mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Review of multi-objective optimization in long-term energy system models

Modeling and optimizing long-term energy systems can provide solutions to various energy and environmental policies involving public-interest issues.The conventional optimization of long-term energy system models focuses on a single economic goal.However,the increasingly complex demands of energy systems necessitate the comprehensive consideration of multiple dimensional objectives,such as environmental,social,and energy security.Therefore,a multiobjective optimization of long-term energy system models has been developed.Herein,studies pertaining to the multiobjective optimization of long-term energy system models are summarized;the optimization objectives of long-term energy system models are classified into economic,environmental,social,and energy security aspects;and the multi-objective optimization methods are classified and explained based on the preferential expression of decision makers.Finally,the key development direction of the multi-objective optimization of energy system models is discussed.
Research on intelligent recognition method for self-blast state of glass insulator based on mixed data augmentation

Automatically and accurately detecting the self-blast state of glass insulators is of great significance to operation and maintenance of transmission lines. To solve the shortcomings of the existing open-loop cognitive models to detect the self-blast state of glass insulators, this study explores a mixed data augmentation-based intelligent recognition method to detect the self-blast state of the glass insulator, by imitating the human cognitive mode. Firstly, generative adversarial network is utilised to obtain the highquality generative self-blast samples of the glass insulator, and the non-generative data augmentation techniques is used to obtain rich sample features. Secondly, considering the characteristics of aerial images such as large scale variations, variable shooting angles and complex backgrounds, feature maps with strong semantics and adaptive multi-scale fusion are extracted using the feature pyramid network with adaptive hierarchy and the multi-deformable convolutional network. Then, the extracted feature maps are transmitted to a two-dimensional stochastic configuration network that can adaptively generate hidden nodes and basis functions so as to develop the self-blast state classification criteria with universal approximation capability. Thirdly, based on the generalised error and entropy theory, the semantic error entropy evaluation indices of recognition results are defined to evaluate in real time, the credibility of the uncertain recognition results for the self-blast state of the glass insulator. Then, based on transfer learning and the established self-optimising feedback mechanism for feature pyramid network, the self-optimising adjustment and reconstruction of the feature map space with strong semantics and multi-scale fusion and its classification criteria are realised. Finally, the stacking method is applied to integrate the recognition results of the feature pyramid network with adaptive hierarchy and multi-channel deformable convolutional networks to improve the robustness of the recognition model. Results of experimental comparison with other machine learning and deep learning methods verify the feasibility and effectiveness of the proposed method.
A passive optical fibre sensor based on Fabry-Perot interferometry for bipolar electrostatic monitoring of insulating dielectrics

The measurement of the surface charge on the insulating dielectrics is critical to estimate the insulation strength of electrical equipment in operation. Unavoidable interactions with the electromagnetic field, however, generally result in distortion measurement of active sensor. Thus, it is of great significance to investigate a passive sensor for monitoring the deposited charge. Here, a passive optical fibre electrostatic sensor is developed on the principle of Fabry-Perot interference to quantify the surface potential of the insulating dielectrics. The sensitivity of quantifying the electrostatic charge is explored in terms of the wavelength shift in the interference spectrum, and the linear correlation is 0.99. Meanwhile, the sensor can identify a negative quadratic trend with the increase of the surface roughness of the insulating dielectrics. The merits of the proposed sensor such as passive monitoring, bipolar electrostatic detection, and the excellent ability of antielectromagnetic interference are highlighted in the results. Hence, this sensor can serve as an effective tool to monitor the electrostatic charge in the fields of smart electrical equipment, fuel transportation, aerospace, integrate circuit etc.
Electrical treeing behaviours in cross-linked polyethylene cables after thermal ageing

Long-term thermal ageing might have impacts on the physicochemical properties of cross-linked polyethene (XLPE) cables, thereby influencing their electrical behaviours, such as electrical treeing initiation and growth. The main objective of this work is to report the effects of thermal ageing on the electrical treeing behaviours (initiation and growth) in XLPE cable insulation. For this purpose, the electrical treeing initiation and growth test were performed in accelerated thermal samples. In addition, Differential Scanning Calorimetry and Fourier Transform Infrared Spectroscopy were utilised to investigate corresponding changes in the microstructures of materials. In addition, a correlation was established between electrical treeing behaviours and physicochemical properties during the thermal ageing process. Test results indicate that the thermal ageing process should be divided into three phases, and the re-crystallisation reaction is considered the primary reason for the increase of average electrical tree initiation voltage (AETIV). Furthermore, the thermal ageing index Xc is correlated to AETIV and the propagation rate of the electrical tree. As equivalent relationships have been established between the relative decrease value w of indexes AETIV, the propagating rate and Xc, this method can be employed to predict the changing pattern of electrical treeing initiation voltage and the propagating rate in future research.
Non-linear electrical conductivity of ethylene-propylene-diene monomer-based composite dielectrics by tuning inorganic fillers

