Comprehensive Energy Research Articles

Godunov-type scheme for air–water transient pipe flow considering variable heat transfer and laboratorial validation

A robust comprehensive energy dissipation model is developed to investigate the rapid filling process of a T-shaped bifurcated pipeline with entrapped air pocket, while an experimental system is designed to validate the numerical model. In this work, a self-adapting heat transfer model is proposed to describe the energy exchange during transient event, fully considering the heat transfer of entrapped air pocket and hydraulic losses caused by steady friction and unsteady friction in the section of the filling water column. Importantly, the related heat transfer coefficient is variable and determined by mechanism formula of media characteristics, which is obviously different from the constant heat transfer coefficient in conventional model relying on the trial-and-error method and experimental data. Moreover, the second-order Godunov-type scheme is introduced to solve the governing equations of filling water column, while a virtual plug approach is proposed to track the air–water interface. The resulting predictions are compared to those obtained via a conventional empirical polytropic model and constant coefficient heat transfer model, and to experimental data. The proposed model accurately reproduces the experimental pressure oscillations. The results display that when an air pocket content exceeds a certain threshold (>1.7%), the comprehensive model using forced convection can reproduce the pressure fluctuations. When the air content is lower (<0.9%), the comprehensive model using natural convection can simulate pressure changes more accurately. The conventional empirical polytropic model underestimates the pressure damping. The constant coefficient heat transfer model previously cannot be employed if there is no experimental data to calibrate the constant coefficient, but now the constant coefficient can be obtained from the results of the proposed model. Significantly, the comprehensive model can directly and accurately simulate the energy dissipation during the rapid filling process.

A comprehensive city-level final energy consumption dataset including renewable energy for China, 2005–2021

The role of China is increasingly pivotal in climate change mitigation, and the formulation of energy conservation and emission reduction policies requires city-level information. The effectiveness of national policy implementation is contingent upon the support and involvement of local governments. Accurate data on final energy consumption is vital to formulate and implement city-level energy transitions and energy conservation and emission reduction policies. However, there is a dearth of data sources pertaining to China’s city-level final energy consumption. To address these gaps, we developed computational modeling techniques along with top-down and downscaling methods to estimate China’s city-level final energy consumption. In this way, we compiled a final energy consumption inventory for 331 Chinese cities from 2005 to 2021, covering seven economic sectors, 30 fossil fuels, and four clean power sources. Moreover, we discussed the validity of the estimation results from multiple perspectives to enhance estimation accuracy. This dataset can be utilized for analysis in various cutting-edge research fields such as energy transition dynamics, transition risk management strategies, and policy formulation processes.

Heat Transfer Performance and Operation Scheme of the Deeply Buried Pipe Energy Pile Group

This paper describes a study on the heat transfer properties of the deeply buried pipeline energy pile group, which is an efficient and convenient geothermal development technology. Through in situ experiments and a simulation algorithm, the research investigated the heat transmission characteristics of the deeply buried pipe energy pile group and optimized different intermittent operation schemes. The findings suggest that prolonged operation of the pile cluster intensifies heat buildup within the pile foundation, thereby adversely affecting the system’s overall heat exchange efficiency. Employing an intermittent operating mode can alleviate this heat accumulation phenomenon, thereby promoting sustained heat exchange performance of the piles over time. To evaluate the comprehensive thermal interaction and energy efficiency ratio of the energy pile heat exchange system, various intermittent operation strategies were compared in the study. Among them, the intermittent operational scheme with a ratio of n = 5 was found to be optimal, with the total average heat transfer rate of the pile set only 0.51% lower than that of the continuous operational mode, but the overall energy efficiency ratio improved by 19.6%. The intermittent operational mode proposed in this study can achieve the goal of saving energy and efficiently extracting geothermal resources, providing theoretical guidance for the extraction and utilization of subsurface geothermal power by energy piles.

