Search

In this paper, the aging characterization of a kind of insulating paper modified by magnetron sputtering MgO particles based on a microstrip resonant sensor was presented. Firstly, the modified insulating paper with 0, 15 and 30 min MgO particle sputtering times was prepared by a magnetron sputtering device. After that, the properties of the modified insulating paper with different sputtering times were analyzed through microscopic characterization, infrared spectrum, polymerization degree, dielectric constant, AC breakdown strength and thermal aging experiments. The results show that the dielectric constant of the modified insulating paper decreased obviously, the AC breakdown strength increased and the thermal aging resistance was better after 15 min of sputtering. The overall performance of the modified insulating paper after 30 min of sputtering is reduced due to excessive sputtering. In addition, microstrip resonant sensors are introduced to characterize the thermal aging degree of the modified insulating paper, and two microstrip resonant sensors are prepared: a complementary split ring resonator (CSRR) and an interdigital-capacitor-shaped defected ground structure resonator (IDCS-DGS). The resonance frequency deviation of the modified insulating paper samples after aging was measured by microstrip resonance sensors to show the influence of aging temperature on aging degree. The experimental results show that the test results of the microstrip resonance sensors are in good agreement with the traditional characterization methods and can characterize the various aging stages of the modified insulating paper to a certain extent, which proves the feasibility of the characterization method. [ABSTRACT FROM AUTHOR]

Oil–paper insulation is the critical insulation element in the modern power system. Under a harsh operating environment, oil–paper insulation will deteriorate gradually, resulting in electrical accidents. Thus, it is important to evaluate and monitor the insulation state of oil–paper insulation. Firstly, this paper introduces the geometric structure and physical components of oil–paper insulation and shows the main reasons and forms of oil–paper insulation's degradation. Then, this paper reviews the existing condition assessment techniques for oil–paper insulation, such as the dissolved gas ratio analysis, aging kinetic model, cellulose–water adsorption isotherm, oil–paper moisture balance curve, and dielectric response technique. Additionally, the advantages and limitations of the above condition assessment techniques are discussed. In particular, this paper highlights the dielectric response technique and introduces its evaluation principle in detail: (1) collecting the dielectric response data, (2) extracting the feature parameters from the collected dielectric response data, and (3) establishing the condition assessment models based on the extracted feature parameters and the machine learning techniques. Finally, two full potential studies are proposed, which research hotspots' oil–paper insulation and the electrical–chemical joint evaluation technique. In summary, this paper concludes the principles, advantages and limitation of the existing condition assessment techniques for oil–paper insulation, and we put forward two potential research avenues. [ABSTRACT FROM AUTHOR]

Natural and synthetic esters are increasingly being chosen instead of mineral oil for environmental and fire safety reasons. However, their use in power transformers is limited due to insufficiently well-understood ageing processes affecting their properties and the properties of cellulosic materials impregnated with them. The research results presented in many scientific papers prove that the use of esters slows the ageing process of cellulosic materials. This article presents the results of research aimed at answering the question of whether the effect of slowing the ageing process will also occur in the case of insulation with very low initial moisture. The answer to this question will allow us to better understand the role of water in the ageing process of the transformer's insulation system. The thermal ageing process was carried out at a temperature of 150 °C in closed systems. The degree of cellulose polymerisation was taken as a measure of the degree of paper ageing. Great attention was paid to measuring the water content in both paper and electro-insulating liquids at various stages of their ageing. Furthermore, measurements of the properties of electro-insulating liquids were made, which are considered markers of ageing. The test results obtained indicate that in the case of a dry insulation system, corresponding to the initial moisture of the new units, the type of liquid used to impregnate the cellulosic material does not significantly affect its depolymerisation process. However, in the case of paper impregnated with natural esters, a lower dynamic of moisture increase in insulation was observed. [ABSTRACT FROM AUTHOR]

Mass-impregnated (MI) cables have been used for many years as cables in high-voltage direct current (HVDC) systems. In line commutated converter (LCC) HVDC systems, polarity reversal for power flow control can induce significant electrical stress on MI cables. Furthermore, the mass oil and kraft paper comprising the impregnated insulation have significantly different coefficients of thermal expansion. Load fluctuations in the cable lead to expansion and contraction of the mass, creating pressure within the insulation and causing redistribution of the impregnant. During this process, shrinkage cavities can form within the butt gaps. Since the dielectric strength of the cavities is lower than that of the surrounding impregnation, cavitation phenomena in impregnated paper insulation are considered a factor in degrading insulation performance. Consequently, this study analyzes the electrical conductivity of thermally aged materials and investigates the transient electric field characteristics within the cable. Additionally, it closely analyzes the formation and dissolution of cavities in MI cables during polarity reversal based on a numerical model of pressure behavior in porous media. The conductivity of the impregnated paper indicates that it has excellent resistance to thermal degradation. Simulation results for various load conditions highlight that the interval of load-off time and the magnitude of internal pressure significantly influence the cavitation phenomenon. Lastly, the study proposes stable system operation methods to prevent cavitation in MI cables. [ABSTRACT FROM AUTHOR]

Heat pumps have the potential for several applications across various industrial sectors, showcasing significant promise, especially in sectors such as pulp and paper, food and beverage, chemical, non-metallic minerals, and machinery. Envisioning the near future, there is confidence that heat pumps can achieve temperatures above 200 °C, offering substantial potential for utilization in these sectors. Nevertheless, a crucial aspect for the advancement of high-temperature heat pumps is the selection of the fluid. Fluid selection involves considerations of both thermodynamic efficiency and environmental impact, requiring fluids with zero ODP, negligible GWP, and no PFAS. Moreover, it is essential to consider the risks to human health associated with a specific fluid. Despite extensive research, particularly in the realm of vapour compression heat pumps, choosing the most suitable working fluid for these applications is a complex undertaking. Therefore, this paper conducts a theoretical analysis to evaluate potential fluids with suitable thermodynamic properties for high-temperature heat pumps (HTHPs). The comparative results gleaned from this study provide valuable insights for the comprehensive analysis of fluids, showing promise within temperature ranges dictated by specific applications. The metrics employed in the comparison emphasise the merits of fluids in terms of the overall performance, dimensions, and operating ranges of applicable compressor, heat exchange capacity, transport properties, and safety. One noteworthy finding from the analysis is that maintaining a constant HTHP lift (at 40 K) results in having the highest COP across all fluids when the condensing temperature ranges between 85% and 90% of their respective critical temperatures. According to the results of the analysis, natural fluids, including water and alcohols like ethanol or methanol, emerge as particularly compelling candidates. [ABSTRACT FROM AUTHOR]

