Energies

24 pages, 4949 KiB

Open AccessArticle

Equilibrium Interaction Strategies for Integrated Energy System Incorporating Demand-Side Management Based on Stackelberg Game Approach

by Kangli Xiang, Jinyu Chen, Li Yang, Jianfa Wu and Pengjia Shi

Energies 2024, 17(14), 3603; https://doi.org/10.3390/en17143603 - 22 Jul 2024

Viewed by 914

Abstract

This paper analyzes the balanced interaction strategy of an integrated energy system (IES) operator and an industrial user in the operation process of the IES under the demand-side management (DSM) based on game theory. Firstly, we establish an electric–thermal IES, which includes a [...] Read more.

This paper analyzes the balanced interaction strategy of an integrated energy system (IES) operator and an industrial user in the operation process of the IES under the demand-side management (DSM) based on game theory. Firstly, we establish an electric–thermal IES, which includes a power grid, a heat grid and a natural gas grid. Secondly, a two-stage Stackelberg dynamic game model is proposed to describe the game behavior of IES operators and industrial users in the process of participating in DSM. The interactions between the IES operator (leader) and the user (follower) are formulated into a one-leader–one-follower Stackelberg game, where optimization problems are formed for each player to help select the optimal strategy. A pricing function is adopted for regulating time-of-use (TOU), which acts as a coordinator, inducing users to join the game. Then, for the complex two-stage dynamic game model established, the lower user-side constraint optimization problem is replaced by its KKT condition, so that the two-stage hierarchical optimization problem is transformed into a single-stage mixed-integer nonlinear optimization model, and the branch-and-bound method is introduced to solve it. Finally, the equilibrium strategies and income values of both sides of the game are obtained through a case simulation, and the dynamic equilibrium strategy curves under different capacity configurations are obtained through the sensitivity analysis of key parameters. The equilibrium income of the IES is USD 93.859, while the equilibrium income of industrial users in the park is USD 92.720. The simulation results show that the proposed method and model are effective. Full article

(This article belongs to the Section K: State-of-the-Art Energy Related Technologies)

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28 pages, 17728 KiB

Open AccessArticle

Computational Fluid Dynamics Simulation on Blade Geometry of Novel Axial FlowTurbine for Wave Energy Extraction

by Mohammad Nasim Uddin, Yang Gao and Paul M. Akangah

Energies 2024, 17(14), 3602; https://doi.org/10.3390/en17143602 - 22 Jul 2024

Viewed by 1104

Abstract

Wave energy converters (WECs) utilizing the Oscillating Water Column (OWC) principle have gained prominence for harnessing kinetic energy from ocean waves. This study explores an innovative approach by transforming the pivoting Denniss–Auld turbine blades into a fixed configuration, offering a simplified alternative. The [...] Read more.

Wave energy converters (WECs) utilizing the Oscillating Water Column (OWC) principle have gained prominence for harnessing kinetic energy from ocean waves. This study explores an innovative approach by transforming the pivoting Denniss–Auld turbine blades into a fixed configuration, offering a simplified alternative. The fixed-blade design emulates the maximum pivot points during the OWC’s exhalation and inhalation phases. Traditional Denniss–Auld turbines rely on complex hub systems to enable controllable blade rotation for performance optimization. This research examines the turbine’s efficiency without mechanical actuation. The simulations were conducted using ANSYS™ CFX 2023 R2 to solve the three-dimensional, incompressible, steady-state Reynolds-Averaged Navier–Stokes (RANS) equations, employing the k-ω SST turbulence model to close the system of equations. A grid convergence study was performed, and the numerical results were validated against available experimental and numerical data. An in-depth analysis of the intricate flow field around the turbine blades was also conducted. The modified Denniss–Auld turbine demonstrated a broad operating range, avoiding stalling at high flow coefficients and exhibiting performance characteristics like an impulse turbine. However, the peak efficiency was 12%, significantly lower than that of conventional Denniss–Auld and impulse turbines. Future research should focus on expanding the design space through parametric studies to enhance turbine efficiency and power output. Full article

(This article belongs to the Topic Energy from Sea Waves)

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26 pages, 8942 KiB

Open AccessArticle

Energy Management of Green Port Multi-Energy Microgrid Based on Fuzzy Logic Control

by Yu Deng and Jingang Han

Energies 2024, 17(14), 3601; https://doi.org/10.3390/en17143601 - 22 Jul 2024

Cited by 1 | Viewed by 1033

Abstract

The green port multi-energy microgrid, featuring renewable energy generation, hydrogen energy, and energy storage systems, is an important gateway to achieve the net-zero emission goal. But there are many forms of energy in green port multi-energy microgrid systems, the power fluctuates frequently, and [...] Read more.

The green port multi-energy microgrid, featuring renewable energy generation, hydrogen energy, and energy storage systems, is an important gateway to achieve the net-zero emission goal. But there are many forms of energy in green port multi-energy microgrid systems, the power fluctuates frequently, and the port loads with large fluctuations and fast changes. These factors can easily lead to the problem of the state of charge exceeding the limit of the energy storage system. To distribute the fluctuating power in the green port multi-energy microgrid system reasonably and maintain the state of charge (SOC) of the hybrid energy storage system in an moderate range, an energy management strategy (EMS) based on dual-stage fuzzy control with a low pass-filter algorithm is proposed in this paper. First, the mathematical model of a green port multi-energy microgrid system is established. Then, fuzzy rules are designed, and the dual-stage fuzzy controller is used to change the time constant of the low-pass filter (LPF) and modify the initial power distribution by an LPF algorithm. Finally, simulation models are built in Matlab 2016a/Simulink. The simulation results demonstrate that, compared with other algorithms under the control of the EMS proposed in this paper, the high-frequency component in the flywheel power is smaller, and the SOC of the supercapacitor is maintained in a reasonable range of 34–78%, which extends the lifespan of the flywheel and supercapacitor. Additionally, it has a faster automatic adjustment ability for the state of charge of the energy storage system, which is conducive to better maintaining the stable operation of green port multi-energy microgrid systems. Full article

(This article belongs to the Section A1: Smart Grids and Microgrids)

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6 pages, 178 KiB

Open AccessEditorial

A Review of Exploration and Development Technologies for Coal, Oil, and Natural Gas

by Gan Feng, Guifeng Wang, Hongqiang Xie, Yaoqing Hu, Tao Meng and Gan Li

Energies 2024, 17(14), 3600; https://doi.org/10.3390/en17143600 - 22 Jul 2024

Cited by 1 | Viewed by 1266

Abstract

Energy is the fundamental prerequisite for human survival and development, as well as the driving force behind the progress of human civilization [...] Full article

(This article belongs to the Special Issue Advanced Coal, Petroleum and Nature Gas Exploration Technology, 2nd Edition)

20 pages, 8914 KiB

Open AccessArticle

Improved Amott Method to Determine Oil Recovery Dynamics from Water-Wet Limestone Using GEV Statistics

by Ksenia M. Kaprielova, Maxim P. Yutkin, Mahmoud Mowafi, Ahmed Gmira, Subhash Ayirala, Ali Yousef, Clayton J. Radke and Tadeusz W. Patzek

Energies 2024, 17(14), 3599; https://doi.org/10.3390/en17143599 - 22 Jul 2024

Viewed by 960

Abstract

Counter-current spontaneous imbibition of water is a critical oil recovery mechanism. In the laboratory, the Amott test is a commonly used method to assess the efficacy of brine imbibition into oil-saturated core plugs. The classic Amott-cell experiment estimates ultimate oil recovery, but not [...] Read more.

