Applications In Energy Systems Research Articles

Modeling hydrogen storage at room temperature: Adsorbent materials for boosting pressure reduction in compressed H2 tanks

Energy storage systems are required for an efficient integration of renewables into the grid to achieve a net zero energy system. Hydrogen compressed at 700 bar, is one of the key energy storage technologies. This study evaluates the effectiveness of solid-state hydrogen storage, particularly physisorption in porous materials, to enhance storage performance and safety at room temperature by reducing the operating tank pressure. We model dynamically the entire storage system, comparing adsorbent materials to traditional compression in terms of maximum tank pressure and round-trip storage efficiency. Different energy system applications with varied cycle frequencies and discharge durations were examined. Results indicate that porous material-based systems exhibit higher efficiency for long-duration energy storage services than the compressed hydrogen. Notably, bulk density plays a pivotal role in storage performance. For instance, IRMOF-1 with a bulk density of 500 kg/m3, shows a 70 % pressure reduction compared to compressed hydrogen systems. In contrast, when its bulk density is reduced to 130 kg/m3, the maximum tank pressure is even 30 % higher than the compressed tank. We emphasize the need for comprehensive material characterization, highlighting the significance of parameters like bulk density for determining the most performing hydrogen adsorbent material in terms of maximum tank pressure and efficiency. As general outcome, the best performing material depends on the specific target or system requirements, such as pressure, volume, cost, or weight.

Numerical modeling of mixed convective nanofluid flow with fractal stochastic heat and mass transfer using finite differences

This study presents the first comprehensive numerical simulation of heat and mass transfer in fractal-like mixed convective nanofluid flows. The flow of non-Newtonian nanofluids over flat and oscillating sheets is modelled mathematically, and a finite difference scheme is used to solve this model. The two-stage scheme can tackle fractal and fractal stochastic mathematical models of partial differential equations. The consistency in the mean square is proved, and Fourier series stability analysis is adopted to find stability conditions for fractal stochastic partial differential equation. The scheme is applied to solve the unsteady Casson nanofluid flow over the flat and oscillatory sheet, which affects thermal radiation, heat source, and chemical reaction. The existence of the solution is also provided for the Navier-Stokes equation of the considered flow model using fractal time derivative. The graph illustrates that the proposed fractal technique achieves faster convergence than the Crank-Nicolson approach. Applications in energy systems, materials science, and environmental engineering are just a few of the domains that could benefit from a better understanding of mixed convective nanofluid flows with fractal features, and that is what this research study hopes to accomplish. Scientists and engineers may better develop efficient and environmentally friendly systems by simulating and analyzing these complicated processes with the suggested finite difference technique.

Optical and thermal performance enhancement of parabolic dish collector: Effects of cavity receiver's surface modification and covering aperture

Regarding the increasing demand for renewable energy sources, especially solar energy, researchers are trying to develop more efficient solar energy systems. Parabolic dish collectors are solar thermal collectors that can be utilized in various thermal energy system applications. Cavity receivers of the dish collectors are one of the crucial parts of these collectors, and the studies on their thermal performance improvement and heat loss reduction are critical. The current study follows the experimental investigation of the glass covering of cylindrical-conical cavity receiver along with the cavity's coil surface modification with various geometries. According to the results, applying the glass covering enhanced the thermal efficiency by 18.42%, with a maximum thermal efficiency of 52.61% and optical efficiency of 57.89%. Rectangular-triangular geometry for the surface modification of the cavity's coil resulted in a maximum optical efficiency of 59.17%. Overall, rectangular geometry had the best thermal and optical efficiency enhancement results.

Application of renewable energy systems in seaports towards sustainability and decarbonization: Energy, environmental and economic assessment

The application of green energy technologies to supply berthed ships in ports with the necessary power instead of using their diesel generators is considered an initiative towards sustainability and climate change mitigation. Therefore, the current paper investigates the implementation of solar panels, offshore wind turbines, and hydrogen fuel cell systems as green technologies to supply the berthed ships with power in three Egyptian ports. The power requirements are determined by analyzing the annual ship traffic data and estimating the energy demand for each ship type. As a relevant result, the annual energy demand for ships berthed in Alexandria, Damietta, and Safaga ports is about 44.2 × 103 MWh, 22 × 103 MWh, and 5.6 × 103 MWh, respectively. The analysis results reveal a potential annual carbon dioxide reduction of 31.7 k-tons, 15.7 k-tons, and 4.2 k-tons in Alexandria, Damietta, and Safaga ports, respectively. From an economic perspective, the levelized cost of energy (LCOE) of solar panels is estimated to be 80.7–90.1 $/MWh, while hydrogen fuel cells have a cost of 166.8–172 $/MWh. On the other hand, LCOE in the case of wind turbines is estimated to be 140.8 $/MWh for Alexandria ports, 178.3 $/MWh for Damietta port, and 103.9 $/MWh for Safaga port.

