Optimization and Innovation of the Operation Model of Mobile Social E-commerce under AI Empowerment:Taking the Female Community Platform“Little Red Book”as an Example

This article takes the female community platform“Little Red Book”as an example to explore the optimization and innovation of mobile community e-commerce operation mode under Artificial Intelligence(AI)empowerment.Firstly,the relevant concepts were defined,and then the unique attributes of mobile community e-commerce were analyzed.As a typical representative of mobile community e-commerce,Little Red Book introduces the background and characteristics of its platform,analyzes its mobile community operation mode,and focuses on exploring how to establish a mobile community e-commerce platform and effective operation mode under the empowerment of AI technology,to provide some reference and inspiration for the development and operation of Little Red Book and other e-commerce platform enterprises.

Traction power systems for electrified railways:evolution,state of the art,and future trends

Traction power systems(TPSs)play a vital role in the operation of electrified railways.The transformation of conventional railway TPSs to novel structures is not only a trend to promote the development of electrified railways toward high-efficiency and resilience but also an inevitable requirement to achieve carbon neutrality target.On the basis of sorting out the power supply structures of conventional AC and DC modes,this paper first reviews the characteristics of the existing TPSs,such as weak power supply flexibility and low-energy efficiency.Furthermore,the power supply structures of various TPSs for future electrified railways are described in detail,which satisfy longer distance,low-carbon,high-efficiency,high-reliability and high-quality power supply requirements.Meanwhile,the application prospects of different traction modes are discussed from both technical and economic aspects.Eventually,this paper introduces the research progress of mixed-system electrified railways and traction power supply technologies without catenary system,speculates on the future development trends and challenges of TPSs and predicts that TPSs will be based on the continuous power supply mode,employing power electronic equipment and intelligent information technology to construct a railway comprehensive energy system with renewable energy.

A Tutorial Review of the Solar Power Curve: Regressions, Model Chains, and Their Hybridization and Probabilistic Extensions

Owing to the persisting hype in pushing toward global carbon neutrality,the study scope of atmospheric science is rapidly expanding.Among numerous trending topics,energy meteorology has been attracting the most attention hitherto.One essential skill of solar energy meteorologists is solar power curve modeling,which seeks to map irradiance and auxiliary weather variables to solar power,by statistical and/or physical means.In this regard,this tutorial review aims to deliver a complete overview of those fundamental scientific and engineering principles pertaining to the solar power curve.Solar power curves can be modeled in two primary ways,one of regression and the other of model chain.Both classes of modeling approaches,alongside their hybridization and probabilistic extensions,which allow accuracy improvement and uncertainty quantification,are scrutinized and contrasted thoroughly in this review.

Zooplankton community response to eddy during dinoflagellate Noctiluca scintillans blooms off Pakistan,northern Arabian Sea

Eddies are major elements of ocean dynamics that affect ocean production.Understanding their effects on plankton distribution may help understand the dynamics of harmful phytoplankton blooms.Previous studies on the effects of eddies in the northern Arabian Sea have primarily focused on the zooplankton community,and few have observed zooplankton dynamics during winter blooms of Noctiluca scintillans.We investigated zooplankton community structure and the related environmental variability during a N.scintillans bloom that was affected by an eddy in February 2018.The sampling stations were deployed at eddy core and eddy edge distinguished in salinity,temperature,and velocity.Results show that N.scintillans bloomed at the eddy core with high-velocity currents induced by warm eddies that moved from eddy core to eddy edge.As a result,blooms significantly changed the zooplankton community structure.Non-bloom stations had higher zooplankton diversity than bloom stations.Zooplankton at non-bloom stations were dominated by either tunicates or copepods,such as Thalia democratica and Pleuromamma gracilis.In addition to the influence of N.scintillans blooms,the velocity of eddy currents was a crucial factor on the similarities in the zooplankton community composition between eddy edge and eddy core.Moreover,the lower abiotic factors in bloom area contribute to the structuring of the zooplankton community during N.scintillans blooms.

Dynamic analysis of major public health emergency transmission considering the dual-layer coupling of community–resident complex networks

We construct a dual-layer coupled complex network of communities and residents to represent the interconnected risk transmission network between communities and the disease transmission network among residents. It characterizes the process of infectious disease transmission among residents between communities through the SE2IHR model considering two types of infectors. By depicting a more fine-grained social structure and combining further simulation experiments, the study validates the crucial role of various prevention and control measures implemented by communities as primary executors in controlling the epidemic. Research shows that the geographical boundaries of communities and the social interaction patterns of residents have a significant impact on the spread of the epidemic, where early detection, isolation and treatment strategies at community level are essential for controlling the spread of the epidemic. In addition, the study explores the collaborative governance model and institutional advantages of communities and residents in epidemic prevention and control.