Hydrothermal carbonization (HTC) of low quality, wet biogenic residues into intermediate bioenergy carriers can potentially contribute to a more flexible and stable renewable energy system and reduce environmental impacts compared to current residue disposal practices. This study quantifies the environmental impacts via life cycle assessment (LCA) of a novel hydrothermal process for the treatment on an industrial scale of application of three wet biogenic residues (paper bio-sludge, olive pomace, and orange peel) into bioenergy carriers, i.e., solid pellets and biogas. A comprehensive attributional cradle-to-gate life cycle assessment (LCA) was conducted; the life cycle impact assessment (LCIA) utilised the ReCiPe impact assessment method. A selection of 10 significant impact categories was prioritised. Reliability of this categorization was also ensured through a sensitivity analysis carried out using Monte Carlo simulation. Climate change, particulate matter formation and terrestrial acidification impact categories showed the highest reliability, while for freshwater ecotoxicity and freshwater eutrophication impact categories in the study suggest the need for more robust data and further investigation. The climate change impact category presents the following values, as kg CO2eq/tresidue: pulp and paper bio-sludge (PPB), 17.9; olive pomace (OP), −1290; orange peel (ORP), −1301. The LCA study compared electricity yields of the hydrothermal treatment process with conventional treatment processes for each of the target residue streams. The environmental performance of the proposed hydrothermal treatment benefits significantly from the combination of intermediate bioenergy carriers (pellets) from the solid fraction with biogas production from the liquid fraction. Avoided emissions due to the heat recovery provide further environmental benefits. The LCIA results show that the carbon footprint of the F-CUBED production system, as kgCO2eq/kWhe, accounts for –4.56, −0.63, and −0.25 for paper bio-sludge, olive pomace and orange peel, respectively. [ABSTRACT FROM AUTHOR]

The methods of artificial intelligence (AI) have been used in the planning and operation of electric power systems for more than 40 years. In recent years, due to the development of microprocessor and data storage technologies, the effectiveness of this use has greatly increased. This paper provides a systematic overview of the application of AI, including the use of machine learning (ML) in the electric power system. The potential application areas are divided into four blocks and the classification matrix has been used for clustering the AI application tasks. Furthermore, the data acquisition methods for setting the parameters of AI and ML algorithms are presented and discussed in a systematic way, considering the supervised and unsupervised learning methods. Based on this, three complex application examples, being wind power generation forecasting, smart grid security assessment (using two methods), and automatic system fault detection are presented and discussed in detail. A summary and outlook conclude the paper. [ABSTRACT FROM AUTHOR]

The use of film cooling is crucial to avoid high metal temperatures in gas turbine applications, thus ensuring a high lifetime for vanes and blades. The complex turbulent mixing process between the coolant and the main flow requires an accurate numerical prediction to correctly estimate the impact of ejection conditions on the cooling performance. Recent developments in numerical models aim at using hybrid approaches that combine high precision with low computational cost. This paper is focused on the numerical simulation of a cylindrical film cooling hole that operates at a unitary blowing ratio, with a hot gas Mach number of Ma m = 0.6, while the coolant is characterized by plenum conditions ( Ma c = 0). The adopted numerical approach is the Stress-Blended Eddy Simulation model (SBES), which is a blend between a Reynolds-Averaged Navier–Stokes approach and a modeled Large Eddy Simulation based on the local flow and mesh characteristics. The purpose of this paper is to investigate the ability of the hybrid model to capture the complex mixing between the coolant and the main flow. The cooling performance of the hole is quantified through the film cooling effectiveness, the Net Heat Flux Reduction (NHFR), and the discharge coefficient C D calculation. Numerical results are compared both with the experimental data obtained by the University of Karlsruhe during the EU-funded TATEF2 project and with a Scale Adaptive Simulation (SAS) run on the same computational grid. The use of λ 2 profiles extracted from the flow field allows for isolating the main vortical structures such as horseshoe vortices, counter-rotating vortex pairs (e.g., kidney vortices), Kelvin–Helmholtz instabilities, and hairpin vortices. Eventually, the contribution of the unsteady phenomena occurring at the hole exit section is quantified through Proper Orthogonal Decomposition (POD) and Spectral Proper Orthogonal Decomposition methods (SPOD). [ABSTRACT FROM AUTHOR]

There are several complex and unpredictable aspects that affect the power grid. To make short-term power load forecasting more accurate, a short-term power load forecasting model that utilizes the VMD-Crossformer is suggested in this paper. First, the ideal number of decomposition layers was ascertained using a variational mode decomposition (VMD) parameter optimum approach based on the Pearson correlation coefficient (PCC). Second, the original data was decomposed into multiple modal components using VMD, and then the original data were reconstructed with the modal components. Finally, the reconstructed data were input into the Crossformer network, which utilizes the cross-dimensional dependence of multivariate time series (MTS) prediction; that is, the dimension-segment-wise (DSW) embedding and the two-stage attention (TSA) layer were designed to establish a hierarchical encoder–decoder (HED), and the final prediction was performed using information from different scales. The experimental results show that the method could accurately predict the electricity load with high accuracy and reliability. The MAE, MAPE, and RMSE were 61.532 MW, 1.841%, and 84.486 MW, respectively, for dataset I. The MAE, MAPE, and RMSE were 68.906 MW, 0.847%, and 89.209 MW, respectively, for dataset II. Compared with other models, the model in this paper predicted better. [ABSTRACT FROM AUTHOR]

The three-dimensional (3D) path planning problem of an Unmanned Aerial Vehicle (UAV) considering the effect of environmental wind in a dense city is investigated in this paper. The mission of the UAV is to fly from its initial position to its destination while ensuring safe flight. The dense obstacle avoidance and the energy consumption in 3D space need to be considered during the mission, which are often ignored in common studies. To solve these problems, an improved Deep Reinforcement Learning (DRL) path planning algorithm based on Double Deep Q-Network (DDQN) is proposed in this paper. Among the algorithms, the random obstacle training method is first proposed to make the algorithm consider various flight scenarios more globally and comprehensively and improve the algorithm's robustness and adaptability. Then, the linear soft update strategy is employed to realize the smooth neural network parameter update, which enhances the stability and convergence of the training. In addition, the wind disturbances are integrated into the energy consumption model and reward function, which can effectively describe the wind disturbances during the UAV mission to achieve the minimum drag flight. To prevent the neural network from interfering with training failures, the meritocracy mechanism is proposed to enhance the algorithm's stability. The effectiveness and applicability of the proposed method are verified through simulation analysis and comparative studies. The UAV based on this algorithm has good autonomy and adaptability, which provides a new way to solve the UAV path planning problem in dense urban scenes. [ABSTRACT FROM AUTHOR]