Counter-current spontaneous imbibition of water is a critical oil recovery mechanism. In the laboratory, the Amott test is a commonly used method to assess the efficacy of brine imbibition into oil-saturated core plugs. The classic Amott-cell experiment estimates ultimate oil recovery, but not the recovery dynamics that hold fundamental information about the imbibition mechanisms. Retention of oil droplets at the outer core surface and initial production delay are the two key artifacts of the classic Amott experiment. This retention, referred to here as the “external-surface oil holdup effect” or simply “oil holdup effect”, often results in stepwise recovery curves that obscure the true dynamics of spontaneous imbibition. To address these holdup drawbacks of the classic Amott method, we modified the Amott cell and experimental procedure. For the first time, using water-wet Indiana limestone cores saturated with brine and mineral oil, we showed that our improvements of the Amott method enabled accurate and reproducible measurements of oil recovery dynamics. Also for the first time, we used the generalized extreme value (GEV) statistics to describe oil production histories from water-wet heterogeneous limestone cores with finite initial water saturations. We demonstrated that our four-parameter GEV model accurately described the recovery dynamics, and that optimal GEV parameter values systematically reflected the key characteristics of the oil–rock system, such as oil viscosity and rock permeability. These findings gave us a more fundamental understanding of spontaneous, counter-current imbibition mechanisms and insights into what constitutes a predictive model of counter-current water imbibition into oil-saturated rocks with finite initial water saturation. Full article

(This article belongs to the Special Issue Oil Recovery and Simulation in Reservoir Engineering)

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21 pages, 6153 KiB

Open AccessArticle

Permeability Evolution of Shale during High-Ionic-Strength Water Sequential Imbibition

by Tianhao Bai, Sam Hashemi, Noune Melkoumian, Alexander Badalyan and Abbas Zeinijahromi

Energies 2024, 17(14), 3598; https://doi.org/10.3390/en17143598 - 22 Jul 2024

Cited by 1 | Viewed by 1116

Abstract

It is widely accepted in the oil and gas industry that high-ionic-strength water (HISW) can improve oil and gas recovery in unconventional shale reservoirs by limiting shale hydration. Despite numerous supporting studies, there is a lack of a systematic analysis exploring the effect [...] Read more.

It is widely accepted in the oil and gas industry that high-ionic-strength water (HISW) can improve oil and gas recovery in unconventional shale reservoirs by limiting shale hydration. Despite numerous supporting studies, there is a lack of a systematic analysis exploring the effect of HISW on shale permeability evolution, particularly considering varying chemical compositions. In this work, we investigated the impact of different concentrations of NaCl and CaCl₂ on shale permeability through sequential HISW imbibition experiments, beginning with the highest NaCl and lowest CaCl₂ concentrations. After maintaining the highest effective stress for an extended period, significant permeability reduction and potential fracture generation were observed, as indicated by periodic fluctuations in differential pressure. These effects were further intensified by displacements with HISW solutions. Advanced post-experimental analyses using micro-CT scans and SEM-EDS analysis revealed microstructural changes within the sample. Our findings offer initial insight into how HISW-shale interactions influence shale permeability, using innovative approaches to simulate reservoir conditions. The findings indicate that discrepancies in the chemical composition between injected solutions and shale may lead to shale disintegration during hydraulic fracturing processes. Full article

(This article belongs to the Topic Petroleum and Gas Engineering)

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14 pages, 2462 KiB

Open AccessArticle

Artificial Neural Network Model for Estimating the Pelton Turbine Shaft Power of a Micro-Hydropower Plant under Different Operating Conditions

by Raúl R. Delgado-Currín, Williams R. Calderón-Muñoz and J. C. Elicer-Cortés

Energies 2024, 17(14), 3597; https://doi.org/10.3390/en17143597 - 22 Jul 2024

Viewed by 2331

Abstract

The optimal performance of a hydroelectric power plant depends on accurate monitoring and well-functioning sensors for data acquisition. This study proposes the use of artificial neural networks (ANNs) to estimate the Pelton turbine shaft power of a 10 kW micro-hydropower plant. In the [...] Read more.

The optimal performance of a hydroelectric power plant depends on accurate monitoring and well-functioning sensors for data acquisition. This study proposes the use of artificial neural networks (ANNs) to estimate the Pelton turbine shaft power of a 10 kW micro-hydropower plant. In the event of a failure of the sensor measuring the torque and/or rotational speed of the Pelton turbine shaft, the synthetic turbine shaft power data generated by the ANN will allow the turbine output power to be determined. The experimental data were obtained by varying the operating conditions of the micro-hydropower plant, including the variation of the input power to the electric generator and the variation of the injector opening. These changes consequently affected the flow rate and the pressure head at the turbine inlet. The use of artificial neural networks (ANNs) was deemed appropriate due to their ability to model complex relationships between input and output variables. The ANN structure comprised five input variables, fifteen neurons in a hidden layer and an output variable estimating the Pelton turbine power. During the training phase, algorithms such as Levenberg–Marquardt (L–M), Scaled Conjugate Gradient (SCG) and Bayesian were employed. The results indicated an error of 0.39% with L–M and 7% with SCG, with the latter under high-flow and -energy consumption conditions. This study demonstrates the effectiveness of artificial neural networks (ANNs) trained with the Levenberg–Marquardt (L–M) algorithm in estimating turbine shaft power. This contributes to improved performance and decision making in the event of a torque sensor failure. Full article

(This article belongs to the Section A3: Wind, Wave and Tidal Energy)

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15 pages, 1606 KiB

Open AccessArticle

Integration of Electric Vehicle Power Supply Systems—Case Study Analysis of the Impact on a Selected Urban Network in Türkiye

by Wojciech Lewicki, Hasan Huseyin Coban and Jacek Wróbel

Energies 2024, 17(14), 3596; https://doi.org/10.3390/en17143596 - 22 Jul 2024

Cited by 3 | Viewed by 1034

Abstract

Undoubtedly, the transition to electromobility with several million new, efficient charging points will have consequences for the energy industry, and in particular for network operators of the distribution infrastructure. At the same time, in the coming years the energy landscape will change into [...] Read more.