The Correlation between the Power Quality Indicators and Entropy Production Characteristics of Wind Power+Energy Storage Systems

Power quality improvements help guide and solve the problems of inefficient energy production and unstable power output in wind power systems.The purpose of this paper is mainly to explore the influence of different energy storage batteries on various power quality indicators by adding different energy storage devices to the simulated wind power system,and to explore the correlation between systementropy generation and various indicators,so as to provide a theoretical basis for directly improving power quality by reducing loss.A steady-state experiment was performed by replacing the wind wheel with an electric motor,and the output power qualities of the wind power systemwith andwithout energy storagewere compared and analyzed.Moreover,the improvement effect of different energy storage devices on various indicatorswas obtained.Then,based on the entropy theory,the loss of the internal components of the wind power system generator is simulated and explored by Ansys software.Through the analysis of power quality evaluation indicators,such as current harmonic distortion rate,frequency deviation rate,and voltage fluctuation,the correlation between entropy production and each evaluation indicator was explored to investigate effective methods to improve power quality by reducing entropy production.The results showed that the current harmonic distortion rate,voltage fluctuation,voltage deviation,and system entropy production are positively correlated in the tests and that the power factor is negatively correlated with system entropy production.In the frequency range,the frequency deviationwas not significantly correlated with the systementropy production.

Selection of media tools for community planning:A study from the perspective of communicative planning

In community planning,due to the lack of evidence regarding the selection of media tools,this study examines how a common but differentiated ideal speech situation can be created as well as how more appropriate media tools can be defined and selected in the community planning process.First,this study describes the concept and theoretical basis of media used in community planning from the perspectives of the multiple effects of media evolution on communicative planning.Second,the classification criteria and typical characteristics of media tools used to support community planning are clarified from three dimensions:acceptability,cost effectiveness,and applicability.Third,strategies for applying media tools in the four phases of communicative planning-namely,state analysis,problem identification,contradictory solution and optimization-are described.Finally,trends in the development of media tools for community planning are explored in terms of multistakeholder engagement,supporting scientific decision-making and multiple-type media integration.The results provide a reference for developing more inclusive,effective,and appropriate media tools for enhancing decision-making capacity and modernizing governance in community planning and policy-making processes.

Comparison of the Overall CO_(2) Emissions of Different Powertrain Systems Depending on the Energy Sector Emissions

A circular and sustainable economy for the private transport sector requires a holistic view of the emitted CO_(2) emissions.Looking at the energy supplied to the vehicle in terms of a circular economy leads to defossilisation.The remaining energy sources or forms are renewable electric energy,green hydrogen and renewable fuels.A holistic view of the CO_(2) emissions of these energy sources and forms and the resulting powertrain technologies must take into account all cradle-to-grave emissions for both the vehicle and the energy supply.In order to compare the different forms of energy,the three most relevant forms of powertrain technology are considered and a configuration is chosen that allows for an appropriate comparison.For this purpose,data from the FVV project“Powertrain 2040”are used[1]and combined with research data on the energy supply chain for passenger cars.The three comparable powertrain configurations are a battery electric vehicle,a fuel cell electric vehicle and an internal combustion engine hybrid vehicle fueled with electric fuel.First,the three selected powertrain configurations are presented in terms of their performance,weight,technology and other characteristics.A comparative analysis is carried out for different CO_(2) emissions of the electricity mix.The electricity mix is used for both the production of the vehicle and the energy.The results are presented in the form of cradle-to-wheel emissions,which consider the total CO_(2) emissions of the vehicle over its life cycle.Finally,the results are analyzed and discussed to determine which powertrain technology fits best into which energy sector CO_(2) emissions window.