The transition process from fossil fuels to environmentally friendly renewable energy sources carries the risk of creating new environmental damages. Photovoltaic technology represents one of the alternatives with the least risk of harmful environmental impact. However, this technology has two important drawbacks: the significant land occupation for the installation of PV systems and the uncontrollability of production. By constructing floating photovoltaic plants on hydroelectric reservoirs, both of these problems can be reduced to an acceptable level. Some artificial reservoirs, originally built for hydroelectric power plants, have acquired a significant secondary function as recreational areas and fish breeding sites. Therefore, there is justified resistance from the local community to change the existing appearance and purpose of such reservoirs. This paper proposes a completely new concept of integrating the interests of the local community into such objects. In addition to preserving existing uses, the concept also offers new features. This can make the entire system environmentally friendly and sustainable. This paper details the technology behind the construction of floating photovoltaic power plants on artificial reservoirs and emphasizes their various advantages. These benefits include the non-utilization of cultivable land, the ease of assembly and construction, integration into existing power grids, and the potential to address electricity storage issues. For instance, Buško Lake, covering an area of 55.8 km2, may host 2.93 km2 of installed floating photovoltaic (FPV) facilities, enabling a total installed capacity of 240 MW. With an average of 5.5 h of daily sunshine, this totals 2007 annual hours, equivalent to a 55 MW thermal power plant. An analysis showed that, with losses of 18.2%, the average annual production stands at 302 G W h , translating to an annual production value of 18 million € at 60 €/MWh. The integration of this production into an existing hydroelectric power plant featuring an artificial reservoir might boost its output by 91%. The available transmission line capacity of 237 MW is shared between the hydroelectric power plant (HPP) and FPV; hence during the FPV maximum power generation time, the HPP halts its production. HPP Orlovac operates a small number of hours annually at full capacity (1489 h); therefore in combination with the FPV, this number can be increased to 2852 h. This integration maintains the lake's functions in tourism and fishing while expanding its capabilities without environmental harm. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive and systematic analysis of the environmental impacts (EI) produced by novel nickel-zinc battery (RNZB) technology, which is a promising alternative for energy storage applications. The paper develops mathematical models for estimating the life cycle environmental impacts of RNZB from cradle to grave, based on an extensive literature review and the ISO standards for life cycle costing and life cycle analysis. The paper uses the ReCiPe 2016 method of life cycle analysis (LCA) to calculate the EI of RNZB in terms of eighteen Midpoint impact categories and three Endpoint impact categories: damage to human health, damage to ecosystem diversity, and damage to resource availability. The paper also compares the EI of RNZB with those of other battery technologies, such as lead-acid and lithium-ion LFP and NMC. The paper applies the models and compares results with those provided by the software openLCA (version 1.11.0), showing its reliability and concluding that NiZn batteries contribute approximately 14 MJ for CED and 0.82 kg CO2 eq. for global warming per kWh of released energy, placing them between lithium-ion and lead-acid batteries. This study suggests that NiZn battery technology could benefit from using more renewable energy in end-use applications and adopting green recovery technology to reduce environmental impact. Further developments can use these models as objective functions for heuristic optimisation of the EI in the life cycle of RNZB. [ABSTRACT FROM AUTHOR]

Degradation is an inevitable companion in the operation of solid oxide fuel cell (SOFC) systems since it directly deteriorates the reliability of the system's operation and the system's durability. Both are seen as barriers that limit the extensive commercial use of SOFC systems. Therefore, diagnosis and prognosis are valuable tools that can contribute to raising the reliability of the system operation, efficient health management, increased durability and implementation of predictive maintenance techniques. Remaining useful life (RUL) prediction has been extensively studied in many areas like batteries and proton-exchange membrane fuel cell (PEM) systems, and a range of different approaches has been proposed. On the other hand, results available in the domain of SOFC systems are still relatively limited. Moreover, methods relying on detailed process models and models of degradation turned out to have limited applicability for in-field applications. Therefore, in this paper, we propose an effective, data-driven approach to predicting RUL where the trend of the health index is modeled by an adaptive linear model, which is updated at all times during the system operation. This allows for a closed-form solution of the probability distribution of the RUL, which is the main novelty of this paper. Such a solution requires no computational load and is as such very convenient for the application in ordinary low-cost control systems. The performance of the approach is demonstrated first on the simulated case studies and then on the data obtained from a long-term experiment on a laboratory SOFC system. From the tests conducted so far, it turns out that the quality of the RUL prediction is usually rather low at the beginning of the system operation, but then gradually improves while the system is approaching the end-of-life (EOL), making it a viable tool for prognosis. [ABSTRACT FROM AUTHOR]

This paper deals with the quasi-instantaneous determination (in a single-step response time) of apparent, active, and reactive (i.e., blind and distortion) power mean values including the total power factor, total harmonic distortion, and phase shift of fundamentals of a power electronic and electrical system (PEES) using the ip-iq method, which is the main contribution of the paper. The power components' mean values are investigated during the transient and steady states. The power components' mean values can be determined directly from phase current and voltage quantities, using an integral calculus over one period within the next calculation step and using moving average and moving rms techniques (or digital filtering). Consequently, the power factor can be evaluated with known values of a phase shift of fundamentals (using a Fourier analysis). The results of this study show how a distortion power component during transients is generated even under a harmonic supply and linear resistive–inductive load. The paper contains a theoretical base, modeling, and simulation for the three and single phases of the transients in power electronic systems. The worked-out results can be used to determine and size any PES. The presented approach brings a detailed time waveform verified by simulations in Matlab/Simulink 2022a and the Real-time HW Simulator Plecs RT Box 1. [ABSTRACT FROM AUTHOR]

Full- and reduced-order observers have been used in many engineering applications, particularly for energy systems. Applications of observers to energy systems are twofold: (1) the use of observed variables of dynamic systems for the purpose of feedback control and (2) the use of observers in their own right to observe (estimate) state variables of particular energy processes and systems. In addition to the classical Luenberger-type observers, we will review some papers on functional, fractional, and disturbance observers, as well as sliding-mode observers used for energy systems. Observers have been applied to energy systems in both continuous and discrete time domains and in both deterministic and stochastic problem formulations to observe (estimate) state variables over either finite or infinite time (steady-state) intervals. This overview paper will provide a detailed overview of observers used for linear and linearized mathematical models of energy systems and review the most important and most recent papers on the use of observers for nonlinear lumped (concentrated)-parameter systems. The emphasis will be on applications of observers to renewable energy systems, such as fuel cells, batteries, solar cells, and wind turbines. In addition, we will present recent research results on the use of observers for distributed-parameter systems and comment on their actual and potential applications in energy processes and systems. Due to the large number of papers that have been published on this topic, we will concentrate our attention mostly on papers published in high-quality journals in recent years, mostly in the past decade. [ABSTRACT FROM AUTHOR]

With the high proportion of renewable energy sources and power electronic devices accessed in the distribution network, the harmonic pollution problem has become increasingly serious. The traditional centralized harmonic mitigation strategy has difficulty in effectively dealing with these scattered and random harmonics. Therefore, a distributed harmonic mitigation strategy based on the dynamic points incentive of blockchain communities is proposed in this paper. Firstly, a comprehensive voltage sensitivity partitioning method with harmonic weight differentiation is proposed to realize the reasonable partitioning of each control node and controlled node in the distribution network concerning variability in harmonic components and their distribution. Then, a harmonic mitigation strategy based on the dynamic integral excitation of self-learning algorithms is constructed to promote self-organized optimization and active distributed coordinated control of mitigation devices. The strategy ensures that the total harmonic voltage distortion rate of each node meets the requirements by adjusting the partitioned collaboration to realize optimal harmonic mitigation. By setting optimized partitions in different scenarios and conducting simulation verification, the results demonstrate the effectiveness of the strategy in this paper. It stimulates synergy between devices through a dynamic incentive mechanism and significantly reduces the total harmonic voltage distortion rate across various test scenarios, reflecting the adaptability of the harmonic mitigation method presented. [ABSTRACT FROM AUTHOR]