An Improved Single-Phase Multiple DC Source Inverter Topology for Distributed Energy System Applications

This work presents an improved structure of a single-phase muti-input multilevel inverter (MIMLI) for distributed energy resources, which is capable of producing a nine-level output in symmetric mode and 21 levels in asymmetrical mode. The topology uses four DC sources and ten switches, with four switches being bidirectional and the remaining unidirectional. The operation of the circuit is analyzed in an asymmetrical mode, and switching signals are accomplished using the Nearest Level Control (NLC) PWM technique. Depending on the value of the DC sources used, the number of levels can vary. In this work, different DC source algorithms were also proposed, and the analysis of the inverter has been carried out considering the algorithms producing the maximum number of levels. The inverter was simulated in MATLAB/Simulink under steady state and dynamic conditions, achieving a 3.89% THD in output. The thermal analysis was conducted using PLECS software 4.1.2 to assess losses and efficiency. A laboratory prototype of the proposed topology was developed and tested, confirming its performance through simulation results and proving it economically viable for medium- and high-power applications.

Dynamics of Casson/Carreau hybrid nanofluid flow over a wedge with thermophoresis and Brownian motion effects

ABSTRACT In recent years, nanotechnological research has introduced hybrid nanofluids, which are advanced fluids with augmented thermal properties that give better results than regular nanofluids. The thermal transfer characteristics of the Falkner-Skan flow of MgO-MoS2/Engine oil hybrid nanofluid induced by a wedge surface with thermophoresis and Brownian motion are numerically investigated. The main objective of this research is to examine the augmented thermal transport behavior of Casson and Carreau hybrid nanofluids. The equations that arise are solved by adopting the bvp5c scheme in MATLAB software. Plots and numerical values illustrate the stimulus of various pertinent parameters on the flow-determining factors such as velocity, thermal and concentration fields, wall friction, energy, and mass transports. The rate of energy transport in the Carreau hybrid nanofluid is significantly larger than that of the Casson hybrid nanofluid. The implication of 5% volume of MgO-MoS2 nanoparticles enhances the rate of thermal transport by 53% in the Carreau fluid and 47% in the Casson fluid, respectively. This research holds potential for applications in geothermal energy systems.

Superwetting Capillary Tubes: Surface Science under Confined Space.

Capillarity is a crucial and pervasive phenomenon in nature and has found important applications in wearable electronics, medical devices, and miniature energy systems. Capillary tubes are the transport vessels in which the surface wettability plays an essential role in efficient and accurate liquid delivery. However, it remains a challenging issue to tailor and measure the surface wettability inside the tubes in view of the confined space. Herein, recent progress on the surface science under confined space is discussed, with a particular focus on surface modification, wettability evaluation, and advanced applications of the superwetting capillary tubes. This Perspective aims to highlight the emerging opportunities in surface science with spatial confinement toward flexible and portable devices.

MoS2/ReS2 Hollow Heterojunction for Enhanced Aqueous Zinc-Ion Storage Performance.

The research of cathode materials for water-based zinc ion batteries (ZIBs) is very hot because the current mainstream electrode makes it difficult to meet the requirements of high specific discharge capacity and maintain a stable structure in the electrochemical process. In this work, the cathode properties are adjusted by the modification idea of morphology regulation and heterojunction construction. The simple hydrothermal method is used to prepare the hollow bimetallic heterojunction nanospheres, and their electrochemical properties as cathode materials for ZIBs are studied for the first time. Herein, the optimized cathode delivers high-rate performance and long-term cycling stability (∼98.9% Coulombic efficiency at 0.1 A g-1 after 200 cycles). The results indicate that the hollow bimetallic heterojunction nanospheres can support the material structure and provide a wide Zn2+ migration channel. The excellent performance is because hollow heterojunction bimetallic sulfides can provide abundant catalytic active sites, improve the mobility of electrons, and enhance the battery performance fundamentally. Therefore, we firmly believe that the combination of the different modification ideas can coordinate to adjust the electrode performance of ZIBs, enriching the electrode types and expanding the energy system application range.