Undoubtedly, the transition to electromobility with several million new, efficient charging points will have consequences for the energy industry, and in particular for network operators of the distribution infrastructure. At the same time, in the coming years the energy landscape will change into a system in which an increase in decentralized systems based on renewable energy sources will take over the leading function. This transformation process will further increase the complexity and overall pressure for change in energy systems over the next decade. In order to be able to ensure the energy supply and the reliable system operation of the grids in the future as well, communicative networking of generators, storage systems, electrical consumers and grid equipment is indispensable. This study aims to investigate the consequences of including electric vehicles in Istanbul’s power system using a unit commitment simulation model. The presented considerations analyze how uncertain and managed charging strategies affect the power system in terms of operating costs and renewable resources. The presented simulations indicate that, in economic terms, the use of a managed charging strategy saves 2.3%, reducing the total cost from USD 66.71 million to USD 65.18 million. The recipients of the presented research are both the demand and supply sides of the future energy transformation based on the idea of synergy of electromobility and renewable energy sources within the framework of the smart city idea. Full article

(This article belongs to the Special Issue Electric Vehicles for Smart Cities: Trends, Challenges and Opportunities)

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15 pages, 3997 KiB

Open AccessArticle

A Generalized Load Model Considering the Fault Ride-Through Capability of Distributed PV Generation System

by Haiyun Wang, Qian Chen, Linyu Zhang, Xiyu Yin, Han Cui, Zhijian Zhang, Huayue Wei and Xiaoyue Chen

Energies 2024, 17(14), 3595; https://doi.org/10.3390/en17143595 - 22 Jul 2024

Viewed by 694

Abstract

Considering the voltage stability problem brought by large-scale distributed PV access to the distribution network, this paper proposes a generalized load model that considers the fault ride-through capability of distributed PV. Firstly, the detailed model of the distribution network is established, and the [...] Read more.

Considering the voltage stability problem brought by large-scale distributed PV access to the distribution network, this paper proposes a generalized load model that considers the fault ride-through capability of distributed PV. Firstly, the detailed model of the distribution network is established, and the detailed model is calibrated based on the measured data, the simulation errors are below 1%. And then establish a generalized load model considering distributed PV high and low voltage traversal ability. The sensitivity analysis results are used to rank the parameters to be identified, and the parameters with higher sensitivity are identified. The parameters are obtained from the detailed model and measured data, and four sets of parameters are identified and simulated under different PV penetration rates and fault conditions. The calculated fitting errors are less than 1%. The results show that the generalized load gray box model of the distribution network with distributed PV high and low voltage ride-through capability can reflect the dynamic characteristics of the distribution network well. Full article

(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)

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2 pages, 357 KiB

Open AccessCorrection

Correction: Meena et al. Innovation in Green Building Sector for Sustainable Future. Energies 2022, 15, 6631

by Chandan Swaroop Meena, Ashwani Kumar, Siddharth Jain, Ateeq Ur Rehman, Sachin Mishra, Naveen Kumar Sharma, Mohit Bajaj, Muhammad Shafiq and Elsayed Tag Eldin

Energies 2024, 17(14), 3594; https://doi.org/10.3390/en17143594 - 22 Jul 2024

Viewed by 582

Abstract

Error in Figure [...] Full article

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18 pages, 4741 KiB

Open AccessArticle

The Effect of Hydrogen as a Coolant on the Characteristics of Humidification-Dehumidification Desalination Systems

by Antar M. M. Abdala, Fifi N. M. Elwekeel and Rodolfo Taccani

Energies 2024, 17(14), 3593; https://doi.org/10.3390/en17143593 - 22 Jul 2024

Viewed by 754

Abstract

The air humidification-dehumidification (HDH) technique for water desalination can be useful in many water production applications. Researchers from all around the world have examined various implementations of this technology to improve it. The present research investigates the effect of three dehumidifier coolants on [...] Read more.

The air humidification-dehumidification (HDH) technique for water desalination can be useful in many water production applications. Researchers from all around the world have examined various implementations of this technology to improve it. The present research investigates the effect of three dehumidifier coolants on the system. These coolants include water, helium, and hydrogen. The impact of these coolants on the parameters of the humidification-dehumidification desalination system will be discussed. The investigation’s parameters are tested at various mass ratios, air flow rates, and air outlet heaters. The results show that when hydrogen is employed as a dehumidifier coolant, the gained output ratio (GOR) achieves its peak of 6.37 in the considered mass ratio range of 2.1 to 3. On the other hand, when hydrogen is utilized as a dehumidifier coolant, the system produces the maximum entropy, with the dehumidifier contributing the most. When the mass ratio changes from 2 to 3, the average entropy generation for the system using hydrogen in the dehumidifier increases by 3.8 and 2.9 times, respectively, compared to the average entropy generation for the system using water and helium. However, when hydrogen is used as a dehumidifier coolant, safety concerns must be addressed, as well as the size and cost of heat exchangers in comparison to water. Full article

(This article belongs to the Section J: Thermal Management)

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33 pages, 18076 KiB

Open AccessArticle

Multi-Agent Reinforcement Learning Optimization Framework for On-Grid Electric Vehicle Charging from Base Transceiver Stations Using Renewable Energy and Storage Systems

by Abdullah Altamimi, Muhammad Bilal Ali, Syed Ali Abbas Kazmi and Zafar A. Khan

Energies 2024, 17(14), 3592; https://doi.org/10.3390/en17143592 - 22 Jul 2024

Viewed by 1067

Abstract

Rapid growth in a number of developing nations’ mobile telecommunications sectors presents network operators with difficulties such as poor service quality and congestion, mostly because these locations lack a dependable and reasonably priced electrical source. In order to provide a sustainable and reasonably [...] Read more.

