Research on Interpolation Method for Missing Electricity Consumption Data

Missing value is one of the main factors that cause dirty data.Without high-quality data,there will be no reliable analysis results and precise decision-making.Therefore,the data warehouse needs to integrate high-quality data consistently.In the power system,the electricity consumption data of some large users cannot be normally collected resulting in missing data,which affects the calculation of power supply and eventually leads to a large error in the daily power line loss rate.For the problem of missing electricity consumption data,this study proposes a group method of data handling(GMDH)based data interpolation method in distribution power networks and applies it in the analysis of actually collected electricity data.First,the dependent and independent variables are defined from the original data,and the upper and lower limits of missing values are determined according to prior knowledge or existing data information.All missing data are randomly interpolated within the upper and lower limits.Then,the GMDH network is established to obtain the optimal complexity model,which is used to predict the missing data to replace the last imputed electricity consumption data.At last,this process is implemented iteratively until the missing values do not change.Under a relatively small noise level(α=0.25),the proposed approach achieves a maximum error of no more than 0.605%.Experimental findings demonstrate the efficacy and feasibility of the proposed approach,which realizes the transformation from incomplete data to complete data.Also,this proposed data interpolation approach provides a strong basis for the electricity theft diagnosis and metering fault analysis of electricity enterprises.

Harnessing overlapped temperature-salinity gradient in solar-driven interfacial seawater evaporation for efficient steam and electricity generation

Solar-driven interfacial water evaporation(SIWE)offers a superb way to leverage concentrated solar heat to minimize energy dissipation during seawater desalination.It also engenders overlapped temperaturesalinity gradient(TSG)between water-air interface and adjacent seawater,affording opportunities of harnessing electricity.However,the efficiency of conventional SIWE technologies is limited by significant challenges,including salt passivation to hinder evaporation and difficulties in exploiting overlapped TSG simultaneously.Herein,we report self-sustaining hybrid SIWE for not only sustainable seawater desalination but also efficient electricity generation from TSG.It enables spontaneous circulation of salt flux upon seawater evaporation,inducing a self-cleaning evaporative interface without salt passivation for stable steam generation.Meanwhile,this design enables spatial separation and simultaneous utilization of overlapped TSG to enhance electricity generation.These benefits render a remarkable efficiency of90.8%in solar energy utilization,manifesting in co-generation of solar steam at a fast rate of 2.01 kg m^(-2)-h^(-1)and electricity power of 1.91 W m^(-2)with high voltage.Directly interfacing the hybrid SIWE with seawater electrolyzer constructs a system for water-electricity-hydrogen co-generation without external electricity supply.It produces hydrogen at a rapid rate of 1.29 L h^(-1)m^(-2)and freshwater with 22 times lower Na+concentration than the World Health Organization(WHO)threshold.

Electricity Carbon Quota Trading Scheme based on Certificateless Signature and Blockchain

The carbon tradingmarket can promote“carbon peaking”and“carbon neutrality”at low cost,but carbon emission quotas face attacks such as data forgery,tampering,counterfeiting,and replay in the electricity trading market.Certificateless signatures are a new cryptographic technology that can address traditional cryptography’s general essential certificate requirements and avoid the problem of crucial escrowbased on identity cryptography.However,most certificateless signatures still suffer fromvarious security flaws.We present a secure and efficient certificateless signing scheme by examining the security of existing certificateless signature schemes.To ensure the integrity and verifiability of electricity carbon quota trading,we propose an electricity carbon quota trading scheme based on a certificateless signature and blockchain.Our scheme utilizes certificateless signatures to ensure the validity and nonrepudiation of transactions and adopts blockchain technology to achieve immutability and traceability in electricity carbon quota transactions.In addition,validating electricity carbon quota transactions does not require time-consuming bilinear pairing operations.The results of the analysis indicate that our scheme meets existential unforgeability under adaptive selective message attacks,offers conditional identity privacy protection,resists replay attacks,and demonstrates high computing and communication performance.