Rolling Decision Model of Thermal Power Retrofit and Generation Expansion Planning Considering Carbon Emissions and Power Balance Risk

With the increasing urgency of the carbon emission reduction task,the generation expansion planning process needs to add carbon emission risk constraints,in addition to considering the level of power adequacy.However,methods for quantifying and assessing carbon emissions and operational risks are lacking.It results in excessive carbon emissions and frequent load-shedding on some days,although meeting annual carbon emission reduction targets.First,in response to the above problems,carbon emission and power balance risk assessment indicators and assessment methods,were proposed to quantify electricity abundance and carbon emission risk level of power planning scenarios,considering power supply regulation and renewable energy fluctuation characteristics.Secondly,building on traditional two-tier models for low-carbon power planning,including investment decisions and operational simulations,considering carbon emissions and power balance risks in lower-tier operational simulations,a two-tier rolling model for thermal power retrofit and generation expansion planning was established.The model includes an investment tier and operation assessment tier and makes year-by-year decisions on the number of thermal power units to be retrofitted and the type and capacity of units to be commissioned.Finally,the rationality and validity of the model were verified through an example analysis,a small-scale power supply system in a certain region is taken as an example.The model can significantly reduce the number of days of carbon emissions risk and ensure that the power balance risk is within the safe limit.

Research on the MPPT of Photovoltaic Power Generation Based on Improved WOA and P&O under Partial Shading Conditions

Partial shading conditions(PSCs)caused by uneven illumination become one of the most common problems in photovoltaic(PV)systems,which can make the PV power-voltage(P-V)characteristics curve show multi-peaks.Traditional maximum power point tracking(MPPT)methods have shortcomings in tracking to the global maximum power point(GMPP),resulting in a dramatic decrease in output power.In order to solve the above problems,intelligent algorithms are used in MPPT.However,the existing intelligent algorithms have some disadvantages,such as slow convergence speed and large search oscillation.Therefore,an improved whale algorithm(IWOA)combined with the P&O(IWOA-P&O)is proposed for the MPPT of PV power generation in this paper.Firstly,IWOA is used to track the range interval of the GMPP,and then P&O is used to accurately find the MPP in that interval.Compared with other algorithms,simulation results show that this method has an average tracking efficiency of 99.79%and an average tracking time of 0.16 s when tracking GMPP.Finally,experimental verification is conducted,and the results show that the proposed algorithm has better MPPT performance compared to popular particle swarm optimization(PSO)and PSO-P&O algorithms.

Increasing the Efficiency and Level of Environmental Safety of Pro-Environmental City Heat Supply Technologies by Low Power Nuclear Plants

In connection with the current prospect of decarbonization of coal energy through the use of small nuclear power plants (SNPPs) at existing TPPs as heat sources for heat supply to municipal heating networks, there is a technological need to improve heat supply schemes to increase their environmental friendliness and efficiency. The paper proves the feasibility of using the heat-feeding mode of ASHPs for urban heat supply by heating the network water with steam taken from the turbine. The ratio of electric and thermal power of a “nuclear” combined heat and power plant is given. The advantage of using a heat pump, which provides twice as much electrical power with the same heat output, is established. Taking into account that heat in these modes is supplied with different potential, the energy efficiency was used to compare these options. To increase the heat supply capacity, a scheme with the use of a high-pressure heater in the backpressure mode and with the heating of network water with hot steam was proposed. Heat supply from ASHPs is efficient and environmentally friendly even in the case of significant remoteness of heat consumers.

Two stages power generation test of the hot dry rock exploration and production demonstration project in the Gonghe Basin,northeastern Qinghai-Tibet plateau,China

The Hot Dry Rock(HDR)is considered as a clean and renewable energy,poised to significantly contribute to the global energy decarbonization agenda.Many HDR projects worldwide have accumulated valuable experience in efficient drilling and completion,reservoir construction,and fracture simulation.In 2019,China Geological Survey(CGS)initiated a demonstration project of HDR exploration and production in the Gonghe Basin,aiming to overcome the setbacks faced by HDR projects.Over the ensuing four years,the Gonghe HDR project achieved the first power generation in 2021,followed by the second power generation test in 2022.After establishing the primary well group in the initial phase,two directional wells and one branch well were drilled.Noteworthy progress was made in successfully constructing the targeted reservoir,realizing inter-well connectivity,power generation and grid connection,implementing of the real-time micro-seismic monitoring.A closed-loop technical validation of the HDR exploration and production was completed.However,many technical challenges remain in the process of HDR industrialization,such as reservoir fracture network characterization,efficient drilling and completion,multiple fracturing treatment,continuous injection and production,as well as mitigation of induced seismicity and numerical simulation technology.

