Energies

14 pages, 11563 KiB

Open AccessArticle

Analysis of Circuits Supplying Thomson Coil Actuator Operating in Vacuum Contact Units of DC and AC Ultra-Fast Circuit Breakers

by Michal Rodak and Piotr Borkowski

Energies 2024, 17(22), 5809; https://doi.org/10.3390/en17225809 - 20 Nov 2024

Viewed by 281

Abstract

The use of vacuum-hybrid DC circuit breaking methods allows the short-circuit current to be switched off in a shorter time, resulting in a reduction in the arc burning time. This requires the use of a drive, such as the Thomson Coil Actuator TCA, [...] Read more.

The use of vacuum-hybrid DC circuit breaking methods allows the short-circuit current to be switched off in a shorter time, resulting in a reduction in the arc burning time. This requires the use of a drive, such as the Thomson Coil Actuator TCA, capable of providing a short response time for opening the vacuum interrupter VI, regardless of its rated current. The IDD is powered by a pre-charged capacitor, which, together with the drive coil, forms an LC oscillating circuit that, when switched on by a thyristor, generates a current pulse of several kA with a frequency above 1 kHz. The paper investigates the effect of modifying the basic IDD power supply circuit by adding semiconductor diodes to shape the current pulse and improve its performance. The authors also focused on exploring the impact of the connection quality and their length and the associated loss in drive force while proving that a circuit with a reverse diode on the IDD coil is most beneficial and that the effect of the circuit on the front of the current pulse can significantly slow down the drive. Full article

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

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14 pages, 3794 KiB

Open AccessArticle

Development of a Battery Diagnostic Method Based on CAN Data: Examining the Accuracy of Data Received via a Communication Network

by Balázs Baráth, Gergő Sütheö and Letícia Pekk

Energies 2024, 17(22), 5808; https://doi.org/10.3390/en17225808 - 20 Nov 2024

Viewed by 232

Abstract

In order to reduce the emissions caused by internal combustion engine vehicles, the industry is introducing more and more electric or hybrid vehicles to the market nowadays. The battery cells and modules of these vehicles require a lot of care, as improper or [...] Read more.

In order to reduce the emissions caused by internal combustion engine vehicles, the industry is introducing more and more electric or hybrid vehicles to the market nowadays. The battery cells and modules of these vehicles require a lot of care, as improper or improperly maintained battery units can cause serious problems inside vehicles and can be extremely dangerous. The safest solution is to keep this unit of a vehicle under constant supervision so that it can be repaired immediately in case of an issue. Since all necessary data can be extracted from a vehicle’s communication network(s) through standard communication protocols, it is advisable to use them for continuous monitoring and diagnostics of units, while also considering cost-effectiveness and simplicity. The data received from here can also be used for measurement of electric powertrains and other parameters. However, since these data go through many conversions and computers (ECUs) before reaching us, their accuracy is questionable. In this study, we present our own custom battery diagnostic tool based on data extracted from a communication network. With the help of commercially available diagnostic tools, we also compare several measurements of the extent of the error limits of the data arriving at the communication network, how far they differ from the real values, and with the help of these, we analyze the accuracy of the device we have made. We present the commonly used Controller Area Network (CAN) communication protocol for passenger vehicles and briefly describe the construction of the high-voltage battery unit of the test vehicle. Full article

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

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9 pages, 831 KiB

Open AccessArticle

Modeling of Collusion Behavior in the Electrical Market Based on Deep Deterministic Policy Gradient

by Yifeng Liu, Jingpin Chen, Meng Chen, Zhongshi He, Ye Guo and Chenghan Li

Energies 2024, 17(22), 5807; https://doi.org/10.3390/en17225807 - 20 Nov 2024

Viewed by 227

Abstract

The evolution of the electricity market has brought the issues of market equilibrium and collusion to the forefront of attention. This paper introduces the Deep Deterministic Policy Gradient (DDPG) algorithm on the IEEE three-bus electrical market model. Specifically, it simulates the behavior of [...] Read more.

The evolution of the electricity market has brought the issues of market equilibrium and collusion to the forefront of attention. This paper introduces the Deep Deterministic Policy Gradient (DDPG) algorithm on the IEEE three-bus electrical market model. Specifically, it simulates the behavior of market participants through reinforcement learning (DDPG), and Nash equilibrium and the collusive equilibrium of the power market are simulated by setting different reward functions. The results show that, compared with the Nash equilibrium, collusion equilibrium can increase the price of nodal marginal electricity and reduce total social welfare. Full article

(This article belongs to the Special Issue Electricity Market Modeling Trends in Power Systems)

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24 pages, 7050 KiB

Open AccessArticle

Quantile Connectedness of Uncertainty Indices, Carbon Emissions, Energy, and Green Assets: Insights from Extreme Market Conditions

by Tiantian Liu, Yulian Zhang, Wenting Zhang and Shigeyuki Hamori

Energies 2024, 17(22), 5806; https://doi.org/10.3390/en17225806 - 20 Nov 2024

Viewed by 267

Abstract

In this study, we investigate the volatility spillover effects across uncertainty indices (Infectious Disease Equity Market Volatility Tracker (IDEMV) and Geopolitical Risk Index (GPR)), carbon emissions, crude oil, natural gas, and green assets (green bonds and green stock) under extreme market conditions based [...] Read more.

In this study, we investigate the volatility spillover effects across uncertainty indices (Infectious Disease Equity Market Volatility Tracker (IDEMV) and Geopolitical Risk Index (GPR)), carbon emissions, crude oil, natural gas, and green assets (green bonds and green stock) under extreme market conditions based on the quantile connectedness approach. The empirical findings reveal that the total and directional connectedness across green assets and other variables in extreme market conditions is much higher than that in the median, and there is obvious asymmetry in the connectedness measured at the extreme lower and upper quantiles. Our findings suggest that the uncertainty caused by COVID-19 has a more significant impact on green assets than the uncertainty related to the Russia–Ukraine war under normal and extreme market conditions. Furthermore, we discover that the uncertainty indices are more important in predicting green asset volatility under extreme market conditions than they are in the normal market. Finally, we observe that the dynamic total spillover effects in the extreme quantiles are significantly higher than those in the median. Full article

(This article belongs to the Special Issue International Finance and Energy Markets: Energy Supplying, Prices, Investments and Trends)

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25 pages, 2367 KiB

Open AccessArticle

The Impact of Policy Thematic Differences on Industrial Development: An Empirical Study Based on China’s Electric Vehicle Industry Policies at the Central and Local Levels

by Zizheng Liu and Tao Xie

Energies 2024, 17(22), 5805; https://doi.org/10.3390/en17225805 - 20 Nov 2024

Viewed by 256

Abstract

Since the 21st century, the electric vehicle (EV) industry has become a key driver of global transformation, with increasing emphasis on the study and evaluation of industrial policies across nations. However, traditional frameworks struggle to capture the dynamic interactions between policies at different [...] Read more.