Cutting-Edge Triple-Port Soft-Switching Converter for Seamless Renewable Energy Integration

Three-port converters with high voltage gain are desirable solutions for integrating renewable energy and energy storage devices into high voltage dc bus. A high gain three-port converter with soft switching is proposed in this paper, which can realize zero voltage switching (ZVS) for all switches and zero current switching (ZCS) for all diodes in various operating modes. Single coupled inductor is used to achieve high voltage gain and to reduce the voltage stress of switches so that switches with low on-resistance can be selected to reduce the conduction loss. In addition, the advantages of fewer components, higher voltage gain, and very low switch voltage stresses make the proposed converter more suitable for application in renewable energy systems than similar solutions. Various operating modes, performance analysis, design considerations, efficiency analysis, and control method of the proposed converter are discussed. A laboratory prototype with 30V renewable energy source, 48V energy storage device and 400V output is designed to verify the performance of the proposed three-port converter.

Long-term solar radiation forecasting based on LSTM and attention mechanism: a case study in Algeria

The growing adoption of photovoltaic (PV) energy in urban areas underscores its capability to meet energy demands effectively. The accurate forecasting of meteorological parameters, particularly global solar radiation, is paramount for the efficient management and utilization of solar energy resources. Solar radiation forecasting methods typically fall into two main categories: cloud imagery combined with physical approaches, and Artificial Intelligence (AI) based methods. Due to the non-stationary nature of solar radiation and the high nonlinearity of atmospheric conditions, conventional forecasting approaches often exhibit poor accuracy. Artificial intelligence based approaches, such as machine learning and deep learning algorithms, are extensively employed in global solar radiation forecasting research, demonstrating impressive accuracy. In this respect, this paper presents a novel approach for long term monthly forecasting of global solar radiation using a Bidirectional Long Short-Term Memory (LSTM) architecture augmented with an attention mechanism that includes a Squeeze and Excitation (SE) block (SE-BiLSTM). The effectiveness of this model is extensively evaluated for long-term monthly solar radiation forecasting using meteorological data collected over a 20-year period (from Jan 2001 to Dec 2020) from the National Aeronautics and Space Administration (NASA). The proposed SE-BiLSTM model is compared with well-established forecasting models including Naïve, Autoregressive Moving Average (ARMA), Multi-layer Perceptron (MLP), LSTM, and Bidirectional LSTM. Through rigorous simulation tests, our model demonstrates superior performance, achieving the lowest mean absolute percentage error (MAPE) of 4.52% and mean absolute error (MAE) of 7.89 kW/m2. This advancement holds significant promise for enhancing solar energy forecasting accuracy and its practical application in renewable energy systems.

A data mining-based framework to define optimal operation strategies for in-duct ultraviolet germicidal irradiation systems for different climatic conditions

This paper presents a novel data mining framework for optimizing the operation of in-duct Ultraviolet germicidal irradiation (UVGI) systems employed for air disinfection within air handling units. The performance of the UVGI system is influenced by the operating conditions of air handling units. As a result, under favourable operating conditions, the system produces excessive Ultraviolet C energy beyond the required disinfection levels, causing energy waste and accelerating the degradation of heating, ventilation, and air conditioning (HVAC) components. The framework aims to improve energy efficiency and mitigate material degradation within HVAC components by systematically adjusting UVGI system output based on changing operating conditions of air handling units throughout the year using advanced data mining techniques. The methodology involves several steps: Firstly, data pre-processing is performed to improve data quality. Then, the K-means clustering algorithm is applied to discover patterns in operational data. Subsequently, an effective performance index and baseline are defined to identify energy-saving opportunities within each cluster. Finally, the optimal operation strategy is defined based on the determined baseline. The framework is extended to five distinct climate zones to derive region-specific operation strategies. Results from a case study in a small office building in Montreal and an extension to five distinct climate zones in Canada demonstrate energy savings from 8% to 37%. This study offers a promising approach to optimize UVGI system operation, with potential applications in various energy systems in buildings requiring adaptive operational conditions for optimal performance.