In this study, three kinds of inorganic fillers are chosen and filled into ethylene-propylenediene monomer (EPDM) matrix, including silicon carbide, copper calcium titanate (CCTO), and vanadium dioxide (VO_2). The electrical properties of the three modified composites at different temperatures have been systematically studied. The intrinsic conductance behaviours of different inorganic fillers on the direct current conductance and electric breakdown strength of the composite dielectrics are also analysed, and the possible mechanism for non-linear conductivity is revealed. The electrical conductivity increases with the increase of fillers content, where 30 wt.% CCTO/EPDM composite dielectric has a high non-linear coefficient of 5.71. The increase in temperature can further increase the conductivity of the composites, accompanying a lower breakdown strength. When the temperature rises to 70°C, the VO_2/EPDM composite has a higher conductivity, but the electric breakdown strength degrades seriously. The simulation results show that the composites with non-linear electrical conductivity characteristics can effectively uniform the electric field and solve the problem of electric field concentration at the root of the stress cone, which is beneficial to improving the safe operation of the cable accessories.
Dual-salt assisted synergistic synthesis of Prussian white cathode towards high-capacity and long cycle potassium ion battery

Prussian blue analogues(PBAs)are considered as superior cathode materials for potassium-ion batteries(PIBs)because of their three-dimensional open framework structure, high stability, and low cost. However, the intrinsic lattice defects and low potassium content typically results in poor rate and cycling performance, thus limited their practical applications. In this work, high-quality K_(1.64)FeFe(CN)_6(PW-HQ)material with less crystalline water(6.21%)and high potassium content(1.64 mol~(-1))was successfully synthesized by a novel coprecipitation method with potassium citrate(K-CA)and potassium chloride(KCl)addition. Specifically, the electrode delivers a reversible capacity of 113.1 mA h g~(-1) at the current rate of 50 mA g~(-1) with -100% coulombic efficiency. Besides, the electrode retained 90% reversible capacity at 500 mA g~(-1) current density after 1000 cycles, indicating only 0.01% capacity decay per cycle. Moreover, we have revealed that the introduction of K-CA controlled the chelating rate of Fe(II)and the addition of KCl increased the K~+ content, hence improving the capacity and stability of the asprepared electrodes. Structural evolution and potassium storage mechanism were further investigated by detailed ex-situ X-ray diffraction and in-situ Raman measurements, which demonstrated reversible potassiation/depotassiation behavior and negligible volume change during the electrochemical process. In general, this work provides an efficient strategy to eliminate water contents in Prussian blue cathode and improve its electrochemical performance, which plays a key role in promoting the industrialization of potassium ion batteries.
Long cycle performance of NC@VN/MnO cathode for AZIBs based on Mn/V relay type collaboration

Aqueous zinc ion batteries(AZIBs)have received great attention because of their non-toxicity, high safety, low cost, high abundance, and high specific power. However, their specific capacity is still low compared with lithium ion battery, and current academic research interesting has been focused on developing new cathode materials with high specific capacity. In this study, a Mn/V hybrid polymer framework is designed by a simple self-polymerization scheme. During subsequent calcination, ultrafine VN quantum dots and MnO nanoparticles are generated in situ and stably encapsulated inside N-doped carbon(NC)shells to obtain a novel hybrid cathode NC@VN/MnO for AZIBs. According to the density functional theory(DFT)calculation, the hybrids of MnO and VN can generate both interfacial effects and built-in electric fields that significantly accelerate ion and electron transport by tuning the intrinsic electronic structure, thus enhancing electrochemical performance. A synergistic strategy of composition and structural design allows the rechargeable AZIBs to achieve low-cost and excellent long-cycle performance based on a relay type collaboration at different cycling stages. Consequently, the NC@VN/MnO cathode has output a capacity of 108.3 mA h g~(-1) after 12,000 cycles at 10 A g~(-1). These results clearly and fully demonstrate the advantages of the hybrid cathode NC@VN/MnO.
Edge atomic Fe sites decorated porous graphitic carbon as an efficient bifunctional oxygen catalyst for Zinc-air batteries