Since the 21st century, the electric vehicle (EV) industry has become a key driver of global transformation, with increasing emphasis on the study and evaluation of industrial policies across nations. However, traditional frameworks struggle to capture the dynamic interactions between policies at different government levels or effectively analyze large volumes of policy texts. This study adopted a central–local policy interaction perspective, employing the BERT deep semantic learning model and a threshold regression model to investigate the impact of policy differences on industrial development. The findings reveal an inverted U-shaped relationship between central–local policy thematic similarity and EV market penetration, with the optimal similarity shifting as policy volume increases. This suggests the necessity of dynamically allocating central and local policies to balance national consistency with regional flexibility and promote synergy among regions. Recommendations include optimizing multi-level coordination, maintaining a balance between uniformity and specialization, strengthening policy error tolerance mechanisms, and fostering innovation. By integrating text analysis with econometric modeling, this study offers a novel framework aligned with China’s political system, providing insights into central–local policy interactions and serving as a reference for other countries seeking to refine their industrial strategies. Full article

(This article belongs to the Section E: Electric Vehicles)

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16 pages, 2004 KiB

Open AccessArticle

Constraint Optimal Model-Based Disturbance Predictive and Rejection Control Method of a Parabolic Trough Solar Field

by Shangshang Wei, Xianhua Gao and Yiguo Li

Energies 2024, 17(22), 5804; https://doi.org/10.3390/en17225804 - 20 Nov 2024

Viewed by 263

Abstract

The control of the field outlet temperature of a parabolic trough solar field (PTSF) is crucial for the safe and efficient operation of the solar power system but with the difficulties arising from the multiple disturbances and constraints imposed on the variables. To [...] Read more.

The control of the field outlet temperature of a parabolic trough solar field (PTSF) is crucial for the safe and efficient operation of the solar power system but with the difficulties arising from the multiple disturbances and constraints imposed on the variables. To this end, this paper proposes a constraint optimal model-based disturbance predictive and rejection control method with a disturbance prediction part. In this method, the steady-state target sequence is dynamically corrected in the presence of constraints, the lumped disturbance, and its future dynamics predicted by the least-squares support vector machine. In addition, a maximum controlled allowable set is constructed in real time to transform an infinite number of constraint inequalities into finite ones with the integration of the corrected steady-state target sequence. On this basis, an equivalent quadratic programming constrained optimization problem is constructed and solved by the dual-mode control law. The simulation results demonstrate the setpoint tracking and disturbance rejection performance of our design under the premise of constraint satisfaction. Full article

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

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16 pages, 6066 KiB

Open AccessArticle

Simulation of Ozone Distribution in an Innovative Drying and Sanitising Cabinet Chamber

by Damian Cebulski and Piotr Cyklis

Energies 2024, 17(22), 5803; https://doi.org/10.3390/en17225803 - 20 Nov 2024

Viewed by 261

Abstract

Common designs of workwear drying units require not only energy efficiency but also effective disinfection. One possibility of sanitising clothes during drying is to use the ozone generated inside the drying chamber. This process requires precise management of airflow and a uniform distribution [...] Read more.

Common designs of workwear drying units require not only energy efficiency but also effective disinfection. One possibility of sanitising clothes during drying is to use the ozone generated inside the drying chamber. This process requires precise management of airflow and a uniform distribution of ozone in the chamber. Therefore, optimising the shape of the drying chamber must include not only the correct flow of drying air but also the correct distribution of ozone. This paper addresses the difficult problem of modelling the flow of sanitising ozone in an innovative drying chamber. The innovative shape of the chamber is shown in this article. Due to the low percentage of ozone in the air (up to 10 ppm), CFD simulation models of the usual mixture type are too inaccurate; therefore, special models have to be used. Therefore, this paper presents an experimentally verified methodology to simulate ozone flow in an innovative drying and sanitising cabinet using two methods: Discrete Phase Model (DPM) and Species Transport (ST). The DPM method uses a Euler–Lagrange approach to qualitatively assess the spread of ozone particles, treated with a description of the movement of the particles and not as a continuous gaseous substance. On the other hand, this already allows the verification of ozone concentrations, with an appropriate conversion of the measured quantities. The ANSYS/FLUENT 2023R1 program was used for the simulations after careful selection of the mesh, closing models, boundary conditions, etc. Simulations made it possible to analyse the distribution of ozone in the workspace and assess the effectiveness of the sanitisation process. The results of the simulations were verified on the basis of empirical tests, which showed the correctness of the model and the correct distribution of the sanitising ozone in the entire volume of the drying chamber in the innovative drying–sanitising chamber. The complete simulation of the air and ozone distribution using the presented models allowed for the optimisation of the opening and shapes, which contributed to improving the energy efficiency of the unit and increasing the efficiency of the sanitisation processes, making the described methodology very effective for optimising the chambers of various types of dryers. Full article

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

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27 pages, 3941 KiB

Open AccessArticle

The Pushback Against Canada’s Carbon Pricing System: A Case Study of Two Canadian Provinces, Saskatchewan and Nova Scotia

by Larry Hughes and Sarah Landry

Energies 2024, 17(22), 5802; https://doi.org/10.3390/en17225802 - 20 Nov 2024

Viewed by 292

Abstract

As part of its plan to transition to an energy secure and environmentally sustainable future, Canada has had a national carbon pricing system since 2019. When first introduced, the $20 (‘$’ refer to Canadian dollars (CAD) in this paper) per tonne price was [...] Read more.

As part of its plan to transition to an energy secure and environmentally sustainable future, Canada has had a national carbon pricing system since 2019. When first introduced, the $20 (‘$’ refer to Canadian dollars (CAD) in this paper) per tonne price was widely accepted by most Canadians and seen as a way of helping Canada meet its emissions reduction pledges made at the 2015 United Nations Climate Change Conference (COP 21) in Paris. The Canadian system is novel in that it both charges consumers for their emissions and reimburses them for their expected emissions; this is intended to raise awareness of their emissions and encourage those who can afford to opt for lower-emissions energy services to do so. By 2023, the combination of the carbon price reaching $65 per tonne and the post-pandemic economic slowdown was seized on by numerous politicians as a way of pushing back against the carbon pricing system, with most demanding the entire system be scrapped. The debate intensified in late 2023 and into 2024, when the federal government removed the carbon tax on home heating oil because the reimbursement was insufficient to cover the cost of the tax. In this paper, we consider the recent actions of two Canadian provinces, Saskatchewan and Nova Scotia, embroiled in the federal carbon pricing system debate due to the removal of the carbon tax on fuel oil for space heating. The objective of this paper is to identify how some of the reasons, including global post-pandemic inflation and other challenges facing Canadians, such as those cited in third-party polls, have contributed to a rise in the system’s unpopularity. Our method estimates and compares the impacts of the carbon tax on the household energy services for space and water heating, lighting and appliances, and private (i.e., household) transportation for different types of housing (apartment, single-attached, and single-detached) and number of occupants (two, three, and four) in Saskatchewan and Nova Scotia. The results of this work show that while Saskatchewan households have higher energy intensities than those in Nova Scotia, the impact of the carbon tax on Nova Scotians using fuel oil for heating was greater than in Saskatchewan. In Saskatchewan and Nova Scotia, natural gas and electricity, respectively, are used for heating. This paper concludes with a summary of our findings and potential options for improving perceptions of the system. Full article

(This article belongs to the Special Issue Energy Transition and Environmental Sustainability: 3rd Edition)

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14 pages, 2647 KiB

Open AccessArticle

Influence of Control Strategy on Heat Recovery Efficiency in a Single-Duct Periodic Ventilation Device

by Piotr Koper

Energies 2024, 17(22), 5801; https://doi.org/10.3390/en17225801 - 20 Nov 2024

Viewed by 200

Abstract

The subject of the research was a single-duct, decentralised periodic ventilation unit, using accumulative heat exchanger for heat recovery (also called single-core fixed-bed regenerator). It can achieve high efficiency of heat recovery but is vulnerable to pressure differences between the interior of the [...] Read more.