Blockchain technology in the renewable energy sector: A co-word analysis of academic discourse

The transformative potential of blockchain technology in the renewable energy sector is increasingly gaining recognition for its capacity to enhance energy efficiency, enable decentralized trading, and ensure transaction transparency. However, despite its growing importance, there exists a significant knowledge gap in the holistic understanding of its integration and impact within this sector. Addressing this gap, the current study employs a pioneering approach, marking it as the first comprehensive bibliometric analysis in this field. We have systematically examined 390 journal articles from the Web of Science database, covering the period from 2017 through the end of February 2024, to map the current landscape and thematic trajectories of blockchain technology in renewable energy. The findings highlight several critical thematic areas, including blockchain's integration with smart grids, its role in electric vehicle integration, and its application in sustainable urban energy systems. These themes not only illustrate the diverse applications of blockchain but also its substantial potential to revolutionize energy systems. This study not only fills a crucial gap in existing literature but also sets a precedent for future interdisciplinary research in this domain, bridging theoretical insights with practical applications to fully harness the potential of blockchain in the renewable energy sector.

Review of heat pipes for power batteries of new energy vehicles

With the global energy crisis becoming one of the most concerned topics, the application of new energy systems has become the most popular research at present. In addition, with the emerging new energy vehicles, problems such as high calorific value and insufficient heat dissipation performance of lithium batteries for new energy vehicles have not been solved, so the research on thermal management technology of lithium batteries is essential. Based on the analysis of heat pipe research, this paper summarizes heat pipe from three aspects, including structure and arrangement of the heat pipe, wall materials of the heat pipe and phase change materials of the heat pipe. This paper puts forward new insights and provides a reference for the research on the thermal management of lithium batteries for new energy vehicles.

Multi-objective optimization study of regional integrated energy systems coupled with renewable energy, energy storage, and inter-station energy sharing

Globally, countries have established timelines and technological pathways towards achieving "carbon neutrality". Regional integrated energy systems, as an efficient and clean mode of energy provision, are particularly suitable for supplying various forms of energy to building users. However, due to the complexity of their structure and multiple energy flow couplings, regional integrated energy systems face challenges in system optimization, warranting further exploration in design optimization and benefit analysis. Therefore, a regional integrated energy system was established, integrating renewable energy, energy storage, and power/thermal sharing between stations. A multi-objective optimization model for the regional integrated energy system was established, targeting economic benefits, carbon reduction, and reliability. Overall benefits of the internal energy stations in the regional integrated energy system were meticulously analyzed, considering system benefits, inter-station energy sharing, and energy storage. Research findings indicate, the regional integrated energy system constructed in this study exhibited superior energy-saving, carbon reduction, and independence, compared to other integrated energy systems. For the proposed system, the annual total cost was 38.41 CNY/m2, primary energy consumption stood at 16.26 kWh/m2, carbon emission was recorded at 4.33 kg/m2, and the system interaction power measured 9.99 kWh/m2. Final, this study provides theoretical support for the application and promotion of regional integrated energy systems.

Preface

It is with great pleasure and enthusiasm that we present the proceedings of the 2023 3rd International Conference on Frontiers of Electrical Power & Energy Systems. This conference, held from December 23-24, 2023, brought together researchers, scholars, engineers, and industry professionals from around the world to share their latest advancements and discoveries in the dynamic field of electrical power and energy systems.Electrical power and energy systems form the backbone of modern society, enabling the seamless functioning of industries, homes, and technological advancements. The conference theme, “Advancing Innovation in Power and Energy Systems,” underscored the importance of embracing cutting-edge technologies, novel methodologies, and innovative solutions to address the challenges and opportunities in the realm of electrical power and energy. The papers selected for inclusion cover a wide spectrum of topics, spanning Electrical and Electronic Engineering, Energy and Power System, Automation and Engineering Application and so on.One of the highlights of this conference was the international collaboration and knowledge exchange that took place among participants. Researchers from different continents and cultural backgrounds shared their unique perspectives, fostering a global understanding of the issues at hand. This interconnectedness is vital as we collectively strive towards sustainable and efficient solutions for the world’s growing energy needs.The diversity and depth of the papers included in these proceedings reflect the richness of the discussions and presentations that took place during the conference. We extend our sincere appreciation to all the authors for their valuable contributions, which have significantly enriched the body of knowledge in this rapidly evolving field. We also extend our gratitude to the dedicated reviewers who rigorously evaluated each submission. Their commitment to academic excellence has ensured the high quality and relevance of the papers included in these proceedings. Special thanks are due to the organizing committee, session chairs, keynote speakers, and sponsors for their invaluable contributions to the success of the conference. Their dedication and support have played a pivotal role in creating a vibrant and intellectually stimulating environment.Once again, we welcome you to the proceedings of the 2023 3rd International Conference on Frontiers of Electrical Power & Energy Systems and hope that the insights gained from this conference will contribute to the development of sustainable and resilient solutions that address the evolving challenges in our ever-changing world. We look forward to continued collaboration and the prospect of meeting again at future conferences to further advance the frontiers of electrical power and energy systems. EPES 2023 Organizing Committee List of Committee Members is available in this pdf.