From 3D to 5D tracking: SMX ASIC-based double-sided micro-strip detectors for comprehensive space, time, and energy measurements

We present the recent development of a lightweight detector capable of accurate spatial, timing, and amplitude resolution of charged particles. The technology is based on double-sided double-metal p+ – n – n+ micro-strip silicon sensors, ultra-light long aluminum-polyimide micro-cables for the analogue signal transfer, and a custom-developed SMX read-out ASIC capable of measurement of the time (Δt ≲ 5 ns) and amplitude. Dense detector integration enables a material budget > 0.3 % X 0. A sophisticated powering and grounding scheme keeps the noise under control.In addition to its primary application in Silicon Tracking System of the future CBM experiment in Darmstadt, our detector will be utilized in other research applications.

The effect of Zn doping on the structure, phase transformation and electric properties of 0.5BZT-0.5BCT materials

In the current study, an improved method of adding Zn ion doping to the 0.5BZT–0.5BCT–based films with high pyroelectric properties was designed. Under different Zn ion doping ratios, the structure, dielectric constant, phase transition relationship and other characteristics of the test product were analyzed experimentally to obtain the optimal ratio parameters. The experimental results demonstrate that the dielectric properties of the 0.5BZT–0.5BCT–xZn–based films proposed in this study can be far superior to those of other films under the optimal preparation process. The optimal dielectric properties and ferroelectric properties are obtained when the doped data are 0.008. Considering the comprehensive dielectric and energy storage capacity, the optimal doping ratio is 0.01, which can take into account dielectric data and energy storage performance. The energy storage density is 1.842 J/cm3, and the energy storage efficiency exceeds 30%. From 0 to 0.02, the properties of the material, such as the hysteresis loop and phase transition relationship are excellent. The properties of the materials studied in this study are excellent, and they are excellent candidate materials for the future application of ferroelectric materials, and provide ideas for related work.

Practical application mode and future development of multi-energy coupling system

Abstract Compared with the single energy structure in the past, the energy coupling system can realize the coordinated planning and mutual economic regulation among various energy systems, which plays an important role in improving the efficiency of energy utilization. At present there are many related studies but there is a lack of systematic summary. Combining the domestic actual situation, the article mainly lists several multi-energy coupling systems including EWN, IES, BPG, etc., to analyze the energy sources, structural composition and how these systems play a good role in improving energy efficiency, it also summarizes the present situation of comprehensive energy coupling system development research and the shortcomings of current research and prospects for future development are put forward.

Comprehensive Analysis of E478 Single-Component Epoxy Resin and Tungsten-E478 Interface for Metallic-Polymer Composite Electron Source Applications.

This study provides comprehensive elemental, optical, and energy gap characteristics of the E478 single-component epoxy resin. This type of epoxy resin has imperative applications in medium voltage insulation and cold field emission of electrons. X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and hydrogen nuclear magnetic resonance (1H-NMR) were used to study the elemental and structural analyses, ultraviolet photoelectron spectroscopy (UPS) was used to obtain the local work function and the ionization potential energies, and ultraviolet/visible light spectroscopy (UV/VIS) was used to report the optical and energy gap characteristics of the epoxy resin being studied. Moreover, the UPS and UV/VIS analyses were merged to obtain the electron affinity of the E478 epoxy resin and to study the epoxy's energy band diagram and the tungsten-epoxy interface band structure. The results showed that the E478 epoxy resin is considered an n-type semiconductor of energy gap ∼3.94 eV, local work function ∼3.42 eV, ionization potential ∼6.10 eV, electron affinity ∼2.16 eV, and tungsten-epoxy Schottky contact barrier height ∼2.50 eV.