The subject of the research was a single-duct, decentralised periodic ventilation unit, using accumulative heat exchanger for heat recovery (also called single-core fixed-bed regenerator). It can achieve high efficiency of heat recovery but is vulnerable to pressure differences between the interior of the building and the outside. To counter this, two control strategies were proposed: adjustment of the fan speed based on an air flow sensor and adjustment of the working cycle length based on temperature sensors. The strategies were tested experimentally in actual working conditions. Due to the use of cheap and simple sensors, it was possible to retain the low price of the device. Both control strategies proved to be successful in equalising the amount of supplied and removed air in a single cycle. Moreover, the heat recovery efficiency increased by more than 10% compared to the default working mode. Full article

(This article belongs to the Special Issue Thermal Comfort, Environment Quality and Energy Consumption)

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17 pages, 6180 KiB

Open AccessArticle

Hydrogen, Methane, Brine Flow Behavior, and Saturation in Sandstone Cores During H₂ and CH₄ Injection and Displacement

by Lirong Zhong, Seunghwan Baek, Mond Guo, Christopher Bagwell and Nicolas Huerta

Energies 2024, 17(22), 5800; https://doi.org/10.3390/en17225800 - 20 Nov 2024

Viewed by 253

Abstract

Large-scale underground hydrogen storage (UHS) is a critical component in the emerging hydrogen economy. Knowledge of multiphase flow behavior involving hydrogen in storage reservoir formations is crucial to characterizing hydrogen transport properties and essential for the deliverability and storage operations of UHS. There [...] Read more.

Large-scale underground hydrogen storage (UHS) is a critical component in the emerging hydrogen economy. Knowledge of multiphase flow behavior involving hydrogen in storage reservoir formations is crucial to characterizing hydrogen transport properties and essential for the deliverability and storage operations of UHS. There are still many gaps in fully understanding hydrogen–methane–brine multiphase phase flow that require further investigation. In this work, H₂ and CH₄ were injected through brine-saturated sandstone cores using a tri-axial core holder system fitted with flow rate meters and pressure transducers, while the effluent gas concentrations were analyzed using an online micro gas chromatograph. Brine displacement, permeability, and gas breakthrough curves were measured. We studied the flow behavior of hydrogen and methane in sandstone cores through testing brine displacement by gas injection and comparing the hydrogen displacement of methane with the methane displacement of hydrogen. We also tested the differences between horizontal and vertical flow in brine displacement. The results showed that brine displacement was more efficient in a core with higher permeability and porosity, resulting in a higher initial gas saturation. A higher gas injection rate brought about faster gas breakthrough measured by pore volume and sharper concentration curves. Hydrogen did not exhibit abnormal flow in the sandstone when the flow was horizontal and downward vertical. Gas overriding was observed in brine displacements when the flow was horizontal, with hydrogen showing this behavior more profoundly compared to methane. Downward vertical gas injection induced higher efficiency brine displacement compared to horizontal displacement and resulted in a higher initial gas saturation in the sandstone cores. These findings address critical knowledge gaps regarding gas flow patterns and displacement behaviors during hydrogen injection and recovery phases in UHS facilities using methane as the cushion gas. The insights from this research offer valuable guidance for optimizing UHS systems, ensuring operational efficiency, and advancing sustainable energy solutions in alignment with decarbonization goals. Full article

(This article belongs to the Section A5: Hydrogen Energy)

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18 pages, 3136 KiB

Open AccessArticle

Research on Fault Diagnosis of Ship Diesel Generator System Based on IVY-RF

by Hui Ouyang, Weibo Li, Feng Gao, Kangzheng Huang and Peng Xiao

Energies 2024, 17(22), 5799; https://doi.org/10.3390/en17225799 - 20 Nov 2024

Viewed by 213

Abstract

Ship diesel generator systems are critical to ship navigation. However, due to the harsh marine environment, the systems are prone to failures, and traditional fault diagnosis methods are difficult to meet requirements regarding accuracy, robustness, and reliability. For this reason, this paper proposes [...] Read more.

Ship diesel generator systems are critical to ship navigation. However, due to the harsh marine environment, the systems are prone to failures, and traditional fault diagnosis methods are difficult to meet requirements regarding accuracy, robustness, and reliability. For this reason, this paper proposes a fault diagnosis method for a ship diesel generator system based on the IVY algorithm-optimized random forest (IVY-RF). Firstly, a model of a ship diesel generator system was constructed using MATLAB/Simulink, and the operation data under fault and normal working conditions were collected. Then, the data were preprocessed and time-domain features were extracted. Finally, the IVY-optimized random forest model was used to identify, diagnose, and classify faults. The simulation results show that the IVY-RF method could identify faulty and normal states with 100% accuracy and distinguish 12 types with 100% accuracy. Compared to seven different algorithms, the IVY-RF improved accuracy by at least 0.17% and up to 67.45% on the original dataset and by at least 1.19% and up to 49.40% in a dataset with 5% noise added. The IVY-RF-based fault diagnosis method shows excellent accuracy and robustness in complex marine environments, providing a reliable fault identification solution for ship power systems. Full article

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

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27 pages, 9960 KiB

Open AccessArticle

Energy-Oriented Modeling of Hot Stamping Production Line: Analysis and Perspectives for Reduction

by Qiong Liu, Quan Zuo, Lei Li, Chen Yang, Jianwen Yan and Yuhang Xu

Energies 2024, 17(22), 5798; https://doi.org/10.3390/en17225798 - 20 Nov 2024

Viewed by 214

Abstract

This research aims to develop a comprehensive mathematical model to analyze the energy usage of essential equipment in the hot stamping production line (HSPL) and identify opportunities for improving energy efficiency. This involves refining existing models and parameters related to energy consumption in [...] Read more.