China is currently focusing on the cooperative control of air pollution and CO2 emissions, as well as the mitigation of economic policy uncertainty (EPU). By using panel data from 282 cities spanning from 2003 to 2017 and a newly constructed city-level EPU index, a spatial Durbin, two-way fixed-effects model is employed, with the aim of estimating the impact of EPU on the synergistic emissions intensity (SEI) of air pollutants and CO2. Additionally, this paper investigates the potential channels through which EPU influences SEI. It also explores how pressures related to environmental protection and economic development affect the impact of EPU on SEI. The results indicate that a unit increase in EPU will result in a rise in the SEI of local cities, adjacent cities, and total cities by 930.9%, 69,162.7%, and 70,093.6%, respectively. Moreover, the channel analysis suggests that EPU exacerbates SEI by undermining the upgrading of the industrial structure, augmenting industrial structure distortion, and escalating labor market distortion. Furthermore, the effect of EPU on SEI may be lessened by an increase in environmental protection pressure, while an increase in economic development pressure may exert a positive influence. Finally, this paper concludes by recommending that policymakers should prioritize the maintenance and stability of economic policies, facilitate the advancement of the industrial structure, enhance the efficiency of labor resource allocation, and underscore the significance of managing urban air pollution and CO2 emissions. [ABSTRACT FROM AUTHOR]

This paper investigates whether renewable energy influences economic growth and happiness. Using panel data from 25 European Union countries for the period 2012–2022, this study employs a panel model for estimation with fixed and random effects, and robust HAC standard errors. According to the research results, in general, the growing share of renewable energy in the energy mix has a positive impact on economic growth and the happiness of citizens. However, detailed research has shown that this effect depends on the type of energy; a significant positive impact was recorded only in solar share energy, wind share energy and economic growth. However, almost all types of renewable energy were included, i.e., biofuel, hydro, solar and other renewable share energy, and all had a significantly positive impact on the level of happiness. The exception was wind share energy, which showed a significant negative impact. The research findings of this paper provide empirical support for promoting renewable energy, which is positive both for economies and the happiness of citizens. It is one of the main aspects of sustainable economic growth. [ABSTRACT FROM AUTHOR]

This paper introduces a novel hybrid filtering algorithm that leverages the advantages of Phasor Measurement Units (PMU) to address state estimation challenges in power systems. The primary objective is to integrate the benefits of PMU measurements into the design of traditional power system dynamic estimators. It is noteworthy that PMUs and Supervisory Control and Data Acquisition (SCADA) systems typically operate at different sampling rates in power system estimation, necessitating synchronization during the filtering process. To address this issue, the paper employs a predictive interpolation method for SCADA measurements within the framework of the Extended Kalman Filter (EKF) algorithm. This approach achieves more accurate estimates, closer to real observation data, by averaging the KL distribution. The algorithm is particularly well-suited for state estimation tasks in power systems that combine traditional and PMU measurements. Extensive simulations were conducted on the IEEE-14 and IEEE-30 test systems, and the results demonstrate that the fused estimator outperforms individual estimators in terms of estimation accuracy. [ABSTRACT FROM AUTHOR]

A predictive model for the spatiotemporal distribution of electric vehicle (EV) charging load is proposed in this paper, considering multimodal travel behavior and microscopic traffic simulation. Firstly, the characteristic variables of travel time are fitted using advanced techniques such as Gaussian mixture distribution. Simultaneously, the user's multimodal travel behavior is delineated by introducing travel purpose transfer probabilities, thus establishing a comprehensive travel spatiotemporal model. Secondly, the improved Floyd algorithm is employed to select the optimal path, taking into account various factors including signal light status, vehicle speed, and the position of starting and ending sections. Moreover, the approach of multi-lane lane change following and the utilization of cellular automata theory are introduced. To establish a microscopic traffic simulation model, a real-time energy consumption model is integrated with the aforementioned techniques. Thirdly, the minimum regret value is leveraged in conjunction with various other factors, including driving purpose, charging station electricity price, parking cost, and more, to simulate the decision-making process of users regarding charging stations. Subsequently, an EV charging load predictive framework is proposed based on the approach driven by electricity prices and real-time interaction of coupled network information. Finally, this paper conducts large-scale simulations to analyze the spatiotemporal distribution characteristics of EV charging load using a regional transportation network in East China and a typical power distribution network as case studies, thereby validating the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Due to the influence of many factors, distribution cables are often densely placed at the bottom of the cable trench. As a result, it is easy for distribution cables to become the thermal bottleneck of the whole transmission line. To address this dilemma, this paper establishes a finite element simulation model of a cable trench to analyze the hot spots of cables with different arrangements in the cable trench. Then, the model's accuracy is verified based on real temperature rise experiments. For an arrangement with overheating risk, the ampacity improvement method of filling the cable trench with high-thermal-conductivity material was proposed, and the ampacity improvement effect under different filling ratios was assessed. Finally, combined with the analysis of economic benefit and cost, the method of determining the optimal filling ratio was used, and the impact resistance of the cables under the impact of new energy load was analyzed. The results indicate that, for the case of the optimal filling ratio, the cables in the dense cable trench showed superior impact resistance. The investigations in this paper make significant contributions to the promotion of the maximum utilization of cables. [ABSTRACT FROM AUTHOR]

The objective of a power system is to provide electricity to its customers as economically as possible with an acceptable level of reliability while safeguarding the environment. Power system reliability assessments are routinely performed to ensure adequate system resources and reliable operation using well-established methods, quantitative metrics, regulatory standards and compliance incentives in the jurisdictions of responsibilities. The alarming increase in the occurrence of extreme events, which are not included in routine reliability evaluation, has raised growing concerns due to the catastrophic impacts of these events on distribution systems. The potential economic losses due to prolonged and large-scale outages have motivated utility planners, operators and policy makers to acknowledge the importance of system resiliency against such events. Power system resiliency, however, lacks widely accepted modeling frameworks, standards, assessment methods and metrics. This paper presents a resilience assessment framework, along with quantifiable metrics to assess the resiliency of a distribution system against extreme winds, which are among the most common form of natural disasters affecting the North American region. The paper assesses the effectiveness of infrastructural and operational resilience enhancement strategies. The effectiveness of preventive and corrective strategies is also analyzed on a test distribution system. [ABSTRACT FROM AUTHOR]

Due to its simplicity, the one-diode model is commonly used for modeling the operation of photovoltaic (PV) modules at standard test conditions (STC). However, its inherent implicit nature often presents challenges in modeling PV energy production. In this paper, the innovative explicit one-diode model developed by us over time is adapted for estimating PV power production under real weather conditions. Simple yet accurate equations for calculating the energy output of a PV generator equipped with a maximum power point tracking (MPPT) system are proposed. The model's performance is assessed under various normal and harsh operating conditions against measured data collected from the experimental setup located at the Solar Platform at West University of Timisoara, Romania. As an application of the new equation for maximum power, this paper presents a case study where the energy loss in the absence of an MPPT system is evaluated based on atmospheric and sky conditions. [ABSTRACT FROM AUTHOR]

