorithm is systematically validated using experimental data to classify three critical health states: normal operation membrane drying and hydrogen leakage. The method first converts the 1D sensor signal into a two-dimensional GAF image to capture the temporal dependency and converts the diagnostic problem into an image recognition task. Then the customized CNN architecture extracts hierarchical spatiotemporal features for fault classification while Grad-CAM provides visual explanations by highlighting the most influential regions in the input signal. The results show that the diagnostic accuracy of the proposed model reaches 99.8% which is 4.18% 9.43% and 2.46% higher than other baseline models (SVM LSTM and CNN) respectively. Furthermore the explainability analysis using Grad-CAM effectively mitigates the “black box” problem by generating visual heatmaps that pinpoint the key feature regions the model relies on to distinguish different health states. This validates the model’s decision-making rationality and significantly enhances the transparency and trustworthiness of the diagnostic process.

As a zero-carbon energy carrier hydrogen is playing an increasingly vital role in the decarbonization of maritime transportation. The hydrogen pressure reducing valve (PRV) is a core component of ship-borne hydrogen storage systems directly influencing the safety efficiency and reliability of hydrogen-powered vessels. However the marine environment— characterized by persistent vibrations salt spray corrosion and temperature fluctuations— poses significant challenges to PRV performance including material degradation flow instability and reduced operational lifespan. This review comprehensively summarizes and analyzes recent advances in the study of high-pressure hydrogen PRVs for marine applications with a focus on transient flow dynamics turbulence and compressible flow characteristics multi-stage throttling strategies and valve core geometric optimization. Through a systematic review of theoretical modeling numerical simulations and experimental studies we identify key bottlenecks such as multi-physics coupling effects under extreme conditions and the lack of marine-adapted validation frameworks. Finally we conducted a preliminary discussion on future research directions covering aspects such as the construction of coupled multi-physics field models the development of marine environment simulation experimental platforms the research on new materials resistant to vibration and corrosion and the establishment of a standardized testing system. This review aims to provide fundamental references and technical development ideas for the research and development of high-performance marine hydrogen pressure reducing valves with the expectation of facilitating the safe and efficient application and promotion of hydrogen-powered shipping technology worldwide.

The hybrid energy storage system (HESS) that combines battery with hydrogen storage exploits complementary power/energy characteristics but most studies optimize capacity and operation separately leading to suboptimal overall performance. To address this issue this paper proposes a bi-level co-optimization framework that integrates deep reinforcement learning (DRL) and mixed integer programming (MIP). The outer layer employs the TD3 algorithm for capacity configuration while the inner layer uses the Gurobi solver for optimal operation under constraints. On a standalone PV–wind–load-HESS system the method attains near-optimal quality at dramatically lower runtime. Relative to GA + Gurobi and PSO + Gurobi the cost is lower by 4.67% and 1.31% while requiring only 0.52% and 0.58% of their runtime; compared with a direct Gurobi solve the cost remains comparable while runtime decreases to 0.07%. Sensitivity analysis further validates the model’s robustness under various cost parameters and renewable energy penetration levels. These results indicate that the proposed DRL–MIP cooperation achieves near-optimal solutions with orders of magnitude speedups. This study provides a new DRL–MIP paradigm for efficiently solving strongly coupled bi-level optimization problems in energy systems.

The urgent global transition toward low-carbon energy systems has highlighted the need for systematic planning of hydrogen refueling stations (HRS) to facilitate clean energy adoption. This study develops an integrated framework for regional HRS layout optimization and carbon emission assessment considering population distribution land area and hydrogen demand. Using Hainan Province as a case study the model estimates regional hydrogen demand determines optimal HRS deployment evaluates spatial coverage and refueling distances and quantifies potential carbon emission reductions under various renewable energy scenarios. Model validation with Haikou demonstrates its reliability and applicability at the regional scale. Results indicate pronounced spatial disparities in hydrogen demand and infrastructure requirements emphasizing that prioritizing station deployment in densely populated urban areas can enhance accessibility and maximize emission reduction. The framework offers a practical data-efficient tool for policymakers and planners to guide early-stage hydrogen infrastructure development and supports strategies for regional decarbonization and sustainable energy transitions.