Rational design of natural leather-based water evaporator for electricity generation and functional applications

In recent years,water evaporation-induced electricity has attracted a great deal of attention as an emerging green and renewable energy harvesting technology.Although abundant materials have been developed to fabricate hydrovoltaic devices,the limitations of high costs,inconvenient storage and transport,low environmental benefits,and unadaptable shape have restricted their wide applications.Here,an electricity generator driven by water evaporation has been engineered based on natural biomass leather with inherent properties of good moisture permeability,excellent wettability,physicochemical stability,flexibility,and biocompatibility.Including numerous nano/microchannels together with rich oxygen-bearing functional groups,the natural leather-based water evaporator,Leather_(Emblic-NPs-SA/CB),could continuously produce electricity even staying outside,achieving a maximum output voltage of∼3 V with six-series connection.Furthermore,the leather-based water evaporator has enormous potential for use as a flexible self-powered electronic floor and seawater demineralizer due to its sensitive pressure sensing ability as well as its excellent photothermal conversion efficiency(96.3%)and thus fast water evaporation rate(2.65 kg m^(−2)h^(−1)).This work offers a new and functional material for the construction of hydrovoltaic devices to harvest the sustained green energy from water evaporation in arbitrary ambient environments,which shows great promise in their widespread applications.

Analyzing the Wind-Dominant Electricity Market under Coexistence of Regulated and Deregulated Power Trading

Currently,both regulated and deregulated power trading exist in China’s power system,which has caused imbalanced funds in the electricity market.In this paper,a simulation analysis of the electricity market with wind energy resources is conducted,and the calculation methods of unbalanced funds are investigated systematically.In detail,the calculation formulas of unbalanced funds are illustrated based on their definition,and a two-track electricity market clearing model is established.Firstly,the concept of the dual-track system is explained,and the specific calculation formulas of various types of unbalanced funds are provided.Next,considering the renewable energy consumption,the market clearing model based on DC power flow is constructed and solved;by combining fitting methods of mid-and long-term curves,the unbalanced funds are calculated based on clearing results and formulas.

Optimizing Household Wastes (Rice, Vegetables, and Fruit) as an Environmentally Friendly Electricity Generator

The high consumption of electricity and issues related to fossil energy have triggered an increase in energy prices and the scarcity of fossil resources.Consequently,many researchers are seeking alternative energy sources.One potential technology,the Microbial Fuel Cell(MFC)based on rice,vegetable,and fruit wastes,can convert chemical energy into electrical energy.This study aims to determine the potency of rice,vegetable,and fruit waste assisted by Cu/Mg electrodes as a generator of electricity.The method used was a laboratory experiment,including the following steps:electrode preparation,waste sample preparation,incubation of the waste samples,construction of a reactor using rice,vegetable,and fruit waste as a source of electricity,and testing.The tests included measuring electrical conductivity,electric current,voltage,current density,and power density.Based on the test results,the maximum current and voltage values for the fruit waste samples were 5.53 V and 11.5 mA,respectively,with a current density of 2.300 mA/cm^(2) and a power density of 12.719 mW/cm^(2).The results indicate the potential for a future development.The next step in development involves determining the optimum conditions for utilizing of rice,vegetable,and fruit waste.The results of the electrical conductivity test on rice,vegetable,and fruit waste samples were 1.51,2.88,and 3.98 mS,respectively,with the highest electrical conductivity value found in the fruit waste sample.

Analysis of Electricity Consumption Pattern Clustering and Electricity Consumption Behavior

Studying user electricity consumption behavior is crucial for understanding their power usage patterns.However,the traditional clustering methods fail to identify emerging types of electricity consumption behavior.To address this issue,this paper introduces a statistical analysis of clusters and evaluates the set of indicators for power usage patterns.The fuzzy C-means clustering algorithm is then used to analyze 6 months of electricity consumption data in 2017 from energy storage equipment,agricultural drainage irrigation,port shore power,and electric vehicles.Finally,the proposed method is validated through experiments,where the Davies-Bouldin index and profile coefficient are calculated and compared.Experiments showed that the optimal number of clusters is 4.This study demonstrates the potential of using a fuzzy C-means clustering algorithmin identifying emerging types of electricity consumption behavior,which can help power system operators and policymakers to make informed decisions and improve energy efficiency.

Energy Storage Operation Modes in Typical Electricity Market and Their Implications for China

As the Chinese government proposes ambitious plans to promote low-carbon transition,energy storage will play a pivotal role in China’s future power system.However,due to the lack of a mature electricity market environment and corresponding mechanisms,current energy storage in China faces problems such as unclear operational models,insufficient cost recovery mechanisms,and a single investment entity,making it difficult to support the rapid development of the energy storage industry.In contrast,European and American countries have already embarked on certain practices in energy storage operation models.Through exploration of key issues such as investment entities,market participation forms,and cost recovery channels in both front and back markets,a wealth of mature experiences has been accumulated.Therefore,this paper first summarizes the existing practices of energy storage operation models in North America,Europe,and Australia’s electricity markets separately from front and back markets,finding that perfect market mechanisms and reasonable subsidy policies are among the main drivers for promoting the rapid development of energy storage markets.Subsequently,combined with the actual development of China’s electricity market,it explores three key issues affecting the construction of costsharing mechanisms for energy storage under market conditions:Market participation forms,investment and operation modes,and cost recovery mechanisms.Finally,in line with the development expectations of China’s future electricitymarket,suggestions are proposed fromfour aspects:Market environment construction,electricity price formation mechanism,cost sharing path,and policy subsidy mechanism,to promote the healthy and rapid development of China’s energy storage industry.