Rapid growth in a number of developing nations’ mobile telecommunications sectors presents network operators with difficulties such as poor service quality and congestion, mostly because these locations lack a dependable and reasonably priced electrical source. In order to provide a sustainable and reasonably priced energy alternative for the developing world, this study provides a detailed examination of the core ideas behind renewable energy technology (RET). A multi-agent-based small-scaled smart base transceiver station (BTS) site reinforcement strategy is presented to manage energy resources by boosting resilience so to supply power to essential loads in peak demand periods by leveraging demand-side management (DSM). Diverse energy sources are combined to create interconnected BTS sites, which enable energy sharing to balance fluctuations by establishing a market that promotes economical energy. A MATLAB simulation model was developed to assess the effectiveness of the proposed system by using real load data and fast electric vehicle charging loads from five different base transceiver stations (BTSs) located throughout Pakistan’s southern area. In this proposed study, the base transceiver station (BTS) sites can share their energy through a multi-agent-based system. From the results, it is observed that, after optimization, the base transceiver station (BTS) sites trade their energy with the grid at rate of 0.08 USD/kWh and with other sites at a rate of 0.04 USD/kWh. Therefore, grid dependency is decreased by 44.3% and carbon emissions are reduced by 71.4% after the optimization of the base transceiver station (BTS) sites. Full article

(This article belongs to the Section A: Sustainable Energy)

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20 pages, 1948 KiB

Open AccessReview

Crystal Structure Prediction and Performance Assessment of Hydrogen Storage Materials: Insights from Computational Materials Science

by Xi Yang, Yuting Li, Yitao Liu, Qian Li, Tingna Yang and Hongxing Jia

Energies 2024, 17(14), 3591; https://doi.org/10.3390/en17143591 - 22 Jul 2024

Cited by 1 | Viewed by 1414

Abstract

Hydrogen storage materials play a pivotal role in the development of a sustainable hydrogen economy. However, the discovery and optimization of high-performance storage materials remain a significant challenge due to the complex interplay of structural, thermodynamic and kinetic factors. Computational materials science has [...] Read more.

Hydrogen storage materials play a pivotal role in the development of a sustainable hydrogen economy. However, the discovery and optimization of high-performance storage materials remain a significant challenge due to the complex interplay of structural, thermodynamic and kinetic factors. Computational materials science has emerged as a powerful tool to accelerate the design and development of novel hydrogen storage materials by providing atomic-level insights into the storage mechanisms and guiding experimental efforts. In this comprehensive review, we discuss the recent advances in crystal structure prediction and performance assessment of hydrogen storage materials from a computational perspective. We highlight the applications of state-of-the-art computational methods, including density functional theory (DFT), molecular dynamics (MD) simulations, and machine learning (ML) techniques, in screening, evaluating, and optimizing storage materials. Special emphasis is placed on the prediction of stable crystal structures, assessment of thermodynamic and kinetic properties, and high-throughput screening of material space. Furthermore, we discuss the importance of multiscale modeling approaches that bridge different length and time scales, providing a holistic understanding of the storage processes. The synergistic integration of computational and experimental studies is also highlighted, with a focus on experimental validation and collaborative material discovery. Finally, we present an outlook on the future directions of computationally driven materials design for hydrogen storage applications, discussing the challenges, opportunities, and strategies for accelerating the development of high-performance storage materials. This review aims to provide a comprehensive and up-to-date account of the field, stimulating further research efforts to leverage computational methods to unlock the full potential of hydrogen storage materials. Full article

(This article belongs to the Special Issue Efficient Energy Conversion and Storage via Electrochemical Strategies)

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14 pages, 4537 KiB

Open AccessFeature PaperArticle

Numerical Simulation Method of Hydraulic Power Take-Off of Point-Absorbing Wave Energy Device Based on Simulink

by Fengmei Jing, Song Wang, Tonio Sant, Christopher Micallef and Jean Paul Mollicone

Energies 2024, 17(14), 3590; https://doi.org/10.3390/en17143590 - 22 Jul 2024

Viewed by 895

Abstract

Wave energy has a high energy density and strong predictability, presenting encouraging prospects for development. So far, there are dozens of different wave energy devices (WECs), but the mechanism that ultimately converts wave energy into electrical energy in these devices has always been [...] Read more.

Wave energy has a high energy density and strong predictability, presenting encouraging prospects for development. So far, there are dozens of different wave energy devices (WECs), but the mechanism that ultimately converts wave energy into electrical energy in these devices has always been the focus of research by scholars from various countries. The energy conversion mechanism in wave energy devices is called PTO (power take-off). According to different working principles, PTOs can be classified into the linear motor type, hydraulic type, and mechanical type. Hydraulic PTOs are characterized by their high efficiency, low cost, and simple installation. They are widely used in the energy conversion links of various wave energy devices. However, apart from experimental methods, there is currently almost no concise numerical method to predict and evaluate the power generation performance of hydraulic PTO. Therefore, based on the working principle of hydraulic PTO, this paper proposes a numerical method to simulate the performance of a hydraulic PTO using MATLAB(2018b) Simulink^®. Using a point-absorption wave energy device as a carrier, a float hydraulic system power-generation numerical model is built. The method is validated by comparison with previous experimental results. The predicted power generation and conversion efficiency of the point-absorption wave energy device under different regular and irregular wave conditions are compared. Key factors affecting the power generation performance of the device were investigated, providing insight for the subsequent optimal design of the device, which is of great significance to the development and utilization of wave energy resources. Full article

(This article belongs to the Special Issue Advances in Ocean Energy Technologies and Applications)

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16 pages, 4375 KiB

Open AccessArticle

Performance Analysis of an Ejector-Enhanced Heat Pump System for Low-Temperature Waste Heat Recovery Using UHVDC Converter Valves

by Menghan Jin, Xingjuan Zhang, Jianhui Zhou and Limin Zhang

Energies 2024, 17(14), 3589; https://doi.org/10.3390/en17143589 - 21 Jul 2024

Cited by 1 | Viewed by 943

Abstract

This article proposes a heating method based on heat pump technology to address the large amount of low-grade waste heat generated by a certain type of ultra-high voltage direct current (UHVDC) converter valve. Thermal performance calculations for two systems, a basic vapor compression [...] Read more.