While community energy initiatives and pilot projects have demonstrated technical feasibility and economic benefits their site-specific nature limits transferability to systematic scalable investment models. This study addresses this gap by proposing a modular framework for Renewable Energy Valleys (REVs) developed from real-world Community Energy Lab (CEL) demonstrations in Crete Greece which is an island with pronounced seasonal demand fluctuation strong renewable potential and ongoing hydrogen valley initiatives. Four modular business schemes are defined each representing different sectoral contexts by combining a baseline of 50 residential units with one representative large consumer (hotel rural households with thermal loads municipal swimming pool or hydrogen bus). For each scheme a mixed-integer linear programming model is applied to optimally size and operate integrated solar PV wind battery (BAT) energy storage and hydrogen systems across three renewable energy penetration (REP) targets: 90% 95% and 99.9%. The framework incorporates stochastic demand modeling sector coupling and hierarchical dispatch schemes. Results highlight optimal technology configurations that minimize dependency on external sources and curtailment while enhancing reliability and sustainability under Mediterranean conditions. Results demonstrate significant variation in optimal configurations across sectors and targets with PV capacity ranging from 217 kW to 2840 kW battery storage from 624 kWh to 2822 kWh and hydrogen systems scaling from 65.2 kg to 192 kg storage capacity. The modular design of the framework enables replication beyond the specific context of Crete supporting the scalable development of Renewable Energy Valleys that can adapt to diverse sectoral mixes and regional conditions.

Driven by carbon neutrality goals electric–hydrogen coupled virtual power plants (EHCVPPs) integrate renewable hydrogen production with power system flexibility resources emerging as a critical technology for large-scale renewable integration. As distributed energy resources (DERs) within EHCVPPs diversify heterogeneous resources generate diversified market values. However inadequate benefit allocation mechanisms risk reducing participation incentives destabilizing cooperation and impairing operational efficiency. To address this benefit allocation must balance fairness and efficiency by incorporating DERs’ regulatory capabilities risk tolerance and revenue contributions. This study proposes a multi-stage benefit allocation framework incorporating risk–reward tradeoffs and an enhanced optimization model to ensure sustainable EHCVPP operations and scalability. The framework elucidates bidirectional risk–reward relationships between DERs and EHCVPPs. An individualized risk-adjusted allocation method and correction mechanism are introduced to address economic-centric inequities while a hierarchical scheme reduces computational complexity from diverse DERs. The results demonstrate that the optimized scheme moderately reduces high-risk participants’ shares increasing operator revenue by 0.69% demand-side gains by 3.56% and reducing generation-side losses by 1.32%. Environmental factors show measurable yet statistically insignificant impacts. The framework meets stakeholders’ satisfaction and minimizes deviation from reference allocations.

During the critical period of energy transition the collaborative optimization of the electricity-hydrogentransportation coupling system is of vital importance for achieving efficient energy utilization and sustainable development.This paper proposes a collaborative operation mechanism of Distributed Robust Optimization (DRO) considering carbon emissions. Firstly a Stackelberg game dynamic pricing strategy is constructed for the integrated energy station (IES) and the electricity-hydrogen hybrid charging station (HRS) where the upper-level IES optimizes the electricity price setting strategy and the lower-level HRS dynamically adjusts the electricity purchase-hydrogen production plan. Secondly the Wasserstein distance is used to describe the uncertainties of hydrogen vehicle loads and wind-solar power generation and a bisection algorithm-column constraint generation (BA-C&CG) hybrid algorithm is designed to solve the model. Finally the numerical example verification shows that the daily operation cost of HRS under the proposed mechanism is as low as 1108.53 EUR which is 10.58 % and 7.38 % lower than that of the commonly used stochastic optimization (SO) and robust optimization (RO) respectively. The variance analysis (F = 536.05P < 0.001) confirms that the cost advantage is statistically significant. In terms of carbon emission reduction effect the DRO-Stackelberg game model has the lowest daily carbon cost (6.98EUR). This mechanism effectively balances the economic and robustness of the system and the single dispatch calculation time is only 112.09 s meeting the real-time operation requirements of engineering. It provides technical support for the low-carbon collaborative operation of the electricity-hydrogen-transportation coupling system.