Decentralized energy trading framework with personalized pricing for energy community embedded with shared energy storage

Decentralized energy trading techniques are promising to become the next-generation scheme for energy management with the transformation of energy systems. Influenced by the sharing economy principle, the deployment of shared energy storage (SES) can mitigate the investment of storage devices and facilitate the construction of decentralized energy trading. Under such circumstances, this paper proposes a comprehensive energy trading framework for the energy community constituted of SES, prosumers, and retail energy providers. A Stackelberg game method is utilized to depict the interactions between prosumers and SES, where SES is performed as a leader and prosumers are followers. Besides, prosumers participate in the market to optimize social welfare via peer-to-peer (P2P) energy sharing with other prosumers or energy trading with SES and the main grid. We prove the existence and the uniqueness of the Stackelberg equilibrium (SE). Considering the supply and demand ratio and market contribution, a personalized pricing approach is presented for prosumers and SES to promote market competitiveness. We leverage the fully decentralized algorithm based on the fast alternating direction method of multiplier (ADMM) to solve the model of prosumers. Finally, numerical simulation demonstrates that the proposed transactive framework is economically beneficial for all participants, including SES and prosumers.

Design and control studies of six-phase interleaved boost converter for integrated energy efficiency improvement of green ship

The operation of offshore vessels is characterized by stable loads during normal voyages and significant load variations when leaving port or docking. Conventional ships emit large amounts of greenhouse gases during navigation. In the development of the modern shipbuilding industry, how to effectively reduce gas emissions during ship sailing is a challenging task that still remains under-explored. Green ships equipped with new energy power systems have a greater potential for application. They are equipped with fuel cells and lithium batteries as energy sources, and such a hybrid system requires a comprehensive energy management system to achieve the power distribution between the two energy sources. In this paper, a powerful 10kW six-phase interleaved boost converter (IBC) for the hybrid power generation system of ships is designed to manage the output power of the fuel cell. Firstly, the new circuit topology design principle and construction process are introduced. Later, a step-by-step current adjustment controller is designed for the converter to progressively enforce output current and a maximum limitation of the fuel cell. Afterwards, LTspice simulation is performed to verify the ripple suppression effect and stable anti-interference performance. Finally, the designed IBC has been experimentally constructed, including the input/output current and voltage sampling, temperature control and sampling, and other functions, significantly benefiting real-world marine high-power fuel cells. The stability, reasonableness and effectiveness of the designed IBC are further evaluated through the extensive experimental analyses.

Operational optimisation of a microgrid using non-stationary hybrid switched model predictive control with virtual storage-based demand management

Demand-shaping mechanisms are a key component of modern energy management systems, although not unproblematic. The degree of social acceptance of interference with demand or generation and the ease of integration of various types of non-critical loads depends on the method of their implementation. In addition, the critical load pool typically includes devices with different response times. The energy management systems currently in use often cannot meet user expectations. Especially when considering other vital aspects, such as energy market spread, storage wear, or connection to the utility grid and neighbouring microgrids. The authors adopted an approach of unifying demand side management and response in the form of virtual energy storage. Said store allows for the accommodation of loads operating under differing scheduling horizons. Such a new concept allows management not only in terms of quantity but also in terms of time. The storage is the focal point of a comprehensive energy management system based on switched model predictive control. The receding horizon algorithm relies on a non-stationary hybrid microgrid model. The study compares the operating costs of microgrids with virtual storage, allowing only demand postponement, preponement or bidirectional operation. The energy management system is also examined for sensitivity to changes in the weight matrices of the cost function, horizon length and forecast inaccuracy. Introducing virtual energy storage reduces microgrid operating costs by up to 16%. The decrease in control performance is proportional to the prediction accuracy, and the sensitivity allows for customisation.