The development of advanced bifunctional oxygen electrocatalysts for oxygen reduction and evolution reactions(ORR and OER)is critical to the practical application of zinc-air batteries(ZABs). Herein, a silica-assisted method is reported to integrate numerous accessible edge Fe-Nx sites into porous graphitic carbon(named Fe-N-G)for achieving highly active and robust oxygen electrocatalysis. Silica facilitates the formation of edge Fe-Nx sites and dense graphitic domains in carbon by inhibiting iron aggregation. The purification process creates a well-developed mass transfer channel for Fe-N-G. Consequently, Fe-N-G delivers a half-wave potential of 0.859 V in ORR and an overpotential of 344 mV at 10 mA cm~(-2) in OER. During long-term operation, the graphitic layers protect edge Fe-Nx sites from demetallation in ORR and synergize with FeOOH species endowing Fe-N-G with enhanced OER activity. Density functional theory calculations reveal that the edge Fe-Nx site is superior to the in-plane Fe-Nx site in terms of OH* dissociation in ORR and OOH* formation in OER. The constructed ZAB based on Fe-N-G cathode shows a higher peak power density of 133 mW cm~(-2) and more stable cycling performance than Pt/C + RuO_2 counterparts. This work provides a novel strategy to obtain high-efficiency bifunctional oxygen electrocatalysts through space mediation.
Depleted uranium oxide supported nickel catalyst for autothermal CO_2 methanation in non-adiabatic reactor under induction heating

Undoped nickel-based catalysts supported on depleted uranium oxide allow one to carry out CO_2 methanation process under extremely low reaction temperature under atmospheric pressure and powered by a contactless induction heating.By adjusting the reaction conditions,the catalyst is able to perform CO_2 methanation reaction under autothermal process operated inside a non-adiabatic reactor,without any external energy supply.Such autothermal process is possible thanks to the high apparent density of the UOx which allows one to confine the reaction heat in a small catalyst volume in order to confine the exothermicity of the reaction inside the catalyst and to operate the reaction at equilibrium heat in-heat out.Such autothermal operation mode allows one to significantly reduce the complexity of the process compared to that operated using adiabatic reactor,where complete insulation is required to prevent heat disequilibrium,in order to reduce as much as possible,the heat exchange with the external medium.The catalyst displays an extremely high stability as a function of time on stream as no apparent deactivation.It is expected that such new catalyst with unprecedented catalytic performance could open new era in the field of heterogeneous catalysis where traditional supports show their limitations to operate catalytic processes under severe reaction conditions.
A Roadmap for Sustainable Agricultural Soil Remediation Under China's Carbon Neutrality Vision

Agricultural soil pollution is a major threat affecting soil health and the ability of soil to yield safe and sufficient food; thus, it is a barrier to the goal of zero hunger worldwide [1]. The food deficiency problem continues to grow, particularly under the current atmosphere of global tension. United Nations(UN)organizations, including the UN Environment Program(UNEP)and the Food Agricultural Organization(FAO), previously reached a consensus to ''Be the solution to soil pollution," which has contributed to raising global awareness of the threats posed by soil pollution. According to a national soil survey, millions of hectares of agricultural lands in China are affected by heavy metal(loid)pollution(e.g., cadmium(Cd), nickel(Ni), copper(Cu), and arsenic(As)), resulting in a loss of rice productivity exceeding 10 million tons per year [2]. China has already achieved a miracle in sustaining one quarter of the world's population with only 9% of the world's land in the past decades; however, soil pollution is becoming a new challenge in meeting the increasing demand for food in the 21st century. China's central government released an ambitious soil pollution prevention and control action plan in 2016 aimed at reversing the exacerbation of soil degradation. In contrast to the finely developed framework used in restoring industrial brownfield sites, agricultural soil remediation on such a large scale is unprecedented. During the period of China's 13th Five-Year Plan, pilot-scale demonstrations have been extensively implemented across the country, particularly in southern China, based on the national soil survey. Although a great deal of experience has been gained after a massive injection of funds, many fundamental engineering problems remain unresolved. Since China's new ''double carbon" goal(i.e., achieving a carbon peak and carbon neutrality)was proposed to cope with climate change, there has been a strong demand for integrating carbon neutrality with other targets in order to achieve harmony between state strategies [3]. In particular, a massive injection of energy and resources into the large area of agricultural soil remediation can significantly contribute to carbon emissions, which is unsustainable and unlikely. Agricultural land is considered to be an important component of carbon pools in the terrestrial system; thus, under proper regulation, it can contribute to carbon sequestration and fixation, thereby reversing the carbon flux.
Removable Dyes—The Missing Link for In-Depth N-Glycan Analysis via Multi-Method Approaches