With the IMO’s 2050 decarbonization target hydrogen is a key zero-carbon fuel for shipping but the lack of systematic risk assessment methods for hydrogen-powered marine propulsion systems (under harsh marine conditions) hinders its large-scale application. To address this gap this study proposes an integrated risk evaluation framework by fusing Failure Mode Effects and Criticality Analysis (FMECA) with the Fuzzy Analytic Hierarchy Process (FAHP)—resolving the limitation of traditional single evaluation tools and adapting to the dynamic complexity of marine environments. Scientific findings from this framework confirm that hydrogen leakage high-pressure storage tank valve leakage and inverter overload are the three most critical failure modes with hydrogen leakage being the primary risk source due to its high severity and detection difficulty. Further hazard matrix analysis reveals two key risk mechanisms: one type of failure (e.g. insufficient hydrogen concentration) features “high severity but low detectability” requiring real-time monitoring; the other (e.g. distribution board tripping) shows “high frequency but controllable impact” calling for optimized operations. This classification provides a theoretical basis for precise risk prevention. Targeted improvement measures (e.g. dual-sealed valves redundant cooling circuits AI-based regulation) are proposed and quantitatively validated reducing the system’s overall risk value from 4.8 (moderate risk) to 1.8 (low risk). This study’s core contribution lies in developing a universally applicable scientific framework for marine hydrogen propulsion system risk assessment. It not only fills the methodological gap in traditional evaluations but also provides a theoretical basis for the safe promotion of hydrogen shipping supporting the scientific realization of the IMO’s decarbonization goal.

Liquid hydrogen (LH2) is a promising candidate for zero emission aviation but its cryogenic properties make the refuelling process fundamentally different from that of conventional jet fuels. Although previous studies have addressed LH2 storage and system integration detailed modelling of the refuelling process remains limited. This paper presents the first part of a two-part study focused on simulation of the refuelling process for an LH2-powered commercial aircraft. An existing tank model is substantially modified to more accurately capture relevant physical phenomena including heat transfer and droplet dynamics during top-fill spray injection. Newly available experimental data on LH2 no-vent filling enables direct validation of the model under conditions that match the experimental setup. A sensitivity analysis identifies the most influential parameters that affect model precision including loss coefficient droplet diameter radiative heat ingress and vent-closing pressure. The validated model forms the basis for Part 2 of this study in which it is applied to a representative LH2-powered commercial aircraft to simulate refuelling times quantify venting losses and assess the impact of key operational settings. These results support the design of efficient LH2 refuelling systems for future aircraft and airport infrastructure.

Hydrogen’s increasing potential as an alternative fuel for heavy-duty transport has led to the conversion of conventional diesel compression-ignition engines to spark-ignition hydrogen operation. Hydrogen’s broad flammability range enables leaner operation achieving both higher engine efficiency and near-zero emissions. In particular direct injection hydrogen combustion improves volumetric efficiency and reduces problems including pre-ignition and knock related to hydrogen port-fuel injection. In the present work we performed an optical investigation of direct injection (DI) hydrogen combustion under leaner mixture conditions. The study was conducted using a heavy-duty optical diesel engine modified for spark-ignition operation. Bottom-view natural flame luminosity and OH-PLIF imaging were conducted along with in-cylinder pressure measurements. Experiments were conducted at three air-excess ratios (3 3.4 and 3.8) with spark timings (ST) varied from − 15 ◦CA aTDC to − 30 ◦CA aTDC. Hydrogen injection ended at − 30 ◦CA aTDC with the start of injection adjusted accordingly to achieve the desired lambda conditions. The maximum IMEPg corresponded to the lowest COV of the IMEPg indicating optimal spark timing for lean DI hydrogen combustion. The optimized spark timing for λ = 3 λ = 3.4 and λ = 3.8 were occurred at − 25 ◦CA aTDC − 25 ◦CA aTDC and − 30 ◦CA aTDC respectively. The corresponding COV of IMEPg values were below 5 % indicating stable combustion. The flame kernel first initiates at the spark plug and then propagates toward the piston’s outer boundary however the flame propagation does not remain as a continuous front unlike port-fuel injected hydrogen combustion. The effect of fuel stratification is evident in combustion luminosity and OH-PLIF images showing pockets of varying intensity within the combustion chamber. Natural flame luminosity images reveal incomplete flame coverage and asymmetric combustion emphasizing the need for metal engine experiments to further quantify the unburned hydrogen and associated combustion losses.