Optimization scheduling for low-carbon operation of building integrated energy systems considering source-load uncertainty and user comfort

Hydrogen, being a clean energy source, presents novel possibilities for the efficient exploitation of building energy. Nevertheless, the unpredictability in the production of renewable energy, the fluctuating demand from users, and the varying comfort needs within buildings provide substantial obstacles to the functioning of building energy systems. This work suggests an optimal technique for managing a comprehensive energy system based on hydrogen. The strategy takes into account the variability in energy sources and the need for user satisfaction. Firstly, a model of building integrated energy system (BIES) is created, which includes devices for utilizing hydrogen due to its adaptable qualities. Afterwards, the adaptable attributes of electrical, cooling, and heating loads within the building are carefully examined, resulting in the creation of a integrated demand response (IDR) model and a user-integrated comfort rating model. Moreover, a ladder-type carbon tax framework is implemented, employing robust optimization methods to tackle uncertainty in the production of renewable energy and demand. Finally, a model for optimizing the scheduling of energy system operation is formulated. A case analysis is performed utilizing a spacious office building located in the northern region as an instructive example. The findings indicate that the suggested approaches successfully control user involvement in demand response, decrease carbon emissions in the system, improve user energy comfort, and accomplish the economic, low-carbon, and comfortable functioning of BIES.

Evaluation of energy performance and environmental benefits for transcritical CO2 thermal system in high-speed trains

The conventional air conditioning system used in high-speed railways has limitations in heating performance and environmental impact, necessitating the exploration of alternative refrigerants. The transcritical CO2 system has gained popularity due to its exceptional heating efficiency and environmental benefits. This study aims to evaluate the energy and environmental potentials for transcritical CO2 systems in high-speed trains based on four-vertical-and-four-horizontal railway lines within different climatic regions of China. A high-fidelity transcritical CO2 system model was first developed and validated through experiments. Then, a comprehensive energy and environmental evaluation method was proposed and applied to the four-vertical-and-four-horizontal railway lines. The results indicated that the transcritical CO2 system had a superior heating performance and competitive cooling performance based on daily and annual operations. Furthermore, the transcritical CO2 system exhibited significant environmental advantages with lower total life cycle climate performance for all lines, with an average emissions reduction ratio of 17.6% and a maximum emissions reduction ratio of 26.98%. These findings highlight the competitive energy performance and outstanding environmental benefits offered by transcritical CO2 systems as promising alternatives to air conditioning systems in railway transportation.

A machine learning framework for the prediction of grain boundary segregation in chemically complex environments

The discovery of complex concentrated alloys (CCA) has unveiled materials with diverse atomic environments, prompting the exploration of solute segregation beyond dilute alloys. However, the vast number of possible elemental interactions means a computationally prohibitive number of simulations are needed for comprehensive segregation energy spectrum analysis. Data-driven methods offer promising solutions for overcoming such limitations for modeling segregation in such chemically complex environments (CCEs), and are employed in this study to understand segregation behavior of a refractory CCA, NbMoTaW. A flexible methodology is developed that uses composable computational modules, with different arrangements of these modules employed to obtain site availabilities at absolute zero and the corresponding density of states beyond the dilute limit, resulting in an extremely large dataset containing 10 million data points. The artificial neural network developed here can rely solely on descriptions of local atomic environments to predict behavior at the dilute limit with very small errors, while the addition of negative segregation instance classification allows any solute concentration from zero up to the equiatomic concentration for ternary or quaternary alloys to be modeled at room temperature. The machine learning model thus achieves a significant speed advantage over traditional atomistic simulations, being four orders of magnitude faster, while only experiencing a minimal reduction in accuracy. This efficiency presents a powerful tool for rapid microstructural and interfacial design in unseen domains. Scientifically, our approach reveals a transition in the segregation behavior of Mo from unfavorable in simple systems to favorable in complex environments. Additionally, increasing solute concentration was observed to cause anti-segregation sites to begin to fill, challenging conventional understanding and highlighting the complexity of segregation dynamics in CCEs.