Source-Load Coordinated Optimal Scheduling Considering the High Energy Load of Electrofused Magnesium and Wind Power Uncertainty

In fossil energy pollution is serious and the“double carbon”goal is being promoted,as a symbol of fresh energy in the electrical system,solar and wind power have an increasing installed capacity,only conventional units obviously can not solve the new energy as the main body of the scheduling problem.To enhance the systemscheduling ability,based on the participation of thermal power units,incorporate the high energy-carrying load of electro-melting magnesiuminto the regulation object,and consider the effects on the wind unpredictability of the power.Firstly,the operating characteristics of high energy load and wind power are analyzed,and the principle of the participation of electrofusedmagnesiumhigh energy-carrying loads in the elimination of obstructedwind power is studied.Second,a two-layer optimization model is suggested,with the objective function being the largest amount of wind power consumed and the lowest possible cost of system operation.In the upper model,the high energy-carrying load regulates the blocked wind power,and in the lower model,the second-order cone approximation algorithm is used to solve the optimizationmodelwithwind power uncertainty,so that a two-layer optimizationmodel that takes into account the regulation of the high energy-carrying load of the electrofused magnesium and the uncertainty of the wind power is established.Finally,the model is solved using Gurobi,and the results of the simulation demonstrate that the suggested model may successfully lower wind abandonment,lower system operation costs,increase the accuracy of day-ahead scheduling,and lower the final product error of the thermal electricity unit.

Transient AC Overvoltage Suppression Orientated Reactive Power Control of the Wind Turbine in the LCC-HVDC Sending Grid

High-voltage direct current(HVDC) transmission is a crucial way to solve the reverse distribution of clean energy and loads. The line commutated converter-based HVDC(LCCHVDC) has become a vital structure for HVDC due to its high technological maturity and economic advantages. During the DC fault of LCC-HVDC, such as commutation failure, the reactive power regulation of the AC grid always lags the DC control process, causing overvoltage in the AC sending grid, which brings off-grid risk to the wind power generation based on power electronic devices. Nevertheless, considering that wind turbine generators have fast and flexible reactive power control capability, optimizing the reactive power control of wind turbines to participate in the transient overvoltage suppression of the sending grid not only improves the operational safety at the equipment level but also enhances the voltage stability of the system. This paper firstly analyses the impact of wind turbine's reactive power on AC transient overvoltage. Then, it proposes an improved voltage-reactive power control strategy, which contains a reactive power control delay compensation and a power command optimization based on the voltage time series prediction. The delay compensation is used to reduce the contribution of the untimely reactive power of wind turbines on transient overvoltage, and the power command optimization enables wind turbines to have the ability to regulate transient overvoltage, leading to the variation of AC voltage, thus suppressing the transient overvoltage. Finally, the effectiveness and feasibility of the proposed method are verified in a ±800kV/5000MW LCC-HVDC sending grid model based on MATLAB/Simulink.

Review of Thermal Design of SiC Power Module for Motor Drive in Electrical Vehicle Application

In the current vehicle electric propulsion systems,the thermal design of power modules heavily relies on empirical knowledge,making it challenging to effectively optimize irregularly arranged Pinfin structures,thereby limiting their performance.This paper aims to review the underlying mechanisms of how irregularly arranged Pinfins influence the thermal characteristics of power modules and introduce collaborative thermal design with DC bus capacitor and motor.Literature considers chip size,placement,coolant flow direction with the goal of reducing thermal resistance of power modules,minimizing chip junction temperature differentials,and optimizing Pinfin layouts.In the first step,algorithms should efficiently generating numerous unique irregular Pinfin layouts to enhance optimization quality.The second step is to efficiently evaluate Pinfin layouts.Simulation accuracy and speed should be ensured to improve computational efficiency.Finally,to improve overall heat dissipation effectiveness,papers establish models for capacitors,motors,to aid collaborative Pinfin optimization.These research outcomes will provide essential support for future developments in high power density motor drive for vehicles.