Simulation and Analysis of Cascading Faults in Integrated Heat and Electricity Systems Considering Degradation Characteristics

Cascading faults have been identified as the primary cause of multiple power outages in recent years.With the emergence of integrated energy systems(IES),the conventional approach to analyzing power grid cascading faults is no longer appropriate.A cascading fault analysis method considering multi-energy coupling characteristics is of vital importance.In this study,an innovative analysis method for cascading faults in integrated heat and electricity systems(IHES)is proposed.It considers the degradation characteristics of transmission and energy supply com-ponents in the system to address the impact of component aging on cascading faults.Firstly,degradation models for the current carrying capacity of transmission lines,the water carrying capacity and insulation performance of thermal pipelines,as well as the performance of energy supply equipment during aging,are developed.Secondly,a simulation process for cascading faults in the IHES is proposed.It utilizes an overload-dominated development model to predict the propagation path of cascading faults while also considering network islanding,electric-heating rescheduling,and load shedding.The propagation of cascading faults is reflected in the form of fault chains.Finally,the results of cascading faults under different aging levels are analyzed through numerical examples,thereby verifying the effectiveness and rationality of the proposed model and method.

Electricity as an Energy Vector: A Performance Comparison with Hydrogen and Biodiesel in Italy

This study presents a comparative analysis of electricity, hydrogen, and biodiesel as energy vectors, with a focus on powering an aluminum smelter in southern Italy. It evaluates these vectors in terms of efficiency, land requirements for carbon-neutral energy production, and capital expenditure, providing insights throughout the entire supply chain (upstream, midstream, and downstream) into their feasibility for industrial applications. The research reveals that biodiesel, despite being carbon neutral, is impractical due to extensive land requirements and lower efficiency if compared to other vectors. Hydrogen, downstream explored in two forms as thermal power generation and fuel cell technology, shows lower efficiency and higher capital expenditure compared to electricity. Additionally, green hydrogen production’s land requirements significantly exceed those of electricity-based systems. Electricity emerges as the most viable option, offering an overall higher efficiency, lower land requirements for its green production, and comparatively lower capital expenditure. The study’s findings highlight the importance of a holistic assessment of energy vectors, considering economic, environmental, and practical aspects along the entire energy supply chain, especially in industrial applications where the balance of these factors is crucial for long-term sustainability and feasibility. This comprehensive analysis provides valuable guidance for similar industrial applications, emphasizing the need for a balanced approach in the selection of energy vectors.

Valorization of Agricultural Residues for Hydrogen-Based Electricity Generation towards Circular Bioeconomy

Global crises, notably climate shocks, degraded ecosystems, and growing energy demand, enforce sustainable production and consumption pathways. A circular bioeconomy offers the opportunities to actualize resource and eco-efficiency enhancement, valorization of waste streams, reduction of fossil energy and greenhouse gas (GHG) emissions. Albeit biomass resources are a potential feedstock for bio-hydrogen (bio-H2) production, Ghana’s agricultural residues are not fully utilized. This paper examines the economic and environmental impact of bio-H2 electricity generation using agricultural residues in Ghana. The bio-H2 potential was determined based on biogas steam reforming (BSR). The research highlights that BSR could generate 2617 kt of bio-H2, corresponding to 2.78% of the global hydrogen demand. Yam and maize residues contribute 50.47% of the bio-H2 produced, while millet residues have the most negligible share. A tonne of residues could produce 16.59 kg of bio-H2 and 29.83 kWh of electricity. A total of 4,705.89 GWh of electricity produced could replace the consumption of 21.92% of Ghana’s electricity. The economic viability reveals that electricity cost is $0.174/kWh and has a positive net present value of $2135550609.45 with a benefit-to-cost ratio of 1.26. The fossil diesel displaced is 1421.09 ML, and 3862.55 kt CO2eq of carbon emissions decreased corresponding to an annual reduction potential of 386.26 kt CO2eq. This accounts for reducing 10.26% of Ghana’s GHG emissions. The study demonstrates that hydrogen-based electricity production as an energy transition is a strategic innovation pillar to advance the circular bioeconomy and achieve sustainable development goals.