This article proposes a heating method based on heat pump technology to address the large amount of low-grade waste heat generated by a certain type of ultra-high voltage direct current (UHVDC) converter valve. Thermal performance calculations for two systems, a basic vapor compression heat pump system (BVCHPS) based on thermal expansion valve throttling and an ejector-enhanced heat pump system (EEHPS) are analyzed. The research results show that the EEHPS exhibits superior COP and exergy efficiency when generating hot water above 80 °C using a heat source below 50 °C. Additionally, mathematical modeling analysis identifies optimal structural parameters such as nozzle throat diameter, throat area ratio, and nozzle outlet diameter for the ejector in its design state. The low-temperature waste heat recovered from the UHVDC converter valves can be further used in engineering applications such as heating, refrigeration, seawater desalination, and sewage treatment. Full article

(This article belongs to the Section J1: Heat and Mass Transfer)

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16 pages, 3928 KiB

Open AccessArticle

A Study on the Problem of AC Corrosion of Power Umbilical Cables Caused by Electromagnetic Induction Phenomena

by Pengjin Shao, Haijun Li, Pan Pan, Qibing Shao, Zhen Li and Jiaming Yang

Energies 2024, 17(14), 3588; https://doi.org/10.3390/en17143588 - 21 Jul 2024

Viewed by 961

Abstract

During the normal laying and operation of a three-core umbilical cable, AC current can easily lead to AC electrochemical corrosion on the outer surface of the steel tube. To explore the electrochemical corrosion mechanism and the factors affecting the three-core umbilical cable, this [...] Read more.

During the normal laying and operation of a three-core umbilical cable, AC current can easily lead to AC electrochemical corrosion on the outer surface of the steel tube. To explore the electrochemical corrosion mechanism and the factors affecting the three-core umbilical cable, this paper optimizes the internal induced potential calculation method for three-core umbilical cables. It analyzes the changes in the characteristics of the induced potential and explores the variations in the density of induced current under different conditions. The research results show that by optimizing the calculation method for the induction potential of the umbilical cable’s steel pipe, for the electromagnetic significance of the smallest repeating unit, the induction potential on the steel pipe’s surface exhibited a cyclic change. The peak part of the induction potential is most likely to experience electrochemical corrosion. Additionally, reducing the radius of the outer insulation aperture of the steel pipe and improving the conductivity of seawater will increase the density of the induced current in the insulation aperture, thereby increasing the risk of electrochemical corrosion. As the cable pitch and AC frequency increase, the current density in the steel pipe pores will also rise. Full article

(This article belongs to the Section F1: Electrical Power System)

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21 pages, 1069 KiB

Open AccessArticle

Phasor Measurement Unit-Driven Estimation of Transmission Line Parameters Using Variable Noise Model

by Felipe Proença de Albuquerque, Rafael Nascimento, Carlos A. Prete, Jr. and Eduardo Coelho Marques da Costa

Energies 2024, 17(14), 3587; https://doi.org/10.3390/en17143587 - 21 Jul 2024

Viewed by 1010

Abstract

Accurate parameters are crucial in modern energy systems to ensure the reliable operation of all components. Given the substantial volume of data in monitored systems, high-performance methods are necessary. This paper proposes a new Bayesian multi-output regressor for estimating the parameters of a [...] Read more.

Accurate parameters are crucial in modern energy systems to ensure the reliable operation of all components. Given the substantial volume of data in monitored systems, high-performance methods are necessary. This paper proposes a new Bayesian multi-output regressor for estimating the parameters of a three-phase transmission line. The presented approach achieves acceptable accuracy in parameter estimation using only one end of the line. The Bayesian regressor is developed using information derived from the data themselves, eliminating the need to explicitly model the system. This capability allows the method to estimate parameters while accommodating different noise models, even in the presence of systematic errors and non-Gaussian random noise. The methodology was validated on various systems, including a two-bus system, IEEE 14-bus, IEEE 39-bus, and IEEE 118-bus, under diverse conditions such as varying sample sizes, loads, and noise levels. These tests demonstrate the robustness of the proposed approach. Full article

(This article belongs to the Section F3: Power Electronics)

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22 pages, 2347 KiB

Open AccessEditor’s ChoiceArticle

Well Integrity in Salt Cavern Hydrogen Storage

by Omid Ahmad Mahmoudi Zamani and Dariusz Knez

Energies 2024, 17(14), 3586; https://doi.org/10.3390/en17143586 - 21 Jul 2024

Cited by 4 | Viewed by 2669

Abstract

Underground hydrogen storage (UHS) in salt caverns is a sustainable energy solution to reduce global warming. Salt rocks provide an exceptional insulator to store natural hydrogen, as they have low porosity and permeability. Nevertheless, the salt creeping nature and hydrogen-induced impact on the [...] Read more.

Underground hydrogen storage (UHS) in salt caverns is a sustainable energy solution to reduce global warming. Salt rocks provide an exceptional insulator to store natural hydrogen, as they have low porosity and permeability. Nevertheless, the salt creeping nature and hydrogen-induced impact on the operational infrastructure threaten the integrity of the injection/production wells. Furthermore, the scarcity of global UHS initiatives indicates that investigations on well integrity remain insufficient. This study strives to profoundly detect the research gap and imperative considerations for well integrity preservation in UHS projects. The research integrates the salt critical characteristics, the geomechanical and geochemical risks, and the necessary measurements to maintain well integrity. The casing mechanical failure was found as the most challenging threat. Furthermore, the corrosive and erosive effects of hydrogen atoms on cement and casing may critically put the well integrity at risk. The research also indicated that the simultaneous impact of temperature on the salt creep behavior and hydrogen-induced corrosion is an unexplored area that has scope for further research. This inclusive research is an up-to-date source for analysis of the previous advancements, current shortcomings, and future requirements to preserve well integrity in UHS initiatives implemented within salt caverns. Full article

(This article belongs to the Special Issue Advanced Methods for Hydrogen Production, Storage and Utilization)

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25 pages, 541 KiB

Open AccessReview

Magnetocaloric Refrigeration in the Context of Sustainability: A Review of Thermodynamic Bases, the State of the Art, and Future Prospects

by Umberto Lucia and Giulia Grisolia

Energies 2024, 17(14), 3585; https://doi.org/10.3390/en17143585 - 21 Jul 2024

Viewed by 1382

Abstract

At present, one of the main challenges that industry faces is its impact on global warming, linked to the greenhouse effect and ozone hole problems. These two environmental issues have not yet been solved completely and, concerning the industrial cold sector, countries are [...] Read more.

At present, one of the main challenges that industry faces is its impact on global warming, linked to the greenhouse effect and ozone hole problems. These two environmental issues have not yet been solved completely and, concerning the industrial cold sector, countries are making various decisions on refrigerants. Magnetic refrigeration potentially represents a less impactful refrigeration technology. In this review, the physical basis of magnetic refrigeration is analysed, in order to propose this technology for industrial use. Full article

(This article belongs to the Section A: Sustainable Energy)

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24 pages, 6297 KiB

Open AccessFeature PaperArticle

Harnessing Artificial Neural Networks for Financial Analysis of Investments in a Shower Heat Exchanger

by Sabina Kordana-Obuch, Mariusz Starzec and Beata Piotrowska

Energies 2024, 17(14), 3584; https://doi.org/10.3390/en17143584 - 21 Jul 2024

Viewed by 888

Abstract

This study focused on assessing the financial efficiency of investing in a horizontal shower heat exchanger. The analysis was based on net present value (NPV). The research also examined the possibility of using artificial neural networks and SHapley Additive exPlanation (SHAP) [...] Read more.