The growing concern about the increase in European Union (EU)’s total CO2 emissions due to maritime activities and the ambitious goal of net zero emissions they are asked to fulfil by 2050 are leading the way to the adoption of new sustainable strategies. In this article a novel methodology for the classification of the sustainable actions is proposed. Moreover new indicators have been designed to compare the level of sustainable development of each port. Among them a new coefficient for the assessment of the Ports’ Potential Sustainability (PPS) have been designed. Main results showed that 56% of the actions were in the improvement and environmentally sustainable group while 19% were shift-economic actions related to the installation of technologies. As a matter of the fact all European ports under analysis have adopted cold ironing system which can reduce up to 4% of the global shipping emissions. Similarly 50% of them have already integrated renewables energies and prioritize equipment electrification in their processes. Finally the most relevant projects to optimize the energy consumption of daily operations and the main challenges that still need to be addressed have been analyzed showing the current trends maritime sector is undertaking to advance towards the sustainable development.

The last decade has been characterized by a growing environmental awareness and the rise of climate change concerns. Continuous advancement of renewable energy technologies in this context has taken a central stage on the global agenda leading to a diverse array of innovations ranging from cutting-edge green energy production technologies to advanced energy storage solutions. In this evolving context ensuring the sustainability of energy systems—through the reduction of carbon emissions enhancement of energy resilience and responsible resource integration—has become a primary objective of modern energy planning. The integration of hydrogen technologies for power-to-gas (P2G) and power-topower (P2P) and energy storage systems is one of the areas where the most remarkable progress is being made. However real case implementations are lagging behind expectations due to large-scale investments needed which under high energy price uncertainty act as a barrier to widespread adoption. This study proposes a risk-averse approach for sizing an Integrated Hybrid Energy System considering the uncertainty of electricity and gas prices. The problem is formulated as a mixed-integer program and tested on a real-world case study. The analysis sheds light on the value of synergies and innovative solutions that hold the promise of a cleaner more sustainable future for generations to come.

Contemporary research into decarbonized fuels such as H2/NH3 has highlighted complex challenges with applied combustion with marked changes in thermochemical properties leading to significant issues such as limited operational range flashback and instability particularly when attempts are made to optimize emissions production in conventional lean-premixed systems. Non-premixed configurations may address some of these issues but often lead to elevated NOx production particularly when ammonia is retained in the fuel mixture. Optimized fuel injection and blending strategies are essential to mitigate these challenges. This study investigates the application of a 75 %/25 %mol H2/NH3 blend in a swirl-stabilized combustor operated at elevated conditions of inlet temperature (500 K) and ambient pressure (0.11–0.6 MPa). A complex nonmonotonic relationship between swirl number and increasing ambient combustor pressure is demonstrated highlighting the intricate interplay between swirling flow structures and reaction kinetics which remains poorly understood. At medium swirl (SN = 0.8) an increase in pressure initially reduces NO emissions diminishing past ~0.3 MPa with an opposing trend evident for high swirl (SN = 2.0) as NO emissions fall rapidly when combustor pressure approaches 0.6 MPa. High-fidelity numerical modeling is presented to elucidate these interactions in detail. Numerical data generated using Detached Eddy Simulations (DES) were validated against experimental results to demonstrate a change in flame anchoring on the axial shear layer and marked change in recirculated flow structure successfully capturing the features of higher swirl number flows. Favorable comparisons are made with optical data and a reduction in NO emissions with increasing pressure is demonstrated to replicate changes to the swirling flame chemical kinetics. Findings provide valuable insights into the combustion behavior of hydrogen-rich ammonia flames contributing to the development of cleaner combustion technologies.