This research aims to develop a comprehensive mathematical model to analyze the energy usage of essential equipment in the hot stamping production line (HSPL) and identify opportunities for improving energy efficiency. This involves refining existing models and parameters related to energy consumption in hot stamping to ensure precise energy usage monitoring throughout the HSPL. The main focus is on accurately calculating and validating the energy consumption efficiency of equipment within a product’s production cycle on the roller hearth furnace’s HSPL. The model has proven to be highly accurate in predicting energy consumption for various equipment. The average energy consumption of the HSPL in the case study is calculated as 0.597 kwh/kg, and the actual measurement is 0.625 kwh/kg. However, it revealed significant deviation in the cooling system, primarily due to the incorrect water pump head parameters utilization. As per the model’s calculations, most energy consumption is attributed to the furnace (77.51%), followed by the press (10.92%), chillers (6.86%), cooling systems (2.76%), and robots (1.95%). Actual measurements and model calculations highlight mismatches between equipment power ratings and actual demand, resulting in average operating power significantly lower than the rated power. In line with efforts to promote low-carbon manufacturing, practical approaches are being explored to conserve energy and enhance overall process efficiency by refining process parameters, reducing quenching duration, improving SPM on the production line, and adjusting load matching. Full article

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

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37 pages, 699 KiB

Open AccessReview

The State of the Art Electricity Load and Price Forecasting for the Modern Wholesale Electricity Market

by Vasileios Laitsos, Georgios Vontzos, Paschalis Paraschoudis, Eleftherios Tsampasis, Dimitrios Bargiotas and Lefteri H. Tsoukalas

Energies 2024, 17(22), 5797; https://doi.org/10.3390/en17225797 - 20 Nov 2024

Viewed by 268

Abstract

In a modern and dynamic electricity market, ensuring reliable, sustainable and efficient electricity distribution is a pillar of primary importance for grid operation. The high penetration of renewable energy sources and the formation of competitive prices for utilities play a critical role in [...] Read more.

In a modern and dynamic electricity market, ensuring reliable, sustainable and efficient electricity distribution is a pillar of primary importance for grid operation. The high penetration of renewable energy sources and the formation of competitive prices for utilities play a critical role in the wider economic development. Electricity load and price forecasting have been a key focus of researchers in the last decade due to the substantial economic implications for both producers, aggregators and end consumers. Many forecasting techniques and methods have emerged during this period. This paper conducts a extensive and analytical review of the prevailing load and electricity price forecasting methods in the context of the modern wholesale electricity market. The study is separated into seven main sections. The first section provides the key challenges and the main contributions of this study. The second section delves into the workings of the electricity market, providing a detailed analysis of the three markets that have evolved, their functions and the key factors influencing overall market dynamics. In the third section, the main methodologies of electricity load and price forecasting approaches are analyzed in detail. The fourth section offers a comprehensive review of the existing literature focusing on load forecasting, highlighting various methodologies, models and their applications in this field. This section emphasizes the advances that have been made in all categories of forecasting models and their practical application in different market scenarios. The fifth section focuses on electricity price forecasting studies, summarizing important research papers investigating various modeling approaches. The sixth section constitutes a fundamental discussion and comparison between the load- and price-focused studies that are analyzed. Finally, by examining both traditional and cutting-edge forecasting methods, this review identifies key trends, challenges and future directions in the field. Overall, this paper aims to provide an in-depth analysis leading to the understanding of the state-of-the-art models in load and price forecasting and to be an important resource for researchers and professionals in the energy industry. Based on the research conducted, there is an increasing trend in the use of artificial intelligence models in recent years, due to the flexibility and adaptability they offer for big datasets, compared to traditional models. The combination of models, such as ensemble methods, gives us very promising results. Full article

(This article belongs to the Special Issue Application of Machine Learning Tools for Energy System)

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24 pages, 2012 KiB

Open AccessReview

Key Role and Optimization Dispatch Research of Technical Virtual Power Plants in the New Energy Era

by Weigang Jin, Peihua Wang and Jiaxin Yuan

Energies 2024, 17(22), 5796; https://doi.org/10.3390/en17225796 - 20 Nov 2024

Viewed by 228

Abstract

This comprehensive review examines the key role and optimization dispatch of Technical Virtual Power Plants (TVPPs) in the new energy era. This study provides an overview of Virtual Power Plants (VPPs), including their definition, development history, and classification into Technical and Commercial VPPs. [...] Read more.

This comprehensive review examines the key role and optimization dispatch of Technical Virtual Power Plants (TVPPs) in the new energy era. This study provides an overview of Virtual Power Plants (VPPs), including their definition, development history, and classification into Technical and Commercial VPPs. It then systematically analyzes optimization methods for TVPPs from five aspects: deterministic optimization, stochastic optimization, robust optimization, and bidding-integrated optimization. For each method, this review presents its mathematical models and solution algorithms. This review highlights the significance of TVPPs in enhancing power system flexibility, improving renewable energy integration, and providing ancillary services. Through methodological classification and comparative analysis, this review aims to provide valuable insights for the design, operation, and management of TVPPs in future power systems. Full article

(This article belongs to the Special Issue Optimizing Power Networks for Enhanced Resilience and Efficiency in Integrated Energy Systems 2024)

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22 pages, 4687 KiB

Open AccessArticle

Study on the Thermodynamic–Kinetic Coupling Characteristics of Free-Piston Stirling Air Conditioning

by Yajuan Wang, Kang Zhao and Jun’an Zhang

Energies 2024, 17(22), 5795; https://doi.org/10.3390/en17225795 - 20 Nov 2024

Viewed by 218

Abstract

Unlike traditional free-piston Stirling heat engines or heat pumps, the free piston Stirling air conditioning (FPSAC) is specifically designed for electric vehicle air conditioning under ambient room temperature conditions. In the FPSAC system, the displacer and the power piston are coupled through gas [...] Read more.

Unlike traditional free-piston Stirling heat engines or heat pumps, the free piston Stirling air conditioning (FPSAC) is specifically designed for electric vehicle air conditioning under ambient room temperature conditions. In the FPSAC system, the displacer and the power piston are coupled through gas forces, emphasizing the importance of investing the thermodynamic–kinetic coupling characteristics. This study analyzed the damping terms within the dynamic equations of the FPSAC model and solved these equations to reveal system dynamics. By linearizing the working chamber’s pressure, the study examined the machine’s dynamic behavior, presenting solutions for amplitude and phase angle. Derived expressions for the displacement and acceleration of both the power piston and the displacer further support this analysis. The research evaluates the influence of driving force on amplitude and phase angle, alongside the impact of damping coefficients, thereby isolating thermodynamic–dynamic coupling characteristics. Control equations integrating dynamics and thermodynamics were developed, and a comprehensive system model was constructed using MATLAB(2020a)/Simulink to simulate acceleration and displacement variation in the pistons. Key findings include: (1) a positive correlation between driving force and displacer, where increased force leads to higher amplitudes; (2) a frequency of 65 Hz reveals a singularity occurs in displacer amplitude, resulting in system instability; (3) phase angle between pistons reduces to below 10° when the driving force exceeds 150 N; and (4) the power piston’s amplitude decreases with an increase in damping C_1, while changes in damping C₂ primarily affect the displacer’s singularity position around 65 Hz, with higher C₂ values shifting the singularity to lower frequencies. Full article

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

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17 pages, 2460 KiB

Open AccessArticle

Associated Gas Recovery Integrated with Solar Power for Produced Water Treatment: Techno-Economic and Environmental Impact Analyses

by Daniel H. Chen, Fuad Samier Aziz and Gevorg Sargsyan

Energies 2024, 17(22), 5794; https://doi.org/10.3390/en17225794 - 20 Nov 2024

Viewed by 255

Abstract

Excess associated gas from unconventional wells is typically flared while excess produced water is injected underground. In this work, flare gas recovery is integrated with produced water desalination and a solar pre-heater. The solar module with a beam splitter preheats the produced water. [...] Read more.