This study focused on assessing the financial efficiency of investing in a horizontal shower heat exchanger. The analysis was based on net present value (NPV). The research also examined the possibility of using artificial neural networks and SHapley Additive exPlanation (SHAP) analysis to assess the profitability of the investment and the significance of individual parameters affecting the NPV of the project related to installing the heat exchanger in buildings. Comprehensive research was conducted, considering a wide range of input parameters. As a result, 1,215,000 NPV values were obtained, ranging from EUR −1996.40 to EUR 36,933.83. Based on these values, artificial neural network models were generated, and the one exhibiting the highest accuracy in prediction was selected (R² ≈ 0.999, RMSE ≈ 57). SHAP analysis identified total daily shower length and initial energy price as key factors influencing the profitability of the shower heat exchanger. The least influential parameter was found to be the efficiency of the hot water heater. The research results can contribute to improving systems for assessing the profitability of investments in shower heat exchangers. The application of the developed model can also help in selecting appropriate technical parameters of the system to achieve maximum financial benefits. Full article

(This article belongs to the Special Issue Solutions towards Zero Carbon Buildings)

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22 pages, 5706 KiB

Open AccessArticle

Two-Stage Optimal Scheduling for Urban Snow-Shaped Distribution Network Based on Coordination of Source-Network-Load-Storage

by Zhe Wang, Jiali Duan, Fengzhang Luo and Xuan Wu

Energies 2024, 17(14), 3583; https://doi.org/10.3390/en17143583 - 21 Jul 2024

Viewed by 881

Abstract

With the widespread integration of distributed resources, optimizing the operation of urban distribution networks faces challenges including uneven source-load-storage distribution, fluctuating feeder power flows, load imbalances, and network congestion. The urban snow-shaped distribution network (SDN), characterized by numerous intra-station and inter-station tie switches, [...] Read more.

With the widespread integration of distributed resources, optimizing the operation of urban distribution networks faces challenges including uneven source-load-storage distribution, fluctuating feeder power flows, load imbalances, and network congestion. The urban snow-shaped distribution network (SDN), characterized by numerous intra-station and inter-station tie switches, serves as a robust framework to intelligently address these issues. This study focuses on enhancing the safe and efficient operation of SDNs through a two-phase optimal scheduling model that coordinates source-network-load-storage. In the day-ahead scheduling phase, an optimization model is formulated to minimize operational costs and mitigate load imbalances. This model integrates network reconfiguration, energy storage systems (ESSs), and flexible load (FL). During intra-day scheduling, a rolling optimization model based on model predictive control adjusts operations using the day-ahead plan to minimize the costs and penalties associated with power adjustments. It provides precise control over ESS and FL outputs, promptly correcting deviations caused by prediction errors. Finally, the proposed model is verified by an actual example of a snow-shaped distribution network in Tianjin. The results indicate significant improvements in leveraging coordinated interactions among source-network-load-storage, effectively reducing spatial-temporal load imbalances within feeder clusters and minimizing the impact of prediction inaccuracies. Full article

(This article belongs to the Special Issue Control of Renewable Energy Sources in Power Systems and Smart Grids: 2nd Edition)

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23 pages, 25132 KiB

Open AccessArticle

A Gap Nonlinearity Compensation Strategy for Non-Direct-Drive Servo Systems

by Bo Wang, Runze Ji, Chengpeng Zhou, Rana M. Sohel, Kai Liu, Wei Hua and Hairong Ye

Energies 2024, 17(14), 3582; https://doi.org/10.3390/en17143582 - 21 Jul 2024

Viewed by 697

Abstract

In this paper, a gap nonlinear compensation strategy is proposed for the full closed-loop control structure of non-direct-drive servo motor systems. Firstly, an improved deadband model containing the initial value of the gap is proposed, and two gap amplitude identification methods, namely, incremental [...] Read more.

In this paper, a gap nonlinear compensation strategy is proposed for the full closed-loop control structure of non-direct-drive servo motor systems. Firstly, an improved deadband model containing the initial value of the gap is proposed, and two gap amplitude identification methods, namely, incremental torque and velocity difference integral, are compared. Then, for the full closed-loop structure, based on the describing function and the stability theory of the nonlinear system, the limit-loop oscillating frequency and the influencing factors are predicted, which are related to the system control stiffness and independent of the gap amplitude; finally, the state-feedback control is proposed, and the feedback coefficients are designed by using the pole configuration, making the system a pseudo-linear system. Simulation and experimental verification show that the method can suppress the limit loop oscillation, attenuate the system shock, and have a certain robustness. Full article

(This article belongs to the Section F3: Power Electronics)

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22 pages, 5900 KiB

Open AccessFeature PaperArticle

Control of Grid-Connected and Standalone Microhydraulic Turbine Using a Six-Phase Induction Generator

by Marius Ouédraogo, Amine Yazidi and Franck Betin

Energies 2024, 17(14), 3581; https://doi.org/10.3390/en17143581 - 21 Jul 2024

Viewed by 1087

Abstract

Microhydraulic turbines offer a promising solution for decentralized energy production, suitable for both grid-connected and standalone applications, due to their compactness and high efficiency. This paper introduces a control approach for such systems employing microhydraulic turbines as distributed generators (DGs), utilizing six-phase induction [...] Read more.

Microhydraulic turbines offer a promising solution for decentralized energy production, suitable for both grid-connected and standalone applications, due to their compactness and high efficiency. This paper introduces a control approach for such systems employing microhydraulic turbines as distributed generators (DGs), utilizing six-phase induction generators for electricity production. This study emphasizes control strategies for both grid-connected and standalone modes utilizing proportional-integral (PI) controllers. An integrated energy storage system based on Li-Ion battery technology is also implemented to store the excess energy and compensate for production deficits to meet demand. The results obtained using MATLAB/Simulink demonstrate efficient and reliable power management among production sources, the grid and the local load, highlighting the unique contribution of employing a six-phase induction generator with the energy storage system. Full article

(This article belongs to the Special Issue Advanced Control Strategies for Multiphase Induction Generators: Design, Optimization, and Application 2024)

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26 pages, 5228 KiB

Open AccessArticle

Application of Quantum Neural Network for Solar Irradiance Forecasting: A Case Study Using the Folsom Dataset, California

by Victor Oliveira Santos, Felipe Pinto Marinho, Paulo Alexandre Costa Rocha, Jesse Van Griensven Thé and Bahram Gharabaghi

Energies 2024, 17(14), 3580; https://doi.org/10.3390/en17143580 - 21 Jul 2024

Cited by 2 | Viewed by 1491

Abstract

Merging machine learning with the power of quantum computing holds great potential for data-driven decision making and the development of powerful models for complex datasets. This area offers the potential for improving the accuracy of the real-time prediction of renewable energy production, such [...] Read more.

