The paper presents the results of experimental studies on a self-draining bipolar plate used in a low-temperature polymer electrolyte membrane fuel cell (L-PEMFC). These studies investigated the cell's performance under varying platinum catalyst loadings and different hydrogen and oxygen flow rates.Two catalyst loading configurations were tested: (ⅰ) 0.20 mg/cm2 (anode) and 0.40 mg/cm2 (cathode) and (ⅱ) 0.25 mg/cm2 (anode) and 0.50 mg/cm2 (cathode). The gas diffusion layer (GDL) employed was carbon paper, with the catalyst arranged on the carbon substrate.Hydrogen flow rates of 80,100, and 120 ml/min were assessed alongside oxygen supplies at 50%, 100%, and 150% excess relative to the stoichiometric requirement (0%) in relation to the hydrogen supply for both catalyst loading conditions. Additional experiments were conducted at humidification temperatures of 60, 70, 80, 90, and 100 ℃, using the optimal hydrogen flow rate and oxygen supply conditions. To evaluate the stability, the fuel cell operated continuously for 5 hours at the optimal humidification temperature to assess the stability of voltage and power output.The fuel cell using the self-draining bipolar plate demonstrated an approximately 30% increase in load-bearing capacity. However, it did not show significant differences in voltage or power across the varying catalyst loadings. The optimal humidification temperature was determined to be 90 ℃. This study provides valuable insights into the continuous operation of fuel cells under optimal conditions of humidification, excess oxygen, and hydrogen flow rate.

A proton exchange membrane fuel cell (PEMFC) with reduced catalyst loading, specifically 0.2 mg/cm2 at the anode and 0.4 mg/cm2 at the cathode, was investigated using a twin inlet and twin outlet flow field configuration. The author conducted comparisons of voltage overpotential and maximum power output across various gas flow rates and humidification temperatures, contrasting these with results obtained from higher catalyst loading. Hydrogen flow rates of 80,100, and 120 mL/min were utilized, with adjustments made to oxygen levels to achieve stoichiometric ratios, as well as 50%, 100%, and 150% excess oxygen. Notably, at a hydrogen flow rate of 100 mL/min, the maximum power output occurred at an oxygen flow rate of 125 mL/min. The optimal ratio of hydrogen to oxygen was further explored across different humidification temperatures ranging from 60 to 100 ℃, inclusive of experiments conducted without humidification. Intermediate humidification temperatures yielded the best overall performance. We systematically assessed the voltage overpotential, maximum power point, and cell resistance under varying hydrogen-oxygen ratios and humidification temperatures. Our findings were compared with data obtained using higher catalyst loading configurations. The results obtained are validated by statistical analysis. The study demonstrates that the performance levels for reduced catalyst loading come close to that of higher catalyst loading configurations. Consequently, lower catalyst loading, which reduces the overall cost of the fuel cell, can be effectively employed in PEMFCs under specific operational parameters.

Pursuing highly stable and efficient renewable energy solutions remains the driving force for developing perovskite solar cells (PSCs). Central to achieving these cells’ high and optimum performance is the accurate and intelligent design engineering of the device’s architecture. This theoretical study employs the simulation platform SCAPS-1D to systematically investigate the crucial role of the interlayer methylammonium lead iodide (MAPbI3) as an adsorber layer in encouraging the titanium dioxide (TiO2)/MAPbI3/graphene oxide (GO) heterostructure design. By strategic tuning of the MAPbI3 absorber layer, we successfully delivered a remarkable 20.8% power conversion efficiency (PCE) and fill factor (FF) of 80.5% at 300 K, significant improvements over the reference PCE of 11.6% and FF of 78.5%. Significant improvements were made by optimizing MAPbI3 thickness to 1.2 µm and narrowing its bandgap to 1.5 eV, allowing enhanced photon absorption and charge carrier separation and minimizing interface-mediated recombination losses. Importantly, changes to the TiO2 and GO layer thickness had a minimal impact on performance, emphasizing the absorber layer’s dominant role in controlling efficiency. Utilizing low-cost, low-toxicity materials such as abundant TiO2 and GO improves economic feasibility and scalability, and the optimized structure minimizes material consumption, all aligning with sustainable photovoltaic development. These results advance our understanding of PSC optimization and reflect the enormous potential of MAPbI3 materials for developing highly efficient, green alternatives to conventional solar technology, enabling future developments in stable, scalable, and environmentally friendly energy solutions.