Excess associated gas from unconventional wells is typically flared while excess produced water is injected underground. In this work, flare gas recovery is integrated with produced water desalination and a solar pre-heater. The solar module with a beam splitter preheats the produced water. Aspen Plus process modeling, economic analysis, and greenhouse gas analysis were performed. The solar flare gas recovery desalination (Solar-FGRD) process can conserve water resources and reduce the brine injection by 77%. The accompanying solar farm results in excess solar electricity for exporting to the grid. The process burner combustion efficiency (CE) is 99.8%, with a destruction and removal efficiency (DRE) of 99.99% for methane as opposed to a flare CE of 80–98% (and a methane DRE of 91–98%). The greenhouse gas (GHG) emissions for CO₂ and methane, in terms of CO₂ equivalent (CO₂e), can be reduced by 45% for US North Dakota and Texas flaring and 13% for North Sea flaring by employing the Solar-FGRD process. Comprehensive financial analysis demonstrates the financial–economic feasibility of the investment project with or without tax credits. Best-case and worst-case scenarios provide a realistic range that investors can consider before making investment decisions. Full article

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

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15 pages, 3566 KiB

Open AccessReview

A Detailed Review of Partial Discharge Detection Methods for SiC Power Modules Under Square-Wave Voltage Excitation

by Ghulam Akbar, Alessio Di Fatta, Giuseppe Rizzo, Guido Ala, Pietro Romano and Antonino Imburgia

Energies 2024, 17(22), 5793; https://doi.org/10.3390/en17225793 - 20 Nov 2024

Viewed by 272

Abstract

Silicon carbide (SiC) power modules are increasingly being used in high-voltage and high-frequency applications due to their superior electrical and thermal qualities. However, the issue of the partial discharge (PD) phenomenon raises serious reliability difficulties resulting in insulation failure, performance degradation, and potential [...] Read more.

Silicon carbide (SiC) power modules are increasingly being used in high-voltage and high-frequency applications due to their superior electrical and thermal qualities. However, the issue of the partial discharge (PD) phenomenon raises serious reliability difficulties resulting in insulation failure, performance degradation, and potential device collapse. This paper provides a thorough assessment of the current PD detection strategies in SiC power modules. The issues provided by SiC devices’ distinct operational features, such as high switching frequencies and higher voltage stresses, which hinder PD detection and mitigation, are widely investigated. This review compares the effectiveness, benefits, and limitations of various detection methods, emphasizing the need for better strategies to ensure long-term reliability and performance. This study gives an in-depth overview of the numerous forms of PD phenomena that occur in power modules, including internal and surface discharges, as well as how they appear under various detection systems. It examines the performance of several methods for power module technologies such as SiC. To address these PD issues, this article proposes ways to improve reliability and detection accuracy. Full article

(This article belongs to the Section F6: High Voltage)

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19 pages, 3893 KiB

Open AccessArticle

Assessing Suitable Areas for PV Power Installation in Remote Agricultural Regions

by Abdelfetah Belaid, Mawloud Guermoui, Reski Khelifi, Toufik Arrif, Tawfiq Chekifi, Abdelaziz Rabehi, El-Sayed M. El-Kenawy and Amel Ali Alhussan

Energies 2024, 17(22), 5792; https://doi.org/10.3390/en17225792 - 20 Nov 2024

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Abstract

Remote agricultural regions in desert areas, such as Ghardaïa in southern Algeria, face significant challenges in energy supply due to their isolated locations and harsh climatic conditions. Harnessing solar energy through photovoltaic (PV) systems offers a sustainable solution to these energy needs. This [...] Read more.

Remote agricultural regions in desert areas, such as Ghardaïa in southern Algeria, face significant challenges in energy supply due to their isolated locations and harsh climatic conditions. Harnessing solar energy through photovoltaic (PV) systems offers a sustainable solution to these energy needs. This study aims to identify suitable areas for PV power installations in Ghardaïa, utilizing a geographic information system (GIS) combined with the fuzzy analytical hierarchy process (AHP). Various environmental, economic, and technical factors, such as solar radiation, land use, and proximity to infrastructure, are incorporated into the analysis to create a multi-criteria decision-making framework. The integration of fuzzy logic into AHP enables a more flexible evaluation of these factors. The results revealed the presence of ideal locations for installing photovoltaic stations, with 346,673.30 hectares identified as highly suitable, 977,606.84 hectares as very suitable, and 937,385.97 hectares as suitable. These areas are characterized by high levels of solar radiation and suitable infrastructure availability, contributing to reduced implementation costs and facilitating logistical operations. Additionally, the proximity of these locations to agricultural areas enhances the efficiency of electricity delivery to farmers. The study emphasizes the need for well-considered strategic planning to achieve sustainable development in remote rural areas. Full article

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

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20 pages, 6933 KiB

Open AccessArticle

Sky Temperature Forecasting in Djibouti: An Integrated Approach Using Measured Climate Data and Artificial Neural Networks

by Hamda Abdi, Abdou Idris and Anh Dung Tran Le

Energies 2024, 17(22), 5791; https://doi.org/10.3390/en17225791 - 20 Nov 2024

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Abstract

Buildings exchange heat with different environmental elements: the sun, the outside air, the sky, and outside surfaces (including the walls of environmental buildings and the ground). To correctly account for building energy performance, radiative cooling potential, and other technical considerations, it is essential [...] Read more.

Buildings exchange heat with different environmental elements: the sun, the outside air, the sky, and outside surfaces (including the walls of environmental buildings and the ground). To correctly account for building energy performance, radiative cooling potential, and other technical considerations, it is essential to evaluate sky temperature. It is an important parameter for the weather files used by energy building simulation software for calculating the longwave radiation heat exchange between exterior surfaces and the sky. In the literature, there are several models to estimate sky temperature. However, these models have not been completely satisfactory for the hot and humid climate in which the sky temperature remains overestimated. The purpose of this paper is to provide a comprehensive analysis of the sky temperature measurement conducted, for the first time, in Djibouti, with a pyrgeometer, a tool designed to measure longwave radiation as a component of thermal radiation, and an artificial neural network (ANN) model for improved sky temperature forecasting. A systematic comparison of known correlations for sky temperature estimation under various climatic conditions revealed their limited accuracy in the region, as indicated by low R² values and root mean square errors (RMSEs). To address these limitations, an ANN model was trained, validated, and tested on the collected data to capture complex patterns and relationships in the data. The ANN model demonstrated superior performance over existing empirical correlations, providing more accurate and reliable sky temperature predictions for Djibouti’s hot and humid climate. This study showcases the effectiveness of an integrated approach using pyrgeometer-based sky temperature measurements and advanced machine learning techniques ANNs for sky temperature forecasting in Djibouti to overcome the limitations of existing correlations and improve the accuracy of sky temperature predictions, particularly in hot and humid climates. Full article

(This article belongs to the Special Issue New Insights into Hybrid Renewable Energy Systems in Buildings)

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16 pages, 1791 KiB

Open AccessArticle

Exploring the Impact of State of Charge and Aging on the Entropy Coefficient of Silicon–Carbon Anodes

by Kevin Böhm, Simon Zintel, Philipp Ganninger, Jonas Jäger, Torsten Markus and David Henriques

Energies 2024, 17(22), 5790; https://doi.org/10.3390/en17225790 - 20 Nov 2024

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Abstract

Due to its improved capacity compared to graphite, silicon is a promising candidate to handle the demands of high-energy batteries. With the introduction of new materials, further aspects of the battery system must be reconsidered. One of those aspects is the heat generation [...] Read more.