Merging machine learning with the power of quantum computing holds great potential for data-driven decision making and the development of powerful models for complex datasets. This area offers the potential for improving the accuracy of the real-time prediction of renewable energy production, such as solar irradiance forecasting. However, the literature on this topic is sparse. Addressing this knowledge gap, this study aims to develop and evaluate a quantum neural network model for solar irradiance prediction up to 3 h in advance. The proposed model was compared with Support Vector Regression, Group Method of Data Handling, and Extreme Gradient Boost classical models. The proposed framework could provide competitive results compared to its competitors, considering forecasting intervals of 5 to 120 min ahead, where it was the fourth best-performing paradigm. For 3 h ahead predictions, the proposed model achieved the second-best results compared with the other approaches, reaching a root mean squared error of 77.55 W/m² and coefficient of determination of 80.92% for global horizontal irradiance forecasting. The results for longer forecasting horizons suggest that the quantum model may process spatiotemporal information from the input dataset in a manner not attainable by the current classical approaches, thus improving forecasting capacity in longer predictive windows. Full article

(This article belongs to the Section A: Sustainable Energy)

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20 pages, 12983 KiB

Open AccessEditor’s ChoiceArticle

Determination of Ambient Air Vaporizers’ Performance Based on a Study on Heat Transfer in Longitudinal Finned Tubes

by Filip Lisowski and Edward Lisowski

Energies 2024, 17(14), 3579; https://doi.org/10.3390/en17143579 - 21 Jul 2024

Viewed by 1409

Abstract

Ambient air vaporizers (AVVs) are the most commonly used type of heat exchanger for cryogenic regasification stations. The transfer of heat from the environment for heating the liquefied gas and its vaporization is a cost-free and efficient method. Designing ambient air vaporizers for [...] Read more.

Ambient air vaporizers (AVVs) are the most commonly used type of heat exchanger for cryogenic regasification stations. The transfer of heat from the environment for heating the liquefied gas and its vaporization is a cost-free and efficient method. Designing ambient air vaporizers for regasification or fueling stations requires accepting the size and related thermal power of the AVV considering the operating conditions and the type of liquefied gases to be vaporized. The nominal capacity of the ambient air vaporizer depends on its design, the frosting of longitudinal finned tubes, and the airflow through the vaporizer structure. This paper presents the results of experimental studies and computational fluid dynamics (CFD) analysis on determining the heat output of AVV longitudinal finned tubes depending on their design. This experiment was conducted in order to establish a numerical model. The relation between the longitudinal finned tubes thermal power and the air flow velocity is demonstrated and the beneficial effect of forced convection is proved. The obtained results are used for verification calculations of ambient air vaporizers’ performance depending on the size of the AVV, the profile cross-section, and the airflow velocity for different liquefied gases. Under conditions of forced convection, profiles with 12 equal-height fins were discovered to be the most efficient for higher airflow velocity providing up to 7% higher heat rate than profiles with 8 equal-height fins. However, at low air velocity, profiles with 8 equal-length fins showed a comparable heat output to profiles with 12 equal-length fins. Profiles with 8 and 12 unequal high fins differ in average heat output by about 28%. The profile with 12 unequal high fins turned out to be the least effective when 2D airflow was considered in this analysis. Full article

(This article belongs to the Collection Advances in Heat Transfer Enhancement)

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22 pages, 4748 KiB

Open AccessArticle

A Deep Reinforcement Learning Approach to DC-DC Power Electronic Converter Control with Practical Considerations

by Nafiseh Mazaheri, Daniel Santamargarita, Emilio Bueno, Daniel Pizarro and Santiago Cobreces

Energies 2024, 17(14), 3578; https://doi.org/10.3390/en17143578 - 21 Jul 2024

Viewed by 1635

Abstract

In recent years, there has been a growing interest in using model-free deep reinforcement learning (DRL)-based controllers as an alternative approach to improve the dynamic behavior, efficiency, and other aspects of DC–DC power electronic converters, which are traditionally controlled based on small signal [...] Read more.

In recent years, there has been a growing interest in using model-free deep reinforcement learning (DRL)-based controllers as an alternative approach to improve the dynamic behavior, efficiency, and other aspects of DC–DC power electronic converters, which are traditionally controlled based on small signal models. These conventional controllers often fail to self-adapt to various uncertainties and disturbances. This paper presents a design methodology using proximal policy optimization (PPO), a widely recognized and efficient DRL algorithm, to make near-optimal decisions for real buck converters operating in both continuous conduction mode (CCM) and discontinuous conduction mode (DCM) while handling resistive and inductive loads. Challenges associated with delays in real-time systems are identified. Key innovations include a chattering-reduction reward function, engineering of input features, and optimization of neural network architecture, which improve voltage regulation, ensure smoother operation, and optimize the computational cost of the neural network. The experimental and simulation results demonstrate the robustness and efficiency of the controller in real scenarios. The findings are believed to make significant contributions to the application of DRL controllers in real-time scenarios, providing guidelines and a starting point for designing controllers using the same method in this or other power electronic converter topologies. Full article

(This article belongs to the Section F: Electrical Engineering)

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19 pages, 7242 KiB

Open AccessArticle

Switching Current Predictive Control of a Permanent Magnet Synchronous Motor Based on the Exponential Moving Average Algorithm

by Fengming Yu and Jun Liu

Energies 2024, 17(14), 3577; https://doi.org/10.3390/en17143577 - 21 Jul 2024

Viewed by 923

Abstract

To improve the dynamic and steady-state control performance of permanent magnet synchronous motors under the three-vector model predictive current control method, this study proposes a switching current predictive control method based on the exponential moving average algorithm, which evaluates the magnitude of the [...] Read more.