The integration of renewable generation presents a promising venue for displacing fossil fuels, yet integration remains a challenge. This paper investigates Demand Response (DR) as a means of economically integrating Renewable Energy Resources (RERs). We propose Incentive-Based DR (IBDR) programs, particularly suitable for small customers. The uncertainties in the electricity market price pose a challenge to IBDR programs, which is addressed in this paper through a novel and robust IBDR approach that considers both the electricity market price uncertainties and customer responses to incentives. In this paper, scenarios are simulated premised on the Western Electricity Coordinating Council (WECC) 240-bus system in which coal-fired power plants become inactivated, while the RER contribution increases in the span of one year. The simulation results indicate that the proposed IBDR program mitigates the issues associated with renewable expansion, such as utility benefit loss and market price volatility. In addition, the proposed IBDR effectively manages up to 30% of errors in day-ahead wind forecasts that significantly reduce financial risks linked to IBDR programs. [ABSTRACT FROM AUTHOR]

The technique of refracturing is an effective method to solve the rapid decline in oil well production caused by factors such as severe reservoir energy loss and fracture failure after the initial hydraulic fracturing of low-permeability reservoirs. The key to designing refracturing lies in establishing a model for evaluating the potential fracturing layers. Based on the geological characteristics of the low-permeability conglomerate reservoir in the Lower Wuerhe area of the Eig District of the Xinjiang Oilfield, this paper studies the influence of different development approaches on the distribution pattern of remaining oil in the reservoir. A coupled model of remaining oil distribution and the in situ stress field is established and discusses the characteristics of the four-dimensional in situ stress field under different development modes. This paper analyzes the influence of geological factors and well network factors on the distribution of residual oil, and analyzes the influence of various factors, such as reservoir properties and injection and extraction parameters, on ground stress. Based on the residual oil distribution and ground stress changes, an evaluation method for screening potential fractured layers in reservoirs with different development modes (water injection development and depletion development) is developed. [ABSTRACT FROM AUTHOR]

This paper investigates the economic competitiveness of hydrogen-powered trucks. It reviews the growing number of papers that provide an estimate of the total cost of ownership (TCO) of hydrogen-powered trucks relative to their diesel equivalents. It examines the methodology applied, the variables considered, the data used for estimation, and the results obtained. All reviewed studies conclude that hydrogen-powered trucks are not currently cost-competitive, while they might become competitive after 2030. The conclusion holds across truck types and sizes, hydrogen pathways, mission profiles, and countries. However, we find that there is still a huge area of uncertainty regarding the purchase price of hydrogen-powered trucks and the cost of hydrogen, which hampers the reliability of the results obtained. Various areas of methodological improvements are suggested. [ABSTRACT FROM AUTHOR]

According to standards, the harmonic content should be less than 5% at the time of calibration, while the calibration index proposed in this paper stipulates that the primary current amplitude of 1%~120% of the full range of the accuracy level reaches 0.05 S level. In view of the above problems and indexes, this paper adopts the active regulation technology of primary current; firstly, the harmonics of primary current are extracted, and then the opposite harmonic currents are injected by the penetrating wire to offset the harmonics, and finally, charged calibration is carried out. The inductive current transformer charged calibration device was first designed, and the particle swarm algorithm was used to optimize the offset performance of the key link of the background current offset suppression. The transfer function of the offset loop was derived, and it was theoretically analyzed that it can meet the offset requirements up to the 200th harmonic. The results show that the optimized calibration method can realize the full-range calibration of low-voltage inductive current transformers under charged conditions by making a prototype of the device and constructing a test circuit for experiments, and measuring the data and analyzing them. [ABSTRACT FROM AUTHOR]

This paper introduces a novel hybrid filter topology that combines passive and active components to enhance harmonic filtering and resonance damping in electrical power systems. The design integrates a three-phase two-level voltage-source converter with a double-tuned passive filter in parallel, significantly reducing the power rating and operational costs while maintaining good harmonic filtering performance and reactive current compensation. Double-tuned passive filters, compared to single-tuned ones, offer improved harmonic attenuation at multiple frequencies, enhancing overall system efficiency. Moreover, when used with the proposed hybrid filter topology, the double-tuned version allows for even lower dimensions of the active part, thereby further reducing system cost. A state-feedback controller is designed to enhance the performance of the hybrid filter, proving particularly effective in environments with complex impedance conditions. This paper also examines the impact of variations in passive component parameters, demonstrating the design's robustness against potential deviations expected over the operational lifespan. The results indicate that the hybrid filter effectively mitigates harmonics and maintains operational stability under various transient conditions, as confirmed by analytical and simulation studies on a real industrial network model. These findings underline the hybrid filter's potential to significantly improve power quality in modern electrical networks. [ABSTRACT FROM AUTHOR]

This paper is concerned with a hydraulic cylinder directly controlled by a variable speed motor-driven fixed-displacement pump. The considered configuration is referred to as a one-motor-one-pump (1M1P) motor-controlled hydraulic cylinder (MCC). A 1M1P MCC with a hydraulically driven passive load-holding function enabled by controlled system pressures is proposed. The proposed load-holding functionality works if there is a standstill command, a loss of power supply, or a hose rupture. Additionally, this paper conducts a comprehensive analysis of the proposed system's operation and load-holding function across four quadrants. The simulation results demonstrate four-quadrant operation and good load-holding performance under the aforementioned scenarios. In conclusion, the proposed 1M1P MCC can be successfully used on practical applications characterized by overrunning loads and four quadrant operation. [ABSTRACT FROM AUTHOR]

Municipal sewage sludge (MSS) is an inevitable byproduct of wastewater treatment, with increasing amounts year by year worldwide. The development of environmentally and economically acceptable methods for the sustainable management of MSS is a major environmental challenge. Nowadays, sludge management practices, besides the commonly used stabilization methods, focus attention on alternative sludge-disposal pathways, which encompass enhanced energy and valuable-resource recovery. This review presents the recent advances in the recovery of selected value-added products from sludge. Because of the high nitrogen and phosphorus concentrations, waste MSS can be a nutrient source (e.g., struvite). This paper discusses the conditions of and advances in the technology of struvite recovery. As in the extracellular polymeric substances (EPSs) of biological sludge, alginate-like exopolymers (ALEs) are present in MSS systems that treat municipal wastewater. The yields, dynamics in content, and characterization of ALEs and their possible applications were analyzed. MSS is an important source of humic substances. Their occurrence, characterization, and yields in various types of MSS (e.g., untreated, composted, and digested sludge) and main methods of application are presented. The important aspects and trends of MSS pyrolysis, including the thermochemical conversion to biochar, are discussed in this review. The characterization of biochar derived from MSS and the assessment of the environmental risks are also covered. This paper explores the potential use of biochar derived from MSS in various applications, including soil amendment, carbon sequestration, and environmental remediation. [ABSTRACT FROM AUTHOR]

The node pressure and flow rate along the shale gas flow process are analyzed according to the characteristics of the shale gas flow pipe network, and the non-leaking and leaking processes of the shale gas flow pipe network are modeled separately. The changes in pressure over time along each pipe segment in the network provide new ideas for identifying leaking pipe sections. This paper uses the logarithmic value of pressure as the basis for judging whether the flow pipe network is leaking or not, according to the process of varying flow parameters resulting in the regularity of leakage. A graph of the change in pressure of the pipe section after the leak compared to the pressure of the non-leaking section of pipe over time can be plotted, accurately identifying the specific section of pipe with the leak. The accuracy of this novel method is verified by the leakage section and statistical data of the shale gas pipeline network in situ used in this paper. [ABSTRACT FROM AUTHOR]