Security in advanced metering infrastructures: Lightweight cryptography

Abstract Smart grids are designed to revolutionize the energy sector by creating a smarter, more efficient and reliable power supply network. The rise of smart grids is a response to the need for a more comprehensive and sophisticated energy system that caters to the needs of homes and businesses. Key features of smart grids include the integration of renewable energy sources, decentralized generation and advanced distribution networks. At the heart of smart grids is a sophisticated metering system, consisting of intelligent electronic devices that measure energy consumption and enable two-way communication between the utility company and the consumer. The information exchanged via these devices is critical, as it includes sensitive data such as energy consumption patterns and billing information. With the rise of the Internet of Things (IoT) and Industry 4.0, the security of this information is of utmost importance. This paper delves into the security challenges faced by advanced metering infrastructure (AMI) and highlights the crucial role played by cryptography in ensuring the secure exchange of sensitive information. Cryptographic protocols such as encryption, authentication and digital signatures are essential components of a secure smart grid infrastructure. These protocols work together to ensure the confidentiality, integrity and authenticity of the information exchanged between the utility company and the consumer.

Regulating material wettability through surface plastic deformation post-processing via friction modification

The wettability of engineering materials significantly influences their cleaning and antifreeze properties, making it a key consideration in aerospace applications. Methods for controlling surface plastic deformation can alter the wettability of materials and contribute to a certain level of strengthening effect, thereby presenting significant application potential. This study aimed to modify the wetting characteristics of aviation titanium alloys in harsh environments through adjustments in surface roughness via peening treatments (such as laser shock peening with coating and mechanical shot peening). The impact of various peening processes on wetting characteristics was investigated through comprehensive surface energy, macro, and nano morphology analyses. Static contact angle measurements were quantified, followed by evaluating other properties, such as surface free energy. Through adjustments in post-treatment processes and control of surface roughness, tailored acquisition of wetting characteristics was achieved. This study elucidates the beneficial effect of surface plastic deformation post-processing on controlling material wettability and introducing strengthening effects. Additionally, the study indicates the importance of accurately determining the sampling range for precise characterization of material wettability.

Economic and Energy Efficiency Analysis of the Biogas Plant Digestate Management Methods

The aim of this study was to conduct a comprehensive economic and energy efficiency analysis of selected digestate management methods, considering their implications on operational costs and resource management. To achieve this aim, the study focuses on a comparative assessment of different digestate management methods, including land application, mechanical separation, the composting process and pellet production. The economic analysis involves the evaluation of the initial investment, operational expenses, and potential revenue streams associated with each method. The most economical and popular solution of digestate management is direct use as fertilizer, with total costs of 1.98 EUR·Mg−1. All of the other methods involve higher digestate management costs, respectively; for separation it is 2.42 EUR·Mg−1, for composting it is 2.81 EUR·Mg−1. The process that is the most energy-intensive, but profitable, is the production of pellets from digestate, resulting in profits of 334,926 EUR·year−1. It should be noted that the other analyzed methods of digestate management also bring many environmental benefits, affecting sustainability and reducing emissions. The results of this research will contribute unique data on the feasibility of managing the digestate and its fractions. The calculations of economic and energy values for different strategies will allow for the optimization of the overall performance of the biogas plant, thus promoting a circular economy.

Balancing Possibilist-probabilistic risk assessment for smart energy hubs: Enabling secure peer-to-peer energy sharing with CCUS technology and cyber-security

This paper introduces the Possibilistic-Probabilistic Risk-based Smart Energy Hub (PPR-SEH) scheduling model, addressing cybersecurity challenges in the transition to advanced energy systems characterized by decarbonization, decentralization, and digitalization. The model integrates cutting-edge technologies like Carbon Capture Utilization and Storage (CCUS) and demand response programs. It addresses uncertainties from renewable energy sources, demand variability, fuel supply, and energy price fluctuations using a Z-number-based approach. Covering various energy types—electricity, heat, cooling, gas, and water—the PPR-SEH model offers a comprehensive energy management solution. Employing a mixed-integer linear programming (MILP) framework optimized with the CPLEX solver in GAMS software, it uses an epsilon constraint method and a fuzzy satisfying approach for solution selection. The model also evaluates the economic and environmental impacts of peer-to-peer energy-sharing markets linked with carbon emission trading, enhancing the efficiency and sustainability of energy distribution. The findings reveal that incorporating robust cybersecurity measures and integrating demand response and CCUS significantly influence operational efficiency and sustainability, evidenced by an increase in costs and pollution by approximately 11.43 % and 1.8 %, respectively, compared to deterministic approaches. This study underscores the importance of robust planning and the beneficial impact of a carbon system on load curve management and economic returns in smart energy systems.