Due to its improved capacity compared to graphite, silicon is a promising candidate to handle the demands of high-energy batteries. With the introduction of new materials, further aspects of the battery system must be reconsidered. One of those aspects is the heat generation during the charging and discharging of a cell, which delivers important information for the development of cooling systems, the battery management system and the overall performance of the cell. Since the reversible heat presents an important contribution to the overall heat generation during cycling, the entropy coefficient is the main value that needs to be determined. This study evaluates the entropy coefficient of custom-produced 2032 coin half-cells with lithium counter electrodes, containing 45 wt% nanosilicon and 45 wt% carbon black. The potentiometric method, utilizing VR and self-discharge curves, produced reliable results, yielding entropy coefficient values between 95% SoC and 10% SoC during delithiation. These values of the entropy coefficient are consistently negative. Furthermore, ICA measurements identified two phase transitions during delithiation, with these transitions shifting to lower SoC as SoH decreases, impacting the slope of the entropy coefficient. Full article

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

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15 pages, 3897 KiB

Open AccessArticle

Proposal of Low-Speed Sensorless Control of IPMSM Using a Two-Interval Six-Segment High-Frequency Injection Method with DC-Link Current Sensing

by Daniel Konvicny, Pavol Makys and Alex Franko

Energies 2024, 17(22), 5789; https://doi.org/10.3390/en17225789 - 20 Nov 2024

Viewed by 167

Abstract

This paper proposes a modification to existing saliency-based, sensorless control strategy for interior permanent magnet synchronous motors. The proposed approach leverages a two-interval, six-segment high-frequency voltage signal injection technique. It aims to improve rotor position and speed estimation accuracy when utilizing a single [...] Read more.

This paper proposes a modification to existing saliency-based, sensorless control strategy for interior permanent magnet synchronous motors. The proposed approach leverages a two-interval, six-segment high-frequency voltage signal injection technique. It aims to improve rotor position and speed estimation accuracy when utilizing a single current sensor positioned in the inverter’s DC-bus circuit. The key innovation lies in modifying both the high-frequency signal injection and demodulation processes to address challenges in accurate phase current reconstruction and rotor position estimation, at low and zero speeds. A significant modification to the traditional high-frequency voltage signal injection method is introduced, which involves splitting the signal injection and the field-oriented control algorithm into two distinct sampling and switching periods. This approach ensures that no portion of the injected voltage space vector falls into the immeasurable region of space vector modulation, which could otherwise compromise current measurements. The dual-period structure, termed the two-interval six-segment high-frequency injection, allows for more precise current measurement during the signal injection period while maintaining optimal motor control during the field-oriented control period. Furthermore, this paper explores a different demodulation technique that improves the estimation of rotor position and speed. By employing a synchronous filter in combination with a phase-locked loop, the proposed method enhances the robustness of the system against noise and inaccuracies typically encountered in phase current reconstruction. The effectiveness of the proposed modifications is demonstrated through comprehensive simulation results. These results confirm that the enhanced method offers more reliable rotor position and speed estimates compared to the existing sensorless technique, making it particularly suitable for applications requiring high precision in motor control. Full article

(This article belongs to the Special Issue Application of Advanced Control Theories to Power Electronics and Power Systems)

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19 pages, 2792 KiB

Open AccessArticle

Conceptual View of the Implementation of the Nuclear Energy Program in the Republic of Kazakhstan

by Erlan Batyrbekov, Vladimir Vityuk, Denis Zarva and Mazhit Sharipov

Energies 2024, 17(22), 5788; https://doi.org/10.3390/en17225788 - 20 Nov 2024

Viewed by 303

Abstract

This paper presents an analysis of the existing prerequisites and opportunities for the start-up of the Republic of Kazakhstan’s own full-fledged Nuclear Energy Program, a conceptual vision of the development of the Kazakhstani nuclear industry. Recommendations have been formulated for the timely and [...] Read more.

This paper presents an analysis of the existing prerequisites and opportunities for the start-up of the Republic of Kazakhstan’s own full-fledged Nuclear Energy Program, a conceptual vision of the development of the Kazakhstani nuclear industry. Recommendations have been formulated for the timely and successful implementation of the program for the introduction of nuclear power plants into the country’s energy generation structure, the development of the necessary related nuclear infrastructure facilities, national legislation, and other issues directly related to nuclear power development. Full article

(This article belongs to the Section B4: Nuclear Energy)

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26 pages, 652 KiB

Open AccessArticle

Improving Electrical Fault Detection Using Multiple Classifier Systems

by José Oliveira, Dioéliton Passos, Davi Carvalho, José F. V. Melo, Eraylson G. Silva and Paulo S. G. de Mattos Neto

Energies 2024, 17(22), 5787; https://doi.org/10.3390/en17225787 - 20 Nov 2024

Viewed by 243

Abstract

Machine Learning-based fault detection approaches in energy systems have gained prominence for their superior performance. These automated approaches can assist operators by highlighting anomalies and faults, providing a robust framework for improving Situation Awareness. However, existing approaches predominantly rely on monolithic models, which [...] Read more.

Machine Learning-based fault detection approaches in energy systems have gained prominence for their superior performance. These automated approaches can assist operators by highlighting anomalies and faults, providing a robust framework for improving Situation Awareness. However, existing approaches predominantly rely on monolithic models, which struggle with adapting to changing data, handling imbalanced datasets, and capturing patterns in noisy environments. To overcome these challenges, this study explores the potential of Multiple Classifier System (MCS) approaches. The results demonstrate that ensemble methods generally outperform single models, with dynamic approaches like META-DES showing remarkable resilience to noise. These findings highlight the importance of model diversity and ensemble strategies in improving fault classification accuracy under real-world, noisy conditions. This research emphasizes the potential of MCS techniques as a robust solution for enhancing the reliability of fault detection systems. Full article

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

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19 pages, 9395 KiB

Open AccessArticle

Numerical Simulation Study of Salt Cavern CO₂ Storage in Power-to-Gas System

by Weizheng Bai, Jun Lu, Jian Wang, Xinghui Fu, Yaping Fu, Yashuai Huang, Xiao Wang and Xilin Shi

Energies 2024, 17(22), 5786; https://doi.org/10.3390/en17225786 - 20 Nov 2024

Viewed by 269

Abstract

China’s renewable energy sector is experiencing rapid growth, yet its inherent intermittency is creating significant challenges for balancing power supply and demand. Power-to-gas (PtG) technology, which converts surplus electricity into combustible gas, offers a promising solution. Salt caverns, due to their favorable geological [...] Read more.