Aiming at the problem of source-load uncertainty caused by the increasing penetration of renewable energy and the large-scale integration of electric vehicles (EVs) into modern power system, a robust optimal operation scheduling algorithm for regional integrated energy systems (RIESs) with such uncertain situations is urgently needed. Based on this background, aiming at the problem of the irregular charging demand of EV, this paper first proposes an EV charging demand model based on the trip chain theory. Secondly, a multi-RIES optimization operation model including a shared energy storage station (SESS) and integrated demand response (IDR) is established. Aiming at the uncertainty problem of renewable energy, this paper transforms this kind of problem into a dynamic robust optimization with time-varying parameters and proposes an improved robust optimization over time (ROOT) algorithm based on the scenario method and establishes an optimal scheduling mode with the minimum daily operation cost of a multi-regional integrated energy system. Finally, the proposed uncertainty analysis method is verified by an example of multi-RIES. The simulation results show that in the case of the improved ROOT proposed in this paper to solve the robust solution of renewable energy, compared with the traditional charging load demand that regards the EVs as a whole, the EV charging load demand based on the trip chain can reduce the cost of EV charging by 3.5% and the operating cost of the multi-RIES by 11.7%. With the increasing number of EVs, the choice of the starting point of the future EV trip chain is more variable, and the choice of charging methods is more abundant. Therefore, modeling the charging demand of EVs under more complex trip chains is the work that needs to be studied in the future. [ABSTRACT FROM AUTHOR]

This paper presents a review of research progress on photovoltaic direct current arc detection based on VOSviewer bibliometric analysis. This study begins by introducing the basic concept and hazards of photovoltaic DC arcing faults, followed by a summary of commonly used arc detection techniques. Utilizing VOSviewer, the relevant literature is subjected to clustering and visualization analysis, offering insights into research hotspots, trends, and interconnections among different fields. Based on the bibliometric analysis method of VOSviewer software, this paper analyzes the articles published in the last 10 years (2014–2023) on photovoltaic DC fault diagnosis. We analyzed the specific characteristics of 2195 articles on arc failures, including year of publication, author, institution, country, references, and keywords. This study reveals the development trend, global cooperation model, basic knowledge, research hotspots, and emerging frontier of PV DC arc. Future research directions and development trends for photovoltaic DC arc detection are proposed which provides valuable references for further studies and applications in this domain. This comprehensive analysis indicates that photovoltaic DC arc detection technology is expected to find broader applications and greater promotion in the future. [ABSTRACT FROM AUTHOR]

Recent statistics indicate that as of 2023, the global renewable energy capacity has reached new heights, with Saudi Arabia significantly contributing to this growth through its strategic initiatives. The kingdom is particularly focusing on harnessing solar power, given its abundant sunlight, and is also exploring wind energy, leveraging its vast desert landscapes. These efforts are part of Saudi Arabia's broader strategy to become a global leader in renewable energy. This paper provides a detailed exploration of Saudi Arabia's ambitious journey from a fossil-fuel-dominated energy sector to a more sustainable, renewable-energy-driven future. Anchored in the broader context of global energy trends, the study emphasizes the critical shift toward renewable resources, with a particular focus on Saudi Arabia's unique position in this global movement. Key to this transition is Saudi Arabia's Vision 2030, a strategic framework that guides the country's renewable energy policies and initiatives. A comprehensive review of these policies, including other governmental and international collaborations that support renewable energy development, is offered. The current state of renewable energy in Saudi Arabia is assessed, including an overview of existing projects and production statistics. The paper also explores emerging technologies such as energy storage systems and smart grid solutions, emphasizing their role in Saudi Arabia's energy transition. An impact assessment is conducted to understand the environmental, economic, and social effects of this energy shift. The paper also includes a comparative analysis of other countries' renewable energy transitions, extracting lessons and best practices applicable to the Saudi context. Strategic recommendations and reflections on Saudi Arabia's future role in the global energy landscape are provided for stakeholders in energy policy, environmental planning, and sustainable development. [ABSTRACT FROM AUTHOR]

Isolated bidirectional DC–DC converters are becoming increasingly important in various applications, particularly in the electric vehicle sector, due to their ability to achieve bidirectional power flow and their safety features. This paper aims to review the switch strategies and topologies of isolated bidirectional DC–DC converters, with a specific focus on their applications in the field of electric vehicles. From the perspective of topology, PWM-type isolated bidirectional DC–DC converters, dual active bridge converters, and resonant-type isolated bidirectional DC–DC converters constitute the three main categories of these converters. The paper further examines the traditional switch strategies of these converters and discusses how specific switch technologies, such as single-phase shift, expanding-phase shift, double-phase shift, and triple-phase shift, can enhance the overall performance of isolated bidirectional DC–DC converters. The paper meticulously examines the characteristics of each topology and control scheme, as well as their typical use cases in practical applications. Particularly, the paper delves into the applications of isolated bidirectional DC–DC converters in the electric vehicle sector and draws conclusions regarding their potential and trends in future electric vehicle technology. [ABSTRACT FROM AUTHOR]

This paper presents a charging architecture for the Reconfigurable Cascaded Multilevel converter, which was specifically designed for electric vehicle (EV) powertrain applications. The RCMC topology is capable of executing power conversion and actively managing battery systems concurrently. The active battery management is achieved using the Reconfigurable Battery Module, which regulates the serial connection of cells via a switch pattern. In this paper, the RCMC is directly interfaced with an AC three-phase power system, facilitating the dynamic control over battery cells charging. Its inherent design allows for the implementation of various charging algorithms, customizable to specific requirements, without necessitating additional intermediary power stages. Firstly, an overview of the RCMC topology is given, and an analysis to define the optimal filter inductance is carried out. Subsequently, after the AC system characteristics are explained, two charging algorithms are presented and described: one prioritizes State of Charge (SOC) balancing among battery cells, while the other focuses on minimizing power losses. Moreover, a time estimation computation for the RCMC is carried out considering a two-level AC charging station. The result is compared with the time required for a conventional battery pack. The results show a reduction of 10 s in charging time for a mere 20% increase in SOC. Finally, the experimental setup is presented and used to validate the efficacy of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Many countries have a variety of offshore and onshore wind turbines that face extreme aging challenges. Issues with harmful vibrations that must be minimized are addressed in this paper. A new method of wind turbine tower vibration control using piezoelectricity and shunt circuits is proposed in this paper. The passive vibration control method is shown to improve the tower's structural performance under various environmental loads, like wind and seismic excitations. To examine the effectiveness of the suggested shunted piezoelectric system, a simple surrogate finite element model of a wind turbine tower is considered, and various investigations at the second eigenfrequency are carried out. An alternative way of modeling the studied structure is considered and the results demonstrate better performance. The advantages of setting up structural damping systems for decreasing tower vibrational loads and boosting their structural stability and resilience against extreme events are highlighted throughout this work. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV) swarms serve as a dynamic platform for diverse missions, including communication relays, search and rescue operations, and environmental monitoring. The success of these operations crucially depends on the resilience of their electrical support systems, especially in terms of battery management. This paper examines the reliability of electrical support for UAV swarms engaged in missions that require prioritization into high and low categories. The paper proposes a dynamic resource allocation strategy that permits the flexible reassignment of drones across different-priority tasks, ensuring continuous operation while optimizing resource use. By leveraging the Markov chain theory, an analytical model for the evaluation of the resilience of the battery management system under different operational scenarios was developed. The paper quantitatively assesses the impact of different operational strategies and battery management approaches on the overall system resilience and mission efficacy. This approach aims to ensure uninterrupted service delivery for critical tasks while optimizing the overall utilization of available electrical resources. Through modeling and analytical evaluations, the paper quantifies the impact of various parameters and operating strategies on overall system resilience and mission availability, considering the utilization strategies of batteries and their reliability and maintenance metrics. The developed models and strategies can inform the development of robust battery management protocols, resource allocation algorithms, and mission planning frameworks, ultimately enhancing the operational availability and effectiveness of UAV swarms in critical special missions. [ABSTRACT FROM AUTHOR]