Thermo-economic multi-objective optimization of the liquid air energy storage system

Liquid Air Energy Storage (LAES) is a promising energy storage technology for large-scale application in future energy systems with a higher renewable penetration. However, most studies focused on the thermodynamic analysis of LAES, few studies on thermo-economic optimization of LAES have been reported so far. Thus, this work focuses on the multi-objective optimization of LAES by using non-dominated sorting genetic algorithm (NSGA-II), taking the round trip efficiency (RTE) and economic indicators as the optimization objectives. Three major results were obtained from this work. First, the NSGA-II-based optimization framework is able to determine the optimal design and operational parameters of LAES under different configurations and scenarios, including the optimal charging and discharging pressure, heat transfer areas, and mass flow rates of hot and cold storage media etc. It is shown that the increase of energy efficiency by 9 % ~ 14 % and a decrease of exergy destruction by 16 % were seen. Secondly, the design and operational guidelines of LAES can be derived from the optimization. The optimal charging pressure was found to vary between 13 and 15 MPa, and the optimal discharging pressure is between 9 and 12 MPa, depending on the machines' efficiencies and pinch points of heat exchangers of a LAES system. Finally, the Pareto Fronts of capital expenditure, energy efficiency and the occupied space energy density of a LAES system provide system operators good operational and investment advice. Specifically, the RTE of the LAES increasing by 1 % is at the cost of increasing the capital cost by 0.5–1 %. In this study, if the investment budget is over 48 M£, a LAES system with three-stage compressors and four-stage turbines presents better trade-off between RTE and investment cost than the three-stage and four-stage systems. Overall, this work provides, for the first time, an NSGA-II-based optimization framework capable of determining the optimal design and operational parameters of LAES, informing the stakeholders of the design guidelines and investment guidance under different scenarios.

Enhancing Electrical Power Demand Prediction Using LSTM-Based Deep Learning Models for Local Energy Communities

The pursuit of accurate electrical power demand forecasting has led to the application of deep learning algorithms, notably demonstrating promising outcomes despite the prerequisite of substantial training data. This study pioneers a new learning paradigm, employing sophisticated deep learning models specifically, Long Short-Term Memory networks and recurrent neural networks (RNNs). Leveraging historical load data, temperature, wind speed, and day-ahead predicted spot prices, this approach follows a structured flow involving data preprocessing, sequence generation, model training, and subsequent prediction of future load demand using LSTM-based RNN variants. The study’s paramount findings underscore the substantial advancement achieved by this proposed methodology over prevailing techniques. The method significantly improves prediction accuracy by over 11%, demonstrating the efficacy of deep learning models and a significant leap forward in forecasting precision. Beyond its superior predictive capabilities, this novel strategy serves as a catalyst for enhancing energy distribution management in local energy communities. Its effectiveness lies not only in its precision but also in enabling the optimization and cost-effective control of energy distribution, vital for sustainable energy management in these communities. Ultimately, this pioneering approach presents a robust solution poised to revolutionize the landscape of electrical power demand forecasting and its practical application in local energy systems.

Rational Design of CoOOH/α-Fe2O3/SnO2 for Boosted Photoelectrochemical Water Oxidation: The Roles of Underneath SnO2 and Surface CoOOH.