The aim of this report is to investigate the potential of using surplus electricity generated by wind turbines in a power-to-heat (P2H) setup serving the Danish district heating market. The research establishes a theoretical position on variable renewable energy, district heating, heat pumps, boilers, and thermal energy storage through academic literature and industry professional reporting research. The empirical section touches upon the same topics, focusing on total energy production, curtailment, and district heating (DH) in Denmark. An analysis of the amount of curtailed power production in combination with electricity spot prices was used to calculate the corresponding heating demand that could be achieved if the power was used for large-scale heat pumps and electric boilers. It was found that the potential power-to-heat supply ranges from 18,100 to 63,380 households across the scenarios analyzed. The conclusion is that there seems to be a clear potential for redirecting the surplus electricity into DH to meet part of the Danish heat demand, and that the ongoing technological development of DH, thermal energy systems (TES), and variable renewable energy (VREs) in combination with market conditions favors a focus on sector coupling and P2H in the future.

In this study, we introduced a unified family of fractional-order derivatives of the error function, bridging classical error function ($ \alpha = 0 $) and Gaussian ($ \alpha = 1 $) through Maclaurin expansion and Lacroix's fractional calculus. The adaptive model was validated against cubic spline and Gaussian baselines using six days of real photovoltaic measurements from a tropical environment. Moving-window optimization achieved competitive accuracy (Root Mean Squared Error (RMSE): 0.0083–0.0104; Mean Absolute Error (MAE) 0.0068–0.0086) while preserving physical interpretability via the fractional order $ \alpha $. Comparative analysis demonstrated significant improvement over Gaussian fitting, with an average 14.17% reduction in RMSE across all test days. The fractional approach also delivered more consistent daily performance and better captured asymmetric transitions, despite spline's occasional marginal RMSE advantages. Graphical analysis revealed persistent diurnal $ \alpha $ patterns: from 0.50 at sunrise, peaking at 0.90–0.91 near noon, declining to 0.37 afternoon, with sunset rebound. Our results confirmed the model effectively captures photovoltaic memory effects while offering superior interpretability and dynamic adaptation versus traditional methods. The framework enables accurate energy forecasting and condition-based maintenance, with future work focusing on real-time $ \alpha $ tuning and machine learning integration.

<p>As a part of last-mile transportation, electric three-wheelers, popularly known as trikes, are considered as an important aspect of the future of the auto industry. The appropriate choice of electric traction motor drive is imperative to the design of an electric motor power train. In this paper, six main types of sinusoidal-fed electric motor power trains—Ferrite-Assisted Synchronous Reluctance Motor (FASRM), Synchronous Reluctance Motor (SyncRelM), Ferrite-based Spoke motor, Ferrite-based Surface-Mounted Permanent Magnet Synchronous Motor (SMPMSM), Wound-Field Synchronous Motor (WFSM), and Induction Motor (IM)—are compared for their performance in electric trike applications. The permanent magnet machines presented here utilize ferrite magnets, in line with the recent trend of not using rare-earth magnets. The comprehensive comparative analysis establishes that SyncRelM, FASRM, and Spoke motors are superior in terms of overall electromagnetic, thermal, and vibration performance. This paper also focuses on an optimal design of the FASRM due to its high torque density, lower torque ripple, and minimal use of ferrite magnets. A Design of Experiments (DoE)-based statistical analysis tool is used to identify the key parameters needed for robust motor performance in the optimization step. Furthermore, an Extreme Learning Machine (ELM)-based interpolation technique is employed for estimating the performance parameters during each step of the optimization routine. A 1.2 kW FASR motor prototype is developed and tested. A comparison of Finite-Element-Analysis-based modeling results is presented along with Indian drive-cycle results for the FASRM for trike application.</p>