The Burden of Undiagnosed Hypertension and Associated Risk Factors among Adults in a Rural Community in Imo Sate, South-East Nigeria

Background: Cardiovascular diseases are the leading cause of death globally and hypertension is a major contributor to this burden. Many people with hypertension have poorly controlled blood pressure and up to half of the adults with hypertension are unaware of their hypertensive status due to factors that bother on poor management and poor screening approaches. The implication is that people who have poor access to healthcare especially those in the rural communities are at increased risk of cardiovascular complications and all-cause mortality. Unfortunately, not much has been done to ascertain the burden of undiagnosed hypertension and associated risk factors in rural communities in Nigeria. Methods: We conducted a community-based cross-sectional study in a rural community in Imo State, Nigeria, on burden of undiagnosed hypertension with participants recruited via a multi-stage sampling method. An interviewer-administered questionnaire was used, and standardized instruments were applied to obtain, process and analyze the data. Tests of association between the independent variables and outcome were conducted using logistic regression. P-value of Results: A total of 380 adults participated in the study. The mean age was 44.2 years. The prevalence of undiagnosed hypertension was 35.8%. Logistic regression revealed that age, with the respondents in the age groups 26 - 35 years (OR = 10.647, 1.910 - 59.345, p-value = 0.007), 36 - 45 (OR = 3.680, 1.263 - 10.723, p-value = 0.017), 46 - 55 years (OR = 2.737, 1.114 - 6.727, p-value = 0.039), 56 - 65 years old (OR = 3.384, 1.610 - 7.115, p-value = 0.001);and being married (OR = 3.846, 1.118 - 13.233, p-value = 0.033), were independent risk factors for undiagnosed hypertension. Conclusion: The prevalence of undiagnosed hypertension in the rural population of South-East Nigeria is high. Younger age (26 - 35 years) had the highest odds of risk for occurrence of hypertension. Also being married was identified as a risk factor for undiagnosed hypertension.

Reinforcement Learning-Based Energy Management for Hybrid Power Systems:State-of-the-Art Survey,Review,and Perspectives

The new energy vehicle plays a crucial role in green transportation,and the energy management strategy of hybrid power systems is essential for ensuring energy-efficient driving.This paper presents a state-of-the-art survey and review of reinforcement learning-based energy management strategies for hybrid power systems.Additionally,it envisions the outlook for autonomous intelligent hybrid electric vehicles,with reinforcement learning as the foundational technology.First of all,to provide a macro view of historical development,the brief history of deep learning,reinforcement learning,and deep reinforcement learning is presented in the form of a timeline.Then,the comprehensive survey and review are conducted by collecting papers from mainstream academic databases.Enumerating most of the contributions based on three main directions—algorithm innovation,powertrain innovation,and environment innovation—provides an objective review of the research status.Finally,to advance the application of reinforcement learning in autonomous intelligent hybrid electric vehicles,future research plans positioned as“Alpha HEV”are envisioned,integrating Autopilot and energy-saving control.

Review of the Analysis and Suppression for High-frequency Oscillations of the Grid-connected Wind Power Generation System

High-frequency oscillation(HFO)of gridconnected wind power generation systems(WPGS)is one of the most critical issues in recent years that threaten the safe access of WPGS to the grid.Ensuring the WPGS can damp HFO is becoming more and more vital for the development of wind power.The HFO phenomenon of wind turbines under different scenarios usually has different mechanisms.Hence,engineers need to acquire the working mechanisms of the different HFO damping technologies and select the appropriate one to ensure the effective implementation of oscillation damping in practical engineering.This paper introduces the general assumptions of WPGS when analyzing HFO,systematically summarizes the reasons for the occurrence of HFO in different scenarios,deeply analyses the key points and difficulties of HFO damping under different scenarios,and then compares the technical performances of various types of HFO suppression methods to provide adequate references for engineers in the application of technology.Finally,this paper discusses possible future research difficulties in the problem of HFO,as well as the possible future trends in the demand for HFO damping.

International Competition and Cooperation of Artificial Intelligence from the Perspective of State-to-State Power Relations

2023 marks a key juncture for artificial intelligence(AI)to be deeply embedded in international relations.From a technical point of view,the rapid development of generative AI not only provides new carriers and capabilities for countries’foreign exchanges,but also brings new risks and challenges to national security.In terms of topics,AI has created a series of new agendas for international relations,such as security,ethics and development,which need to be accelerated under the framework of global governance.

Choice of the Best Production Prediction Model for the Zagtouli Solar Power Plant in Burkina-Faso

In this paper, we present a study on the prediction of the power produced by the 33 MWp photovoltaic power plant at Zagtouli in Burkina-Faso, as a function of climatic factors. We identified models in the literature, namely the Benchmark, input/output, Marion, Cristo-fri, Kroposki, Jones-Underwood and Hatziargyriou prediction models, which depend exclusively on environmental parameters. We then compared our linear model with these seven mathematical models in order to determine the most optimal prediction model. Our results show that the Hatziargyriou model is better in terms of accuracy for power prediction.