The licensing of new reactors implies the use of verified and validated neutronic codes. Numerical validation can rely on sensitivity and uncertainty studies, but they require repeated execution of time-consuming neutron flux and depletion calculations. The computational costs can be reduced by using perturbation theories. However, the uncoupled Depletion Perturbation Theory is restricted to single integral values such as nuclide density. Relying on reduced-basis approaches, which reconstruct all nuclide densities at once, is one way to get around this restriction. Furthermore, the adjoint-based reduced-order model uses the direct and adjoint equations for projection. For diffusion or transport calculations, the Exact-to-Precision Generalized Perturbation Theory was developed. Still, no models for depletion calculations are readily available. Therefore, this paper describes a novel adjoint-based reduced-order model for the Bateman Equation. It uses a range-finding algorithm to create the basis and the uncoupled Depletion Perturbation Theory for the reconstruction of the first order replaced by with a first order formulation. Our paper shows that for several perturbed cases, the depletion reduced-order model successfully reconstructs the nuclide densities. As a result, this serves as a proof of concept for our adjoint-based reduced-order model, which can perform sensitivity and uncertainty burn-up analysis in a shorter time. [ABSTRACT FROM AUTHOR]

This paper presents a thorough examination of methane capture from Polish coal mines, contextualized within the framework of the European Union's (EU) climate policy objectives. Through a strategic analysis encompassing the interior of coal mines, the surrounding environment, and the macro environment, this study elucidates the complex dynamics involved in methane emissions and capture initiatives. The key findings include a declining trend in absolute methane emissions since 2008, despite fluctuations in coal extraction volumes, and a relatively stable level of methane capture exceeding 300 million m3/year since 2014. The analysis underscores the critical role of government support, both in terms of financial incentives and streamlined regulatory processes, to facilitate the integration of methane capture technologies into coal mining operations. Collaboration through partnerships and stakeholder engagement emerges as essential for overcoming resource competition and ensuring the long-term success of methane capture projects. This paper also highlights the economic and environmental opportunities presented by methane reserves, emphasizing the importance of investment in efficient extraction technologies. Despite these advancements, challenges persist, particularly regarding the low efficiency of current de-methanation technologies. Recommendations for modernization and technological innovation are proposed to enhance methane capture efficiency and utilization. [ABSTRACT FROM AUTHOR]

In this paper, the notion of a cohesive and self-sufficient grid is proposed. Based on a cohesive and self-sufficient virtual microgrid, an active distribution network is optimally planned, and an optimal configuration of demand-side resources, distributed generations, and energy storage systems are generated. To cope with stochastic uncertainty from forecast error in wind speed and load, flexibility reserves are needed. In this paper, the supply relation between flexibility and uncertainty is quantified and integrated in an innovative index which is defined as cohesion. The optimization objectives are a minimized operational cost and system net-ability cohesion as well as self-sufficiency, which is defined as the abilities both to supply local load and to deal with potential uncertainty. After testing the optimal configuration in the PG&E 69 bus system, it is found that with a more cohesive VM partition, the self-sufficiency of VMs is also increased. Also, a case study on uncertainty-caused system imbalance is carried out to show how flexibility resources are utilized in real-time operational balance. [ABSTRACT FROM AUTHOR]

This paper deals with the application of the Model Predictive Control (MPC) algorithm to the sensorless control of a Permanent Magnet Synchronous Motor (PMSM). The proposed estimation strategy, based on the unscented Kalman filter (UKF), uses only the measurement of the motor current for the online estimation of speed, rotor position and load torque. Information about the system state is fed into the MPC algorithm. The results verify the effectiveness and applicability of the proposed sensorless control technique. To demonstrate its real-world applicability, implementation in low-speed direct drive astronomy telescope mount systems is investigated. The outcomes of the implementation are thoroughly examined, leading to insightful conclusions drawn from the observed results. Through rigorous theoretical analysis and extensive simulation studies, this paper establishes a solid foundation for the proposed sensorless control technique. The results obtained from simulation studies and real-world applications underscore the efficacy and versatility of the proposed approach, offering valuable insights for the advancement of sensorless control strategies in motor applications. The main aim of this work is to demonstrate and validate the practical feasibility of combining two complex techniques, establishing that such an integration is not only possible but also effective in achieving the desired objectives. [ABSTRACT FROM AUTHOR]

A correction notice has been issued for a research paper on electricity-generation technologies in West Texas. The correction addresses a minor mistake in the modeling of Battery Energy Storage Systems (BESS). The correction does not change the overall conclusions of the research, but it slightly alters the ranking of impacts associated with wind and solar generation facilities when BESS is added. The corrected figures and tables have been provided, along with additional information from another study on power generation systems. The paper includes tables comparing the environmental impact of solar PV + BESS generation, including data on various impact pathways. The authors express gratitude to those who provided feedback and support for the project. [Extracted from the article]

In the context of China's new power system, various regions have implemented policies mandating the integration of new energy sources with energy storage, while also introducing subsidies to alleviate project cost pressures. Currently, there is a lack of subsidy analysis for photovoltaic energy storage integration projects. In order to systematically assess the economic viability of photovoltaic energy storage integration projects after considering energy storage subsidies, this paper reviews relevant policies in the Chinese photovoltaic energy storage market. It analyzes the cost and revenue composition of photovoltaic energy storage integration projects, and constructs a system dynamics model for the levelized cost of electricity (LCOE) of such projects. Taking a specific photovoltaic energy storage project as an example, this paper measures the levelized cost of electricity and the investment return rate under different energy storage scenarios. Combining energy storage allocation ratios and internal rate of return indicators, this paper analyzes the net present value of photovoltaic energy storage integration projects under different subsidy standards. The results indicate that, while the current energy storage subsidy policies positively stimulate photovoltaic energy storage integration projects, they exhibit a limited capacity to cover energy storage investment costs, thereby failing to incentivize capital market participation in the construction of such projects. Rational allocation of energy storage capacity and optimization of corresponding subsidy policies are crucial prerequisites for enhancing the economic viability and widespread adoption of photovoltaic energy storage integration projects. This study not only aids in investment decision making for photovoltaic power stations but also contributes to the formulation of energy storage subsidy policies. [ABSTRACT FROM AUTHOR]