基于区间毕达哥拉斯犹豫模糊熵和交叉熵的ELECTRE II决策方法

针对属性权重完全未知或部分已知,属性值为区间毕达哥拉斯犹豫模糊数的多属性决策问题,提出了基于区间毕达哥拉斯犹豫模糊熵和交叉熵的ELECTRE II法。首先给出区间毕达哥拉斯犹豫模糊数的区间形式的得分函数和精度函数,定义新的距离测度。然后基于区间毕达哥拉斯犹豫模糊数的模糊因子、直觉因子和幅度因子,给出熵和交叉熵公式,并证明其性质,提出了基于熵和交叉熵确定属性权重的方法。最后提出了区间毕达哥拉斯犹豫模糊环境下的改进的ELECTRE II法,利用综合优势值对方案进行排序,并通过算例和比较分析验证了该方法的可行性和有效性。

SOLIDWORKS Electrical在通过式脚踏封口机自动化改造设计中的应用

小型企业塑封工艺中通过式脚踏封口机应用广泛,但在塑封重型工件时,工人操作非常费力且次品率高,无法保障塑封质量,为此对其进行机构优化与软硬件设计自动化改造。利用SOLIDWORKS Electrical快速建立3D虚拟电气配盘与生成各类BOM清单,大大缩短了研发周期,安装人员还可以根据虚拟电气装配路径进行准确安装。最终设计出结构合理,满足生产工艺要求的自动化装置,企业以极少改造成本提质增效,为机电一体化装置自动化设计提供了一个高效开发途径。

A Review of Atmospheric Electricity Research in China from 2019 to 2022

Atmospheric electricity is composed of a series of electric phenomena in the atmosphere.Significant advances in atmospheric electricity research conducted in China have been achieved in recent years.In this paper,the research progress on atmospheric electricity achieved in China during 2019-22 is reviewed focusing on the following aspects:(1)lightning detection and location techniques,(2)thunderstorm electricity,(3)lightning forecasting methods and techniques,(4)physical processes of lightning discharge,(5)high energy emissions and effects of thunderstorms on the upper atmosphere,and(6)the effect of aerosol on lightning.

Evolutionary game-based optimization of green certificate-carbon emission right-electricity joint market for thermal-wind-photovoltaic power system

With the increasing proportion of renewable energy in the power market,the demands on government financial subsidies are gradually increasing.Thus,a joint green certificate-carbon emission right-electricity multi-market trading process is proposed to study the market-based strategy for renewable energy.Considering the commodity characteristics of green certificates and carbon emission rights,the dynamic cost models of green certificates and carbon rights are constructed based on the Rubinstein game and ladder pricing models.Furthermore,considering the irrational bidding behavior of energy suppliers in the actual electricity market,an evolutionary game based multi-market bidding optimization model is presented.Subsequently,it is solved using a composite differential evolutionary algorithm.Finally,the case study results reveal that the proposed model can increase profits and the consumption rate of renewable energy and reduce carbon emission.

Constructing Built-In Electric Fields with Semiconductor Junctions and Schottky Junctions Based on Mo-MXene/Mo-Metal Sulfides for Electromagnetic Response

The exploration of novel multivariate heterostructures has emerged as a pivotal strategy for developing high-performance electromagnetic wave(EMW)absorption materials.However,the loss mechanism in traditional heterostructures is relatively simple,guided by empirical observations,and is not monotonous.In this work,we presented a novel semiconductor-semiconductor-metal heterostructure sys-tem,Mo-MXene/Mo-metal sulfides(metal=Sn,Fe,Mn,Co,Ni,Zn,and Cu),including semiconductor junctions and Mott-Schottky junctions.By skillfully combining these distinct functional components(Mo-MXene,MoS_(2),metal sulfides),we can engineer a multiple heterogeneous interface with superior absorption capabilities,broad effective absorption bandwidths,and ultrathin matching thickness.The successful establishment of semiconductor-semiconductor-metal heterostructures gives rise to a built-in electric field that intensifies electron transfer,as confirmed by density functional theory,which collaborates with multiple dielectric polarization mechanisms to substantially amplify EMW absorption.We detailed a successful synthesis of a series of Mo-MXene/Mo-metal sulfides featuring both semiconductor-semiconductor and semiconductor-metal interfaces.The achievements were most pronounced in Mo-MXene/Mo-Sn sulfide,which achieved remarkable reflection loss values of-70.6 dB at a matching thickness of only 1.885 mm.Radar cross-section calculations indicate that these MXene/Mo-metal sulfides have tremendous potential in practical military stealth technology.This work marks a departure from conventional component design limitations and presents a novel pathway for the creation of advanced MXene-based composites with potent EMW absorption capabilities.