Hematite (α-Fe2O3) photoanode is a promising candidate for efficient PEC solar energy conversion. However, the serious charge recombination together with the sluggish water oxidation kinetics of α-Fe2O3 still restricts its practical application in renewable energy systems. In this work, a CoOOH/α-Fe2O3/SnO2 photoanode was fabricated, in which the ultrathin SnO2 underlayer is deposited on the fluorine-doped tin oxide (FTO) substrate, α-Fe2O3 nanorod array is the absorber layer, and CoOOH nanosheet is the surface modifier, respectively. The resulting CoOOH/α-Fe2O3/SnO2 exhibited excellent PEC water splitting with a high photocurrent density of 2.05 mA cm-2 at 1.23 V vs RHE in the alkaline electrolyte, which is ca. 3.25 times that of bare α-Fe2O3. PEC characterizations demonstrated that SnO2 not only could block hole transport from α-Fe2O3 to FTO substrate but also could efficiently enhance the light-harvesting property and reduce the surface states by controlling the growth process of α-Fe2O3, while the CoOOH overlayer as cocatalysts could rapidly extract the photogenerated holes and provide catalytic active sites for water oxidation. Benefiting from the synergistic effects of SnO2 and CoOOH, the efficiency of the charge recombination and the overpotential for water oxidation of α-Fe2O3 are obviously decreased, resulting in the boosted PEC efficiency for water oxidation. The rational design and simple fabrication strategy display great potentials to be used for other PEC systems with excellent efficiency.

Application of hybrid renewable energy systems for supplying electricity demand of a water pump station of agricultural plants: a case-based research

Abstract Employing clean energy production in agricultural purposes has attracted the attention of many researchers. One of the challenges is the flexible nature of irrigation of the plants that need to have a changeable power source of pump stations to supply the load demands. Renewable energies are among the best solutions to supply environmentally-friendly power, especially in remote areas where there is no access to the electricity. This study considers the needed water of five different plants, and according to the calculated hydromodule, the capacity of the pump station as well as its monthly and yearly load demands are determined. Based on the calculated load demand, different configurations of hybrid renewable energy systems (HRES) are considered, and the optimum sizes of equipment are determined. The needed load demand is 1463 kWh/day and peak load is 266.16 kW. Based on the suppositions and inputs of this study, results show that the best economic configuration would be PV/wind turbine/diesel generator/battery the way that cost of energy (COE) and net present cost (NPC are 0.28 ($/kWh) and $2.48 million. Also, the best environmentally friendly system (PV/wind turbine/battery) where CO2 emission is zero and RF is 100%, can be obtained with 647 kW PV panels and 106 wind turbines, the way that COE and NPC values are 0.5 ($/kWh) and 4.41 $ million. To reach the best technical system (PV/generator/battery), 514 kW PV, 100 kW diesel generator, and 1816 batteries would have the least unmeted load and excess electricity where COE and NPC values are 0.34 ($/kWh) and 2.98$ million.

Novel Nanocatalysts for Sustainable Hydrogen Production from Renewable Resources

This research delves into the development, manufacturing, and assessment of nanocatalysts with the purpose of producing hydrogen sustainably from renewable resources. Using the sol-gel, hydrothermal, co-precipitation, and solvothermal processes, four distinct catalysts with the labels A, B, C, and D were created, respectively. The rate of hydrogen generation, activation energy, turnover frequency, and surface area were used to assess the catalytic performance. Catalyst A outperformed Catalyst B in terms of hydrogen generation rate, with a 10% increase to 50 mmol/g/hr. Moreover, Catalyst A showed superior reaction kinetics with a lower activation energy of 50 kJ/mol. With a turnover frequency of 0.02 s^-1, catalyst C had the highest activity, indicating a higher catalytic activity per active site. Furthermore, with a surface area of 120 m^2/g, Catalyst D offered the most active locations for reactions that produce hydrogen. Environmental impact analyses showed that various catalysts used varied amounts of resources and produced varying amounts of waste. With 950 liters of water used and 45 kWh of energy consumption, Catalyst B showed the lowest use, whereas Catalyst D produced the least amount of chemical waste (6 kg). The results of the stability tests showed that the durability of the catalysts varied, with Catalyst D showing the maximum stability after 100 cycles. Overall, the results emphasize how crucial catalyst design and synthesis techniques are to the development of effective and long-lasting hydrogen generation technologies. To optimize catalyst compositions, improve stability, and scale up manufacturing for real-world applications in renewable energy systems, further research is necessary.