China’s renewable energy sector is experiencing rapid growth, yet its inherent intermittency is creating significant challenges for balancing power supply and demand. Power-to-gas (PtG) technology, which converts surplus electricity into combustible gas, offers a promising solution. Salt caverns, due to their favorable geological properties, are among the best choices for large-scale underground energy storage in PtG systems. CO₂ leakage along the interlayer and salt rock–interlayer interfaces is a key constraint on the CO₂ tightness of subsurface salt caverns. This paper focuses on the critical issue of tightness within salt cavern CO₂ storage, particularly in the Jintan region. A coupled hydro-mechanics mathematical model is developed to investigate CO₂ transportation and leakage in bedded salt caverns, with key variables such as permeability range, pore pressure evolution, and permeability changes being analyzed. The results reveal that permeability plays a decisive role in determining the CO₂ transportation rate and leakage extent within the salt rock layer. Notably, the CO₂ transportation rate and influence range in the mudstone interlayer are significantly larger than those in the salt rock over the same period. However, with prolonged storage time, the CO₂ transportation rate and pressure increase in both salt rock and mudstone interlayer exhibit a decreasing trend, eventually stabilizing as the CO₂ pressure front reaches the boundary of the simulation domain. Furthermore, elevated operating pressure markedly expands the permeability range and results in higher cumulative leakage. For a specific salt cavern, the CO₂ leakage range can reach up to 142 m, and the leakage volume can reach 522.5 tonnes with the increase in operating pressure during 35 years of operation. Therefore, the setting of operational pressure should fully consider the influence of permeability and mechanical strength of the salt rock and mudstone interlayer. These findings provide valuable insights into optimizing the sealing performance of salt cavern CO₂ storage systems under varying conditions. Full article

(This article belongs to the Collection Feature Papers in Carbon Capture, Utilization, and Storage)

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17 pages, 3833 KiB

Open AccessArticle

A Fast Simulation Method for Wind Turbine Blade Icing Integrating Physical Simulation and Statistical Analysis

by Wei Jiang, Renqiang Wen, Ming Qin, Guohan Zhao, Long Ma, Jun Guo and Jinbo Wu

Energies 2024, 17(22), 5785; https://doi.org/10.3390/en17225785 - 20 Nov 2024

Viewed by 422

Abstract

Simulating wind turbine blade icing quickly is important for wind farms to issue early warnings and effectively deal with the adverse effects of cold weather. However, current numerical simulation methods suffer from high computational costs and lack straightforward acceleration techniques for practical ice [...] Read more.

Simulating wind turbine blade icing quickly is important for wind farms to issue early warnings and effectively deal with the adverse effects of cold weather. However, current numerical simulation methods suffer from high computational costs and lack straightforward acceleration techniques for practical ice prediction. Here, we developed a fast and simple blade icing simulation method via an integrated physical simulation and statistical analysis method. This method consists of two steps: firstly, numerical simulation with CFD, and secondly, table look-up calculations. Over 10,000 sets of wind turbine blade icing simulations based on FENSAP-ICE and an NACA64-A17 wing were conducted to develop this method and analyze the influences of environmental factors on blade icing. The results show that ice thickness generally increases with an increase in wind speed, a decrease in temperature, and an increase in liquid water content (LWC), but there is a nonlinear relationship between them. For example, ice thickness has a linear relationship with the LWC within a certain range but hardly changes with a LWC beyond that range. The validation results show that the fast simulation method established in this paper has good consistency with the original numerical simulation method. It can greatly improve the computational efficiency of icing simulations while retaining the accuracy of numerical simulations. It takes less than 1 s to complete over 1000 sets of icing simulations, which offers potential for the fast prediction of wind turbine blade icing in the future. Full article

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

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20 pages, 7936 KiB

Open AccessArticle

Study on the Influence of Deep Coalbed Methane Horizontal Well Deployment Orientation on Production

by Ruyong Feng, Chen Li, Lichun Sun, Jian Wang, Jia Liu and Na Li

Energies 2024, 17(22), 5784; https://doi.org/10.3390/en17225784 - 20 Nov 2024

Viewed by 190

Abstract

The development of deep coalbed methane has become an important way to obtain natural gas in China. The development of deep CBM mainly depends on horizontal well technology. The different orientations of horizontal wells will have an important impact on the productivity of [...] Read more.

The development of deep coalbed methane has become an important way to obtain natural gas in China. The development of deep CBM mainly depends on horizontal well technology. The different orientations of horizontal wells will have an important impact on the productivity of coalbed methane wells. The angle grid geological model of coalbed methane reservoirs with different inclination angles is established, and the deployment orientation of horizontal wells is changed to study the optimal deployment orientation of deep-saturated coalbed methane reservoirs. When CBM horizontal wells in deep saturated CBM reservoirs are deployed upward along the dip, well-controlled reserves, peak daily gas production, and cumulative gas production increase as the dip decreases. When deploying down the dip, with the increase in dip angle, the well-controlled reserves increase, and the peak daily gas production and cumulative gas production first increase and then decrease. In the low-dip reservoir, the development effect of horizontal wells deployed in different directions is better than that in the up-dip direction. In the high-dip reservoir, the development effect of horizontal wells deployed along the strike is better than that in the up-dip and down-dip directions. The development effect of horizontal wells is controlled by both well-controlled reserves and reservoir pressure drop. Because this method is targeted at different geological conditions, it can be used to guide the horizontal well optimization of other coalbed methane blocks and has very important significance for the development and optimization of coalbed methane reservoirs. Full article

(This article belongs to the Special Issue Advances in the Development of Geoenergy: 2nd Edition)

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24 pages, 3858 KiB

Open AccessArticle

Transient and Steady-State Evaluation of Distributed Generation in Medium-Voltage Distribution Networks

by Daniel Guillén-López, Xavier Serrano-Guerrero, Antonio Barragán-Escandón and Jean-Michel Clairand

Energies 2024, 17(22), 5783; https://doi.org/10.3390/en17225783 - 20 Nov 2024

Viewed by 360

Abstract

As power generation systems with increasingly higher capacities are interconnected with distribution networks, a pressing need arises for a thorough analysis of their integration and the subsequent impacts on medium-voltage lines. This study conducts a comprehensive evaluation, encompassing both steady-state and transient behaviours, [...] Read more.