As the roles of glycans in health and disease continue to be unraveled, it is becoming apparent that glycans’ immense complexity cannot be ignored. To fully delineate glycan structures, we developed an integrative approach combining a set of cost-effective, widespread, and easy-to-handle analytical methods. The key feature of our workflow is the exploitation of a removable fluorescent label—exemplified by 9-fluorenylmethyl chloroformate (Fmoc)—to bridge the gap between diverse glycoanalytical methods, especially multiplexed capillary gel electrophoresis with laser-induced fluorescence detection (xCGELIF) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS). Through the detailed structural analysis of selected, dauntingly complex N-glycans from chicken ovalbumin, horse serum, and bovine transferrin, we illustrate the capabilities of the presented strategy. Moreover, this approach "visualizes" N-glycans that have been difficult to identify thus far—such as the sulfated glycans on human immunoglobulin A—including minute changes in glycan structures, potentially providing useful new targets for biomarker discovery.
Prospects of CP violation in Λ decay with a polarized electron beam at the STCF

Based on 1.89×10~8J/Ψ→ΛΛ Monte Carlo(MC)events produced from a longitudinally-polarized electron beam, the sensitivity of the CP violation of Λ decay is studied using fast simulation software. In addition, the J/Ψ→ΛΛ decay can be used to optimize the detector response using the interface provided by the fast simulation software. In the future, the STCF is expected to obtain 3.4 trillion J/Ψ events, and the statistical sensitivity of the CP violation of Λ decay via the J/Ψ→ΛΛ process is expected to reach O(10~(-5))when the electron beam polarization is 80%.
Synchrophasor-based Online State Estimated in Large-scale Power Grid

With integration of a larger amount of clean power sources and power electronic equipment, operation and dynamic characteristics of the power grid are becoming more and more complicated and stochastic. Therefore, it is necessary and urgent to obtain accurate real-time states, which is difficult from traditional state estimation. This paper systematically develops a phasor measurement unit (PMU) based real-time state estimator for a realistic large-scale power grid for the first time. The estimator mainly relies on three refined algorithms, i.e., an improved linear state estimation algorithm, a practical bad data identification method and a distributed topology check technique. Furthermore, a novel system architecture is designed and implemented for the China Southern Power Grid. Numerical simulations and extensive field operation results of the state estimator recorded under both normal and abnormal situations are presented. All the tests and field results demonstrate the advantages of the proposed algorithms in terms of online system monitoring and feasibility of refreshing the states of the whole system at intervals of tens of milliseconds.
Optimal Allocation of Fault Current Limiter in MMC-HVDC Grid Based on Transient Energy Flow

Economical and reliable protection of DC-side shortcircuit faults has become a key technology for promoting the development of module multilevel converters based on the high voltage direct current grid (MMC-HVDC-Grid). The fault current limiter (FCL) can effectively suppress the rapid development of the fault current and reduce the current breaking capacity of the circuit breaker. In this paper, a method based on transient energy flow (TEF) analysis is proposed to optimize the allocation of a resistive and inductive FCL in the MMC-HVDC-Grid. In the proposed method, the electromagnetic TEF is measured first, and then, the TEF suppression rate and suppression efficiency are defined as optimization objectives, and the installation location of the FCL and its impedance parameters as optimization variables. To test the proposed method, two-terminal and four-terminal bipolar MMC-HVDC-Grids with single-pole-to-ground DC faults are modeled in the PSCAD/EMTDC so that the TEF data can be acquired. The optimal FCLs' location and parameter values are determined through investigating the evolution paradigm of TEF along with changes of the FCL position and parameters. The results prove that the selected parameters can effectively slow down the DC fault current rising rate, thus reducing the requirements on tripping current of the DC breakers.
Data-driven Reliability Assessment of an Electric Vehicle Penetrated Grid Utilizing the Diffusion Estimator and Slice Sampling

Due to the stochasticity of charging behaviors of electric vehicles (EVs), it is difficult to anticipate when charging load demand will be densely concentrated. If massive charging loads and the system peak profile appear at the same time, it may pose a risk to the reliable operation of power grids. For a system integrated with renewable energies, this risk can be much higher because of their unsteady power output. With load measurements more widely collected, this paper presents a data-driven framework to assess the reliability of a power grid considering charging EVs. Specifically, the diffusion estimator is firstly applied to estimate the probability density function of EV charging loads, which possesses both regional adaptivity and good boundary estimation performance. Then, charging load samples are produced through slice sampling. It is capable of sampling from irregularly-shaped distributions with high accuracy. The proposed approach is verified by the numerical results from the simulations on a modified IEEE 30-bus test system based on real measurement data.