While renewable energy deployment has accelerated in recent years fossil fuels continue to play a dominant role in electricity generation worldwide. This necessitates the development of transitional strategies to mitigate greenhouse gas emissions from this sector while gradually reducing reliance on fossil fuels. This study investigates the potential of blending green hydrogen with natural gas as a transitional solution to decarbonize Jordan’s electricity sector. The research presents a comprehensive techno-economic and environmental assessment evaluating the compatibility of the Arab Gas Pipeline and major power plants with hydrogen–natural gas mixtures considering blending limits energy needs environmental impacts and economic feasibility under Jordan’s 2030 energy scenario. The findings reveal that hydrogen blending between 5 and 20 percent can be technically achieved without major infrastructure modifications. The total hydrogen demand is estimated at 24.75 million kilograms per year with a reduction of 152.7 thousand tons of carbon dioxide per annum. This requires 296980 cubic meters of water per year equivalent to only 0.1 percent of the National Water Carrier’s capacity indicating a negligible impact on national water resources. Although technically and environmentally feasible the project remains economically constrained requiring a carbon price of $1835.8 per ton of carbon dioxide for economic neutrality.

The increasing penetration of renewable energy sources in power systems poses significant challenges for maintaining grid reliability mainly due to the variability and uncertainty of solar and demand profiles. Microgrids equipped with diverse storage technologies have emerged as a promising solution to address these issues.This paper proposes an integrated day-ahead and real-time power scheduling approach for grid-connected microgrids equipped with both conventional and hydrogen-based ESSs. While existing strategies often address day-ahead and real-time scheduling separately or rely on a single storage technology this work introduces a unified framework that exploits the complementary characteristics of batteries and hydrogen systems. The proposed approach is based on a novel two-stage stochastic optimization model embedded within a hierarchical optimization framework to address these two intertwined problems efficiently. For the day-ahead scheduling a two-stage stochastic programming energy management model is solved to optimize the microgrid schedule based on forecasted load demand and PV production profiles. Building upon the day-ahead schedule another optimization model is solved which addresses real-time power imbalances caused by deviations in actual PV production and load demand power profiles with respect to the forecasted ones with the aim of minimizing operational disruptions. Simulation results demonstrate the validity of the proposed approach achieving both cost reductions and minimal power imbalances. By dynamically adjusting energy flows and using both conventional batteries and hydrogen systems the proposed approach ensures improved reliability reduced operational costs and enhanced integration of RES in microgrids. These findings highlight the potential of the proposed hierarchical framework to support the large-scale deployment of RES while ensuring resilient and cost-effective microgrid operations.

Achieving net zero by 2050 will require decarbonising stand-alone energy applications. Hydrogen is increasingly viewed as a promising energy carrier but its economic viability remains uncertain due to the lack of consensus on future demand and limited deployment of key components such as fuel cells in stationary stand-alone applications. This study investigates whether hybridising batteries with hydrogen can deliver meaningful cost benefits under future cost trajectories. Using a Monte Carlo framework we simulate 8000 scenarios across constant and seasonal load profiles varying the capital costs of batteries fuel cells electrolysers and hydrogen tanks based on 2025 estimates and 2050 projections. Our results show that hydrogen integration only becomes economically attractive when multiple component costs decline simultaneously. The fuel cell-to-battery power capital cost ratio emerges as the dominant driver of levelised cost of energy (LCOE) improvements. For constant loads median LCOE savings remain below 12 % with more than 5 % savings only achieved when the fuel cell cost is less than 7 times that of the battery. Seasonal nighttime loads offer a wider theoretical LCOE savings range (0–156 %) but substantial gains occur only under unrealistic cost mixes where battery costs remain high and fuel cell costs fall sharply. These findings highlight the sensitivity of hydrogen viability to load profile characteristics and cost interdependencies. They underscore the need for targeted cost reduction strategies particularly for fuel cells to justify added system complexity. These findings are important considerations for future investment and policy decisions.