As power generation systems with increasingly higher capacities are interconnected with distribution networks, a pressing need arises for a thorough analysis of their integration and the subsequent impacts on medium-voltage lines. This study conducts a comprehensive evaluation, encompassing both steady-state and transient behaviours, leading to a holistic assessment of a real-world biogas generation system integrated into a medium-voltage network. Although the methodology does not introduce revolutionary concepts, its detailed application on a real feeder under various operating conditions adds practical value to the existing body of knowledge. The methodology explores various aspects, including voltage profiles, load capacity, power losses, short-circuit currents, and protection coordination in steady-state conditions. Additionally, a transient analysis is performed to examine the system’s response under fault conditions. This systematic approach provides a deep understanding of the system’s behaviour across diverse operational scenarios, enriching the field with practical insights. The key contributions of this study include identifying the effects of distributed generation systems (DGSs) on short-circuit currents, protection coordination, and defining voltage levels that briefly exceed the CBEMA quality curve. The benefits of incorporating a generation system into a distribution network are discussed from various technical perspectives. In a peak demand scenario, with a 1.72 MW generation capacity, the phase current experiences a notable reduction of 35.78%. Concurrently, the minimum peak demand voltage increases from 12.62 to 12.83 kV compared to a nominal voltage of 12.7 kV. Furthermore, the contribution of the generation system to the short-circuit current remains minimal, staying below 4% even under the most adverse conditions. However, our findings reveal that voltage levels exceed the upper limit of the CBEMA quality curve briefly during a single-phase fault with generation, which could potentially damage electronic equipment connected to the grid. Nonetheless, the likelihood of encountering a single-phase grounding fault with zero resistance remains low. Full article

(This article belongs to the Section F2: Distributed Energy System)

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23 pages, 14187 KiB

Open AccessArticle

Numerical Investigation of Combustion and Emission Characteristics of the Single-Cylinder Diesel Engine Fueled with Diesel-Ammonia Mixture

by Ali and Ocktaeck Lim

Energies 2024, 17(22), 5782; https://doi.org/10.3390/en17225782 - 19 Nov 2024

Viewed by 372

Abstract

This study proposes a dual-fuel approach combining diesel and ammonia in a single-cylinder compression ignition engine to reduce harmful emissions from internal combustion. Diesel is directly injected into the combustion chamber, while ammonia is introduced through the intake manifold with intake air. In [...] Read more.

This study proposes a dual-fuel approach combining diesel and ammonia in a single-cylinder compression ignition engine to reduce harmful emissions from internal combustion. Diesel is directly injected into the combustion chamber, while ammonia is introduced through the intake manifold with intake air. In this study, injection timing and the percentage of ammonia energy fraction was varied. A computational fluid dynamics (CFD) model simulates the combustion and emission processes to assess the impact of varying diesel injection timings and ammonia energy contributions. Findings indicate that as ammonia content increases, the engine experiences reductions in peak in-cylinder pressure, temperature, heat release rate, as well as overall efficiency and power output. Emission results suggest that greater ammonia usage leads to a reduction in soot, carbon monoxide, carbon dioxide, and unburned hydrocarbons, though a slight increase in nitrogen oxides emissions is observed. This analysis supports ammonia’s potential as a low-emission alternative fuel in future compression ignition engines. Full article

(This article belongs to the Topic Advanced Engines Technologies)

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15 pages, 10127 KiB

Open AccessArticle

Electrical Tortuosities of Porous Structures Based on Triply Periodic Minimal Surfaces and Honeycombs for Power-to-Heat Systems

by Thorsten Ott and Volker Dreißigacker

Energies 2024, 17(22), 5781; https://doi.org/10.3390/en17225781 - 19 Nov 2024

Viewed by 213

Abstract

Power-to-heat (P2H) systems offer an efficient solution for decarbonization by facilitating the integration of renewable energy into the industrial, heating, and transport sectors. Its key requirements include high thermal efficiency and an appropriate electrical resistivity to meet application-specific electrical needs. When designing P2H [...] Read more.

Power-to-heat (P2H) systems offer an efficient solution for decarbonization by facilitating the integration of renewable energy into the industrial, heating, and transport sectors. Its key requirements include high thermal efficiency and an appropriate electrical resistivity to meet application-specific electrical needs. When designing P2H systems, materials and electrical boundary conditions are often limited by application-specific requirements, whereas geometric structures offer high degrees of freedom. While thermal design calculations are often straightforward due to a variety of available Nusselt and pressure loss correlations, simplified design pathways, particularly for porous structures, are lacking in electrical design. Given the wide range of geometric degrees of freedom for porous structures and the fact that detailed modeling involves substantial computational effort, this work employed electrical tortuosity to capture and correlate the geometry-dependent impacts on the effective electrical resistance in a compact way. Honeycomb and triply periodic minimal surface (TPMS)-based structures were selected for this purpose, as they are characterized by high specific surfaces, allowing for high total heat transfer coefficients. The results show that the effective electrical resistance of both TPMS and honeycomb structures can be adjusted by the geometric structure. It was found that the electrical tortuosities of the investigated TPMS structures are nearly identical, while honeycomb structures show slightly higher values. Furthermore, the electrical tortuosity is mainly a function of the void fraction and does not change with the specific surface when the void fraction is kept constant. Finally, correlations for electrical tortuosity depending on geometric parameters with a mean error below 5% are derived for the first time, thereby providing a basis for simplified and computationally efficient electrical design calculations for P2H systems. Full article

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

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14 pages, 3038 KiB

Open AccessArticle

Catanionic Surfactant Systems for Emulsifying and Viscosity Reduction of Shale Oil

by Qi Li, Xiaoyan Wang, Dongping Li, Hongjiang Ge, Xiangyong Han and Enmao Xue

Energies 2024, 17(22), 5780; https://doi.org/10.3390/en17225780 - 19 Nov 2024

Viewed by 244

Abstract

Shale oil resources are abundant in the second member of the Kongdian Formation, Cangdong Sag, Bohai Bay Basin, China. However, the shale oil here has high viscosity and poor fluidity, resulting in low recovery and huge difficulty in development, gathering, and transporting. This [...] Read more.

Shale oil resources are abundant in the second member of the Kongdian Formation, Cangdong Sag, Bohai Bay Basin, China. However, the shale oil here has high viscosity and poor fluidity, resulting in low recovery and huge difficulty in development, gathering, and transporting. This study assembled a catanionic surfactant (PSG) through electrostatic interactions between cetyltrimethylammonium bromide (CTAB) and α-olefin sulfonate (AOS) in an aqueous phase, which can be used as an effective emulsifying and viscosity-reducing agents for shale oils of Dagang oilfield. The interfacial activity and emulsification performance of PSG can be optimized by changing the molar ratio of CTAB to AOS. Notably, the PSG assembled at the molar ratio of 6:4 shows the best performance, with ultra-high surface activity and excellent salt resistance. At an oil/water ratio of 1:1 and 50 °C, an aqueous solution of 0.2% PSG can emulsify five types of shale oil, making it form shale oil-in-water (O/W) emulsion with a viscosity of less than 35 mPa·s, thereby reducing the viscosity of shale oil and improving its flowability. Importantly, shale oil and water can be separated by simple sedimentation without adding demulsifiers. This study has important guiding significance for the efficient development and transportation of shale oil. Full article

(This article belongs to the Section H: Geo-Energy)

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