Starting from the oil shock of the seventies, how buildings use energy generated by different sources has been under the spotlight [1] . At first, attention was paid mainly to short-term energy-saving goals, accomplished primarily through command and control policies. Later, especially in the last couple of decades, the focus shifted to long-term energy-efficiency targets, which were to be pursued through proactive and incentivizing policies. Accordingly, many national governments-not to mention supranational organizations such as the European Union-have updated their regulations and building codes in the first place and adopted and implemented novel incentive measures in the second place [2] [3] [4] [5] [6] . The variety of monetary incentive tools-ranging from grants and subsidies to tax rebates, from loan reliefs to green mortgages-can be seen among the reasons at the root of the rise and growth of innovative, sustainability-focused entrepreneurial practices and business models [7] . While considerable steps have been taken, and incentive policies jointly with sustainable business models are contributing to improving the renovation rate of the building stock and, perhaps, spreading the adoption of passive design strategies, much remains to be done. Under the above framework, this Special Issue-"Building energy efficiency: New challenges for incentive policies and sustainable business models"-aims to discuss the prospective challenges concerning the research strand of incentive policies and the related novel entrepreneurial approaches. Two of the papers published in the Special Issue analyze energy use and energy efficiency at the city and building type levels, respectively. The review by El Hafdaoui et al. [8] focuses on the town of Ifrane, Morocco. Estimations of energy demand and its trend are considered and discussed in light of government programs meant to improve the efficiency of the country's building stock. The article by focuses on protected housing built in Spain for railway workers. The efficiency of those dwellings is assessed through the thermal analysis of the building envelope. The

<p>Modern electricity networks are facing significant challenges in terms of power quality due to the increasing integration of power electronics. Even though low order harmonic control has largely been achieved, the emergence of supraharmonics is becoming a new cause for concern. This topic has gained interest in the past decade since power quality issues have become important due to the proliferation of highly sensitive electrical and electronic equipment. This special case of harmonics is mainly due to the power electronic converters utilized in industrial as well as residential applications, including electromobility, motor drive systems, and photovoltaic installations. While the adverse effects of supraharmonics have been pointed out in numerous studies and intensive research is underway on the crucial subject of supraharmonic measurements, the parameters affecting their levels have not received adequate attention. We attempted to shed more light on this important issue in the specific case of a small grid-connected PV system. In particular, the supraharmonic emission levels of the system were investigated through experimental measurements, and useful conclusions on the impact of specific environmental factors were derived.</p>

<abstract> <p>In this paper, we propose a forecasting system of sunshine radiation for planners to quickly and accurately predict the output of solar power. The field data, including observation time, temperature, relational humidity, wind speed and global radiation, were collected, and the data clusters were embedded in the Excel Database. To improve the computational performance, the data selection technique was used in the stage of data cleaning, data integration and data reduction. Using the Integration of the Radial Basis Function Network (RBFN) and Sliding Mode Control (SMC), a Sliding Mode Radial Basis Function Network (SMRBFN) was proposed to solve this forecasting problem. Since the Sliding Mode Control has the design's sense of optimal parameters, three parameters in the SMRBFN were dynamically adjusted to promote the accurate and reliability of forecasting system. Linking the SMRBFN and Excel database, the learning stage and testing stage of SMRBFN retrieved the input data from Excel Database to perform and analyze the forecasting system. The proposed algorithm was tested on Kaohsiung district in summer and winter. The average prediction error of MAPE and RMSE obtained from the forecasting results are about 9% and 0.223, respectively. It can be proved that SMRBFN can efficiently forecast the sunshine radiation and accurately provide the output of solar power in an uncertainty environment.</p> </abstract>