Single Atom Catalysts (SACs) are an emerging frontier in heterogeneous electrocatalysis. They are made of metal atoms atomically dispersed on a matrix. A lot of attention has been dedicated to the study of Hydrogen Evolution Reaction (HER) mechanism due to its relevance in energy conversion technologies both with computational and experimental methods. The classical HER mechanism can be described by a Volmer–Heyrovsky–Tafel mechanism where the two desorption steps are competitive. The Volmer-Heyrovsky mechanism is conventionally proposed for single-atom catalysts. It has been computationally demonstrated that hydrogen complexes can form on SACs due to their analogy with homogeneous catalysts. Unfortunately it is hard to “visualize” these species experimentally. Electrochemical Impedance Spectroscopy (EIS) could be the most promising approach to study electrocatalytic mechanisms. In this work we present microkinetic and Electrochemical Impedance Spectroscopy models for HER on SACs describing Volmer-Heyrovsky and a mechanism mediated by the formation of hydrogen complexes. Our simulated data applied to a case study based on Pd@TiN show that Tafel plots will not suffice in the visualization of hydrogen complexes formation and will need the support of electrochemical impedance spectra in order to clarify the correct mechanism.

Decarbonizing industrial heat is critical for achieving climate targets. This study evaluates the economic viability of technologies for decarbonizing industrial heat in Europe through a techno-economic analysis. High-temperature heat pumps (HTHPs) and electric hydrogen and biomass boilers are compared in terms of levelized cost of heat (LCOH) under various scenarios including the impact of thermal storage leveraging dynamic electricity prices. In scenarios for the year 2030 we show that HTHPs leveraging free excess heat achieve LCOH values at least 30% to 60% lower than hydrogen boilers and up to 37% lower than biomass boilers. Integrating daily thermal storage reduces LCOH by up to 15% for heat pumps and 27% for electric boilers. By 2050 anticipated cost and efficiency improvements further enhance the competitiveness of heat pumps. These results highlight the economic advantage of HTHPs particularly when integrating excess heat and thermal storage.

This paper investigates the performance and economic viability of Combined Cycle Gas Turbines (CCGT) operating on natural gas (NG) and hydrogen within the context of evolving electricity markets. The study is structured into several sections beginning with a benchmark analysis to establish baseline performance metrics including break-even prices and price margins for CCGTs running on NG. The research then explores various base cases and sensitivity analyses focusing on different CCGT capacity factors and the uncertainties surrounding key parameters. The study also compares the performance of CCGTs across different European countries highlighting the impact of increased price fluctuations in forecasted electricity markets. Additionally the paper examines Power-to-X-to-Power (P2X2P) configurations assessing the economic feasibility of hydrogen production and its integration into CCGT operations. The analysis considers scenarios where hydrogen is sourced externally or produced on-site using renewable energy or grid electricity during off-peak hours. The results provide insights into the competitiveness and adaptability of CCGTs in a transitioning energy landscape emphasizing the potential role of hydrogen as a flexible and sustainable energy carrier.

A hybrid energy system (HES) integrates various energy resources to attain synchronized energy output. However HES faces significant challenges due to rising energy consumption the expenses of using multiple sources increased emissions due to non-renewable energy resources etc. This study aims to develop an energy management strategy for distribution grids (DGs) by incorporating a hydrogen storage system (HSS) and demand-side management strategy (DSM) through the design of a multi-objective optimization technique. The primary focus is on optimizing operational costs and reducing pollution. These are approached as minimization problems while also addressing the challenge of achieving a high penetration of renewable energy resources framed as a maximization problem. The third objective function is introduced through the implementation of the demand-side management strategy aiming to minimize the energy gap between initial demand and consumption. This DSM strategy is designed around consumers with three types of loads: sheddable loads non-sheddable loads and shiftable loads. To establish a bidirectional communication link between the grid and consumers by utilizing a distribution grid operator (DGO). Additionally the uncertain behavior of wind solar and demand is modeled using probability distribution functions: Weibull for wind PDF beta for solar and Gaussian PDF for demand. To tackle this tri-objective optimization problem this work proposes a hybrid approach that combines well-known techniques namely the non-dominated sorting genetic algorithm II and multi-objective particle swarm optimization (Hybrid-NSGA-II-MOPSO). Simulation results demonstrate the effectiveness of the proposed model in optimizing the tri-objective problem while considering various constraints.