High-entropy relaxor ferroelectric ceramics for ultrahigh energy storage

Dielectric ceramic capacitors with ultrahigh power densities are fundamental to modern electrical devices. Nonetheless, the poor energy density confined to the low breakdown strength is a long-standing bottleneck in developing desirable dielectric materials for practical applications. In this instance, we present a high-entropy tungsten bronze-type relaxor ferroelectric achieved through an equimolar-ratio element design, which realizes a giant recoverable energy density of 11.0 J·cm−3 and a high efficiency of 81.9%. Moreover, the atomic-scale microstructural study confirms that the excellent comprehensive energy storage performance is attributed to the increased atomic-scale compositional heterogeneity from high configuration entropy, which modulates the relaxor features as well as induces lattice distortion, resulting in reduced polarization hysteresis and enhanced breakdown endurance. This study provides evidence that developing high-entropy relaxor ferroelectric material via equimolar-ratio element design is an effective strategy for achieving ultrahigh energy storage characteristics. Our results also uncover the immense potential of tetragonal tungsten bronze-type materials for advanced energy storage applications.

Revolutionizing smart grid-ready management systems: A holistic framework for optimal grid reliability

Existing energy management systems are becoming increasingly insecure and inefficient due to the rapid adoption of smart grid technology. Current research indicates that effectively managing dynamic energy flows, adjusting to changing needs, and protecting against new cyber threats remain significant challenges for the smart grid system. An advanced and comprehensive plan for managing smart grids is therefore required, capable of addressing these delicate and multifaceted problems. The proposed framework addresses these challenges through unifying several key aspects, it includes an advanced data acquisition system that captures real-time data from various grid sources, enabling comprehensive energy monitoring and dynamic flow analysis. By integrating predictive algorithms, the framework provides precise energy demand forecasting, which is essential for adaptive grid management. A significant contribution is the incorporation of an AI-based module for diagnostics and prognostics, which leverages machine learning techniques to shift from reactive to proactive maintenance strategies. The optimal power flow (OPF) optimization module represents a central component of the framework. It employs advanced computational methods to ensure efficient and cost-effective power distribution, particularly in grids incorporating renewable energy sources. Additionally, the architectural framework is strengthened by a robust cybersecurity module designed to safeguard against a wide range of cyber threats, maintaining the integrity of both operational and consumer data. This paper also addresses practical implementation challenges such as compatibility with existing infrastructure, investment costs, and the need for specialized training. This solution represents a new benchmark for smart grid operations, ensuring more sustainable and efficient energy systems.

A novel trigeneration energy system with two modes of operation for thermal energy storage and hydrogen production

This article introduces a new trigeneration system designed to meet the escalating energy demands by harnessing solar energy. Notably, the system features dual-mode operation and integrates ultrasound technology for hydrogen production, enabling it to adapt to varying levels of energy production by seamlessly transitioning between two modes. Through comprehensive energy, exergy, and environmental analyses, this study evaluates the system's performance and its environmental advantages. The results demonstrate that the system achieves the energy and exergy efficiencies of 58.28 % and 76.75 %, respectively. Moreover, it demonstrates that, under sunlight conditions, the system can produce hydrogen at a rate of 1 kg/h and deliver a power output of 1957 kW. During the periods utilizing a thermal energy storage option, the system is capable of generating hydrogen at 0.8 kg/h and an electrical power output of 1481.2 kW. The environmental analysis indicates that the system is eco-friendly, with the potential to reduce carbon dioxide emissions by 4.54 kg/kWh. These results underscore the system's efficiency and its contribution toward a more sustainable and environmentally friendly energy future.