Publications

To address the economic and reliability challenges of high-penetration renewable energy integration in electricity-heat-hydrogen integrated energy systems and support the dualcarbon strategy this paper proposes an optimal dispatch method integrating Information Gap Decision Theory (IGDT) and Fuzzy Chance-Constrained Programming (FCCP). An IES model coupling multiple energy components was constructed to exploit multi-energy complementarity. A stepped carbon trading mechanism was introduced to quantify emission costs. For interval uncertainties in renewable generation IGDT-based robust and opportunistic dispatch models were established; for fuzzy load uncertainties FCCP transformed them into deterministic equivalents forming a dual-layer “IGDT-FCCP” uncertainty handling framework. Simulation using CPLEX demonstrated that the proposed model dynamically adjusts uncertainty tolerance and confidence levels effectively balancing economy robustness and low-carbon performance under complex uncertainties: reducing total costs by 12.7% cutting carbon emissions by 28.1% and lowering renewable curtailment to 1.8%. This study provides an advanced decision-making paradigm for low-carbon resilient IES.

Aqueous phase reforming has been posed as a promising technology for renewable hydrogen production in the framework of the transition to a sustainable energy economy. Since the use of chemical compounds as process feedstock has proven to be one of the major constraints to its potential scalability several cost-free residual biomasses have been investigated as alternative substrates. This also allows for the recovery of residues offsetting the significant costs of waste management through conventional treatment. In recent years different wastes from the food processing industry such as brewery fish canning dairy industries fruit juice extraction and corn production wastewaters have taken the attention of scientific community due to their composition favorable to this process and its high-water content. However few and heterogeneous results can be found within the literature suggesting that the research into this application is now at a stage of development which will require further investigation. Therefore this work is focused on compiling and discussing the reported studies aiming to present a critical reflection on the potential of aqueous phase reforming as a means for the valorization of this kind of residue.

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.

High-temperature proton exchange membrane fuel cells (HT-PEM FCs) represent a promising avenue for generating carbon dioxide-free electricity through the utilization of hydrogen fuel. These systems present numerous advantages and challenges for mobile applications positioning them as pivotal technologies for the realization of emission-free regional aircraft. Efficient thermal management of such fuel cell-powered systems is crucial for ensuring the safe and durable operation of the aircraft while concurrently optimizing system volume mass and minimizing parasitic energy consumption. This paper presents four distinct heat transfer principles tailored for the FC-system of a conceptual hydrogen-electric regional aircraft exemplified by DLR’s H2ELECTRA. The outlined approaches encompass conductive cooling air cooling liquid cooling phase change cooling and also included is the utilization of liquid hydrogen as a heat sink. Approaches are introduced with schematic cooling architectures followed by a comprehensive evaluation of their feasibility within the proposed drivetrain. Essential criteria pertinent to airborne applications are evaluated to ascertain the efficacy of each thermal management strategy. The following criteria are selected for evaluation: safety ease of integration reliability and life-cycle costs technology readiness and development as well as performance which is comprised of heat transfer weight volume and parasitic power consumption. Of the presented cooling methods two emerged to be functionally suitable for the application in MW-scale aircraft applications at their current state of the art: liquid cooling utilizing water under high pressure or other thermal carrier liquids and phase-change cooling. Air cooling and conductive cooling have a high potential due to their reduced system complexity and mass but additional studies investigating effects at architecture level in large-scale fuel cell stacks are needed to increase performance levels. These potentially suitable heat transfer technologies warrant further investigation to assess their potential for complexity and weight reduction in the aircraft drivetrain.

Ammonia due to its favorable physicochemical properties is considered an effective hydrogen carrier enabling the storage of surplus energy generated from renewable sources. Large-scale implementation of this concept requires the safe transport of ammonia over long distances commonly achieved through pipeline systems—a practice with global experience dating back to the 1960s. However operational history demonstrates that failures in such infrastructures remain inevitable often leading to severe environmental consequences. This article reviews both passive and active methods for preventing and mitigating incidents in ammonia pipeline systems. Passive measures include the assessment of material compatibility with ammonia and the designation of adequate buffer zones. Active methods focus on leak detection techniques such as balance-based systems acoustic monitoring and ammonia-specific sensors. Additionally the article highlights the potential environmental risks associated with ammonia release emphasizing its contribution to the greenhouse effect as well as its adverse impacts on soil surface and groundwater and human health. By integrating historical lessons with modern safety technologies the article contributes to the development of reliable ammonia transport infrastructure for the hydrogen economy.

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.

Titanium dioxide (TiO2) is widely used in solar cells and photocatalysts given its excellent photoactivity low cost and high structural electronic and optical stability. Here a novel TiO2 composite was prepared by coating TiO2 inverse opal (IO) with TiO2 nanorods (NRs). With a porous three-dimensional network structure the composite exhibited higher light absorption; enhanced the separation of the electron–hole pairs; deepened the infiltration of the electrolyte; better transported and collected charge carriers; and greatly improved the power conversion efficiency (PCE) of the quantum-dot sensitized solar cells (QDSSCs) based on it while also boosting its own photocatalytic hydrogen generation efficiency. A very high PCE of 12.24% was achieved by QDSSCs utilizing CdS/CdSe sensitizer. Furthermore the TiO2 composite exhibited high photocatalytic activity with a H2 release rate of 1080.2 µ mol h−1 g −1 several times that of bare TiO2 IO or TiO2 NRs.

Hydrogen is widely regarded as a promising carbon-free alternative fuel. However the development of low-emission marine gas turbine combustion systems has been hindered by the associated risks of combustion instability also termed as thermoacoustic oscillations. Although there is sufficient literature on hydrogen fuel and combustion instability systematic reviews addressing the manifestations and mechanisms of these instabilities remain limited. The present study aims to provide a comprehensive review of combustion instabilities in hydrogen-enriched marine gas turbines with a particular focus on elucidating the characteristics and underlying mechanisms. The review begins with a concise overview of recent progress in understanding the fundamental combustion properties of hydrogen and then details various instability phenomena in hydrogen-enriched methane flames. The mechanisms by which hydrogen enrichment affects combustion instabilities are extensively discussed particularly in relation to the feedback loop in thermoacoustic combustion systems. The paper concludes with a summary of the key combustion instability challenges associated with hydrogen addition to methane flames and offers prospects for future research. In summary the review highlights the interaction between hydrogenenriched methane flames and thermoacoustic phenomena providing a foundation for the development of stable low-emission combustion systems in industrial marine applications incorporating hydrogen enrichment.

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.