Marine and island power systems usually incorporate various forms of energy supply which poses challenges to the coordinated control of the system under diverse irregular and complex load operation modes. To improve the stability and self-sufficiency of island-isolated microgrids with high penetration of renewable energy this study proposes a coordinated control strategy for an island microgrid with PV HGT and HESS combining primary power allocation via low-pass filtering with a fuzzy logic-based secondary correction. The fuzzy controller dynamically adjusts power distribution based on the states of charge of the battery and supercapacitor following a set of predefined rules. A comprehensive system model is developed in Matlab R2023b integrating PV generation an electrolyzer HGT and a battery–supercapacitor HESS. Simulation results across four operational cases demonstrate that the proposed strategy reduces DC bus voltage fluctuations to a maximum of 4.71% (compared to 5.63% without correction) with stability improvements between 0.96% and 1.55%. The HESS avoids overcharging and over-discharging by initiating priority charging at low SOC levels thereby extending service life. This work provides a scalable control framework for enhancing the resilience of marine and island microgrids with high renewable energy penetration.

The study focused on designing a sustainable building involving rooftop agrivoltaics advanced glazing technologies and onsite hydrogen production for a residential property in Birmingham UK where green hydrogen produced by harnessing electricity generated by agrivoltaics system on rooftop of the building is employed to change the transparency of vacuum gasochromic glazing and refuel hydrogen-powered fuel cell vehicle using storage hydrogen for a sustainable building approach. The change in the transparency of the glazing reduces the energy requirement of the building according to the occupant’s requirement and weather conditions. This research investigates the performance of various rooftop agrivoltaic systems including vertical optimal 30◦ tilt and dome setups for both monofacial and bifacial agrivoltaic consisting of tomato farming. Promising results were observed for agrivoltaic systems with consistent tomato production of 0.31 kg/m2 with varying shading experienced due to the different photovoltaic setups. Maximum electricity is produced by bifacial 30◦ with 7919 kWh though the lowest LCOE can be observed by monofacial 30◦ with £0.061/kWh. It also compares the efficiency of vacuum gasochromic windows against double glazing vacuum double glazing electrochromic and gasochromic options which can play an essential role in energy saving and reduced carbon emission. Vacuum gasochromic demonstrated the lowest U-value of 1.32 Wm2 K though it has the highest thickness with 24.6 mm. Additionally the study examines the feasibility of small-scale green hydrogen production from the electricity generated by agrivoltaics to fuel hydrogen vehicles and glazing considering the economic viability. The results suggested that the hydrogen required by the glazing accounts for 52.56 g annually and the maximum distance that can be covered theoretically is by bifacial 30◦ which is approximately 64.23 km per day. The interdisciplinary approach aims to optimise land use enhance energy efficiency and promote sustainable urban agriculture to contribute to the UK’s goal of increasing solar energy capacity and achieving net-zero emissions while addressing food security concerns. The findings of this study have potential implications for urban planning renewable energy integration especially solar and sustainable residential design.

The cement industry a foundation of infrastructure development is responsible for nearly 7 % of global CO2 emissions highlighting an urgent need for scalable decarbonization strategies. This study investigates the technoeconomic feasibility of integrating on-site solar-powered green hydrogen production into cement manufacturing processes. A mixed-integer linear programming (MILP) model optimizes the design and operation of solar photovoltaics (PV) proton exchange membrane (PEM) electrolyzer and hydrogen storage for a representative cement plant in Texas. Five hydrogen substitution scenarios (10–30 % of thermal demand) were evaluated based on net present cost (NPC) levelized cost of hydrogen (LCOH) cost of CO2 avoided and greenhouse gas (GHG) emissions reduction. Hydrogen integration up to 30 % is technically viable but economically constrained with LCOH rising non-linearly from $58.7 to $95.3 GJ− 1 due to escalating component costs. Environmentally a 30 % hydrogen share could reduce total U.S. cement sector emissions by 22 %. While significant this confirms at present the solar-driven hydrogen serves as a partial solution rather than a standalone pathway to deep decarbonization suggesting it must complement other strategies like carbon capture electrification and other complementary technologies. The economic viability of this approach is entirely contingent on financial incentives as the investment tax credits of 80 % or higher are essential to enable cost parity with fossil fuels. This work provides a comprehensive techno-economic and environmental framework concluding immense economic barriers and that aggressive policy support is indispensable for enabling the transition to low-carbon cement manufacturing.