To improve the dynamic and steady-state control performance of permanent magnet synchronous motors under the three-vector model predictive current control method, this study proposes a switching current predictive control method based on the exponential moving average algorithm, which evaluates the magnitude of the change of the q-axis current slope in real time to discriminate the motor’s operating conditions and selects the optimal control method for different operating conditions. Meanwhile, the traditional three-vector model predictive current control method is improved by introducing a comparison mechanism for the q-axis current slope to select the second effective voltage vector, avoiding the secondary optimization calculation of the value function and reducing the computational complexity of the traditional method. By comparing the proposed method with the traditional three-vector model predictive current control method, the experimental results prove that the proposed method improves the system’s dynamic response and steady-state performance. Full article

(This article belongs to the Special Issue Power Electronic and Power Conversion Systems for Renewable Energy)

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15 pages, 274 KiB

Open AccessEditor’s ChoiceArticle

Socioeconomic Factors Driving the Transition to a Low-Carbon Energy System

by Evangelia Karasmanaki, Spyros Galatsidas and Georgios Tsantopoulos

Energies 2024, 17(14), 3576; https://doi.org/10.3390/en17143576 - 20 Jul 2024

Viewed by 1110

Abstract

Citizen participation via different investment schemes may be a promising solution to the financing barriers inhibiting energy transition. In this regard, citizens may be approached as potential investors in renewables, but, to mobilize their capital, strategies need to be developed. Much like other [...] Read more.

Citizen participation via different investment schemes may be a promising solution to the financing barriers inhibiting energy transition. In this regard, citizens may be approached as potential investors in renewables, but, to mobilize their capital, strategies need to be developed. Much like other services or products seeking to improve their market position, renewable energy investments by citizens also require dedicated efforts to acquire a strong market position. Using a large sample of Greek citizens, this study investigated whether it is possible to identify distinct and addressable citizen clusters which can enable energy developers and marketers to effectively address the preferences and needs of potential investor segments. The performance of k-means cluster analysis identified four clusters: Indifferent Investors were neither driven by economic or social factors, Enthusiastic Investors were motivated both by economic and social factors, Pro-environmental Investors were driven by the environmental benefits, and Social Investors were motivated by the social aspects of the investment. Moreover, each cluster demonstrated different levels of willingness-to-invest in renewable energy and were knowledge about renewable energy investments. It was concluded that citizens should not be approached as a homogeneous target group by marketing experts and policymakers, while novel strategies should be followed. Full article

(This article belongs to the Special Issue Sustainable and Low Carbon Development in the Energy Sector)

22 pages, 3184 KiB

Open AccessArticle

Fuel Cell-Based Inductive Power Transfer System for Supercapacitor Constant Current Charging

by Nicola Campagna, Vincenzo Castiglia, Francesco Gennaro, Angelo Alberto Messina and Rosario Miceli

Energies 2024, 17(14), 3575; https://doi.org/10.3390/en17143575 - 20 Jul 2024

Viewed by 1002

Abstract

The majority of urban CO₂ emissions come from the transportation sector. To be able to reduce them, it is definitely necessary to replace Internal Combustion Engine (ICE) vehicles with electric ones. In this article, a public transport system is proposed, consisting of [...] Read more.

The majority of urban CO₂ emissions come from the transportation sector. To be able to reduce them, it is definitely necessary to replace Internal Combustion Engine (ICE) vehicles with electric ones. In this article, a public transport system is proposed, consisting of a supercapacitor (SC)-powered electric vehicle (EV) charged through a fuel cell-powered (FC) Inductive Power Transfer (IPT) system. The bus runs the usual route and it is charged each time it reaches the terminal, where the charging system is placed. The main advantages of the proposed system are related to the long-term cost of the EV, compared to a classic battery-powered system, to the aspects of ease of use and safety for charging operations and to the possibility of realizing a net-zero-energy transport system thanks to the use of green hydrogen. In addition, the proposed charging methodology allows for better energy utilization avoiding major changes to the main power grid. In this article, the system is presented considering a real case study; it is simulated at system and hardware level, and then validated through the realization of a scaled-down prototype. Full article

(This article belongs to the Section A: Sustainable Energy)

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19 pages, 5196 KiB

Open AccessArticle

Impact of Air-Cathodes on Operational Stability of Single-Chamber Microbial Fuel Cell Biosensors for Wastewater Monitoring

by Anna Salvian, Daniel Farkas, Marina Ramírez-Moreno, Claudio Avignone Rossa, John R. Varcoe and Siddharth Gadkari

Energies 2024, 17(14), 3574; https://doi.org/10.3390/en17143574 - 20 Jul 2024

Viewed by 1265

Abstract

The increasing global water pollution leads to the need for urgent development of rapid and accurate water quality monitoring methods. Microbial fuel cells (MFCs) have emerged as real-time biosensors for biochemical oxygen demand (BOD), but they grapple with several challenges, including issues related [...] Read more.

The increasing global water pollution leads to the need for urgent development of rapid and accurate water quality monitoring methods. Microbial fuel cells (MFCs) have emerged as real-time biosensors for biochemical oxygen demand (BOD), but they grapple with several challenges, including issues related to reproducibility, operational stability, and cost-effectiveness. These challenges are substantially shaped by the selection of an appropriate air-breathing cathode. Previous studies indicated a critical influence of the cathode on both the enduring electrochemical performance of MFCs and the taxonomic diversity at the electroactive anode. However, the effect of different gas diffusion electrodes (GDE) on 3D-printed single-chamber MFCs for BOD biosensing application and its effect on the bioelectroactive anode was not investigated before. Our study focuses on comparing GDE cathode materials to enhance MFC performance for precise and rapid BOD analysis in wastewater. We examined for over 120 days two Pt-coated air-breathing cathodes with distinct carbonaceous gas diffusion layers (GDLs) and catalyst layers (CLs): cost-effective carbon paper (CP) with hand-coated CL and more expensive woven carbon cloth (CC) with CL pre-applied by the supplier. The results show significant differences in electrochemical characteristics and anodic biofilm composition between MFCs with CP and CC GDE cathodes. CP-MFCs exhibited lower sensitivity (16.6 C L mg⁻¹ m⁻²) and a narrower dynamic range (25 to 600 mg L⁻¹), attributed to biofouling-related degradation of the GDE. In contrast, CC-MFCs demonstrated superior performance with higher sensitivity (37.6 C L mg⁻¹ m⁻²) and a broader dynamic range (25 to 800 mg L⁻¹). In conclusion, our study underscores the pivotal role of cathode selection in 3D-printed MFC biosensors, influencing anodic biofilm enrichment time and overall BOD assessment performance. We recommend the use of cost-effective CP GDL with hand-coated CL for short-term MFC biosensor applications, while advocating for CC GDL supplied with CL as the preferred choice for long-term sensing implementations with enduring reliability. Full article

(This article belongs to the Section D2: Electrochem: Batteries, Fuel Cells, Capacitors)

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Energies, Volume 17, Issue 14 (July-2 2024) – 248 articles

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