With the rapid development of renewable energy and the increasing maturity of energy storage technology, microgrids are quickly becoming popular worldwide. The stochastic scheduling problem of microgrids can increase operational costs and resource wastage. In order to reduce operational costs and optimize resource utilization efficiency, the real-time scheduling of microgrids becomes particularly important. After collecting extensive data, reinforcement learning (RL) can provide good strategies. However, it cannot make quick and rational decisions in different environments. As a method with generalization ability, meta-learning can compensate for this deficiency. Therefore, this paper introduces a microgrid scheduling strategy based on RL and meta-learning. This method can quickly adapt to different environments with a small amount of training data, enabling rapid energy scheduling policy generation in the early stages of microgrid operation. This paper first establishes a microgrid model, including components such as energy storage, load, and distributed generation (DG). Then, we use a meta-reinforcement learning framework to train the initial scheduling strategy, considering the various operational constraints of the microgrid. The experimental results show that the MAML-based RL strategy has advantages in improving energy utilization and reducing operational costs in the early stages of microgrid operation. This research provides a new intelligent solution for microgrids' efficient, stable, and economical operation in their initial stages. [ABSTRACT FROM AUTHOR]

Low carbon operation of power systems is a key way to achieve the goal of energy power carbon peaking and carbon neutrality. In order to promote the low carbon transition of energy and power and the coordinated and optimized operation of distributed energy sources in virtual power plants (VPP), this paper proposes a framework for collaborative utilization of pumped storage–carbon capture–power-to-gas (P2G) technologies. It also constructs a multi-time scale low carbon economic dispatch model for VPP to minimize the internal resource operation cost of VPP in each time period. During the intraday scheduling stage, the day-ahead scheduling results as the planned output and the energy flow is then dynamically corrected at a short-term resolution in the framework. This allows for the exploration of the low-carbon potential of each aggregation unit within the virtual power plant. The results of the simulation indicate that the strategy and model proposed in this paper can effectively encourage the consumption of renewable energy sources, promote the low-carbon operation of power system power, and serve as a valuable reference for the low-carbon economic operation of the power system. [ABSTRACT FROM AUTHOR]

Since power transformers are the most important pieces of equipment in electricity transmission and distribution systems, special attention must be paid to their maintenance in order to keep them in good condition for a long time. This paper reviews the main steps in the process of diagnosing the health of power transformer insulation, which involves the science of analysing the gases dissolved in power transformer oil for effective identification of faults. An accurate diagnosis of incipient faults is favourable to sustainable development and necessary to maintain a reliable supply of electricity. The methods presented for fault diagnosis in mineral-oil-immersed power transformers are divided into analytical and graphical methods and have been found to be simple, economical and effective. After describing the methods, both their strengths and weaknesses were identified, and over the years, the methods were complemented to provide highly accurate information, validated by field inspections. This paper focuses on practical information and applications to manage maintenance based on accurate and up-to-date data. The contents of this paper will be of particular use to engineers who manufacture, monitor and/or use high-power transformers in the energy sector, as well as to undergraduate, master's and PhD students interested in such applications. [ABSTRACT FROM AUTHOR]

To improve the power generation efficiency of offshore wind turbines and address the problem of high fire monitoring and warning costs, we propose a data-driven fire warning method based on transfer learning for wind turbines in this paper. This paper processes wind turbine operation data in a SCADA system. It uses an extreme gradient-boosting tree (XGBoost) algorithm to build an offshore wind turbine unit fire warning model with a multiparameter prediction function. This paper selects some parameters from the dataset as input variables for the model, with average cabin temperature, average outdoor temperature, average cabin humidity, and average atmospheric humidity as output variables. This paper analyzes the distribution information of input and output variables and their correlation, analyzes the predicted difference, and then provides an early warning for wind turbine fires. This paper uses this fire warning model to transfer learning to different models of offshore wind turbines in the same wind farm to achieve fire warning. The experimental results show that the prediction performance of the multiparameter is accurate, with an average MAPE of 0.016 and an average RMSE of 0.795. It is better than the average MAPE (0.051) and the average RMSE (2.020) of the prediction performance of a backpropagation (BP) neural network, as well as the average MAPE (0.030) and the average RMSE (1.301) of the prediction performance of random forest. The transfer learning model has good prediction performance, with an average MAPE of 0.022 and an average RMSE of 1.469. [ABSTRACT FROM AUTHOR]

Hydrogen is a carbon-free energy source that can be obtained from various sources. The blending of hydrogen represents a transitional phase in the shift from natural gas systems to hydrogen-based systems. However, concerns about the safety implications of introducing hydrogen have led to extensive discussions. This paper utilizes Fluent 17.0 numerical simulation software to simulate the leakage of hydrogen-blended natural gas in a closed domestic kitchen and analyze the concentration distribution and its variation pattern after a leakage. An experimental platform is set up, and a mixture of nitrogen and helium gas is used as a substitute for hydrogen-blended natural gas for the simulations and experiments. The simulation results demonstrate that the leaked gas spreads and accumulates towards the top of the space, gradually filling the entire area as the leak persists. As the hydrogen content in the leaked gas increases, the dispersion capacity of the gas in the confined space also increases. Furthermore, as the flow rate of the leaked gas increases, the average concentration of the leaked gas rises, and the gas stratification in the confined kitchen diminishes. The concentration distribution observed in the experiments aligns with the simulation results. After establishing the feasibility conditions of the model, the dispersion of the hydrogen-blended natural gas in the kitchen is further simulated. The results suggest that blending hydrogen into the gas enhances the dispersion of the gas after a leak, leading to a wider distribution within the kitchen and an increased risk in the event of a leak. Additionally, this paper employs the CASD module of FLACS 11.0 software to construct a three-dimensional geometric model of the domestic kitchen for simulation studies on the explosion of hydrogen-blended natural gas in a confined space. By adjusting the hydrogen ratio in the combustible gases present in the space and examining the variations in hydrogen concentration and external conditions, such as opening or closing the door, the influence on parameters including the peak explosion pressure, explosion overpressure, explosion flame temperature, and explosion response time are examined. Furthermore, the extent of the explosion area is determined, and the effect of hydrogen on the blast is clarified. [ABSTRACT FROM AUTHOR]

The performance of the Plate Indirect Evaporative Cooler (PIEC) can be effectively improved by incorporating baffles in the dry channel. However, in the dimensional influence of the baffles on PIEC performance there remains a research gap. In order to investigate the impact of baffle dimensions on the wet bulb efficiency, namely the average heat transfer coefficient and the cooling capacity of the PIEC, this paper proposed and verified a three-dimensional numerical model and method based on the species transport model and the Euler wall film model. At the same time, in order to obtain the equilibrium point between the enhanced heat transfer performance and the additional resistance induced by baffles, a comprehensive performance evaluation index is introduced. The results indicate that, under the same conditions, (1) the baffle effect on PIEC performance is significant at a lower inlet air velocity, and the wet bulb efficiency of the PIEC with baffles can be improved by 22.8%; (2) the baffle effect on PIEC performance is negative if its relative length exceeds 60% or the primary air inlet velocity surpasses 4 m/s under the conditions specified in this paper; and (3) the baffle effect on PIEC performance is significant when its channel height is lower and its channel width is larger, and the wet bulb efficiency of the PIEC with baffles can be improved by 29.3%. [ABSTRACT FROM AUTHOR]