Improved YOLOv8n Model for Detecting Helmets and License Plates on Electric Bicycles

Wearing helmetswhile riding electric bicycles can significantly reduce head injuries resulting fromtraffic accidents.To effectively monitor compliance,the utilization of target detection algorithms through traffic cameras plays a vital role in identifying helmet usage by electric bicycle riders and recognizing license plates on electric bicycles.However,manual enforcement by traffic police is time-consuming and labor-intensive.Traditional methods face challenges in accurately identifying small targets such as helmets and license plates using deep learning techniques.This paper proposes an enhanced model for detecting helmets and license plates on electric bicycles,addressing these challenges.The proposedmodel improves uponYOLOv8n by deepening the network structure,incorporating weighted connections,and introducing lightweight convolutional modules.These modifications aim to enhance the precision of small target recognition while reducing the model’s parameters,making it suitable for deployment on low-performance devices in real traffic scenarios.Experimental results demonstrate that the model achieves an mAP@0.5 of 91.8%,showing an 11.5%improvement over the baselinemodel,with a 16.2%reduction in parameters.Additionally,themodel achieves a frames per second(FPS)rate of 58,meeting the accuracy and speed requirements for detection in actual traffic scenarios.

Research on the optimization strategy of customers’electricity consumption based on big data

Current power systems face significant challenges in supporting large-scale access to new energy sources,and the potential of existing flexible resources needs to be fully explored from the power supply,grid,and customer perspectives.This paper proposes a multi-objective electricity consumption optimization strategy considering the correlation between equipment and electricity consumption.It constructs a multi-objective electricity consumption optimization model that considers the correlation between equipment and electricity consumption to maximize economy and comfort.The results show that the proposed method can accurately assess the potential for electricity consumption optimization and obtain an optimal multi-objective electricity consumption strategy based on customers’actual electricity consumption demand.

Reliability evaluation of IGBT power module on electric vehicle using big data

There are challenges to the reliability evaluation for insulated gate bipolar transistors(IGBT)on electric vehicles,such as junction temperature measurement,computational and storage resources.In this paper,a junction temperature estimation approach based on neural network without additional cost is proposed and the lifetime calculation for IGBT using electric vehicle big data is performed.The direct current(DC)voltage,operation current,switching frequency,negative thermal coefficient thermistor(NTC)temperature and IGBT lifetime are inputs.And the junction temperature(T_(j))is output.With the rain flow counting method,the classified irregular temperatures are brought into the life model for the failure cycles.The fatigue accumulation method is then used to calculate the IGBT lifetime.To solve the limited computational and storage resources of electric vehicle controllers,the operation of IGBT lifetime calculation is running on a big data platform.The lifetime is then transmitted wirelessly to electric vehicles as input for neural network.Thus the junction temperature of IGBT under long-term operating conditions can be accurately estimated.A test platform of the motor controller combined with the vehicle big data server is built for the IGBT accelerated aging test.Subsequently,the IGBT lifetime predictions are derived from the junction temperature estimation by the neural network method and the thermal network method.The experiment shows that the lifetime prediction based on a neural network with big data demonstrates a higher accuracy than that of the thermal network,which improves the reliability evaluation of system.

Electrochemical anodic oxidation assisted fabrication of memristors

Owing to the advantages of simple structure,low power consumption and high-density integration,memristors or memristive devices are attracting increasing attention in the fields such as next generation non-volatile memories,neuromorphic computation and data encryption.However,the deposition of memristive films often requires expensive equipment,strict vacuum conditions,high energy consumption,and extended processing times.In contrast,electrochemical anodizing can produce metal oxide films quickly(e.g.10 s) under ambient conditions.By means of the anodizing technique,oxide films,oxide nanotubes,nanowires and nanodots can be fabricated to prepare memristors.Oxide film thickness,nanostructures,defect concentrations,etc,can be varied to regulate device performances by adjusting oxidation parameters such as voltage,current and time.Thus memristors fabricated by the anodic oxidation technique can achieve high device consistency,low variation,and ultrahigh yield rate.This article provides a comprehensive review of the research progress in the field of anodic oxidation assisted fabrication of memristors.Firstly,the principle of anodic oxidation is introduced;then,different types of memristors produced by anodic oxidation and their applications are presented;finally,features and challenges of anodic oxidation for memristor production are elaborated.