Review of Power Supply and Distribution Construction Technology for Highway Electromechanical Engineering

In recent years,China has made significant progress in the construction of highways,resulting in an improved highway network that has provided robust support for economic and social development.However,the rapid expansion of highway construction,power supply,and distribution has led to several challenges in mechanical and electrical engineering technology.Ensuring the safe,stable,and cost-effective operation of the power supply and distribution system to meet the diverse requirements of highway operations has become a pressing issue.This article takes an example of a highway electromechanical engineering power supply and distribution construction project to provide insight into the construction process of highway electromechanical engineering power supply and distribution technology.

Vulnerability Assessment of Distributed Load Shedding Algorithm for Active Distribution Power System Under Denial of Service Attack

In order to deal with frequency deviation andsupply-demand imbalance in active distribution power system, inthis paper a distributed under frequency load shedding (UFLS)strategy is proposed. Different from conventional centralizedUFLS schemes, no centralized master station gathering all thebuses’ information is required. Instead, each bus decides itsown load shedding amount by only relying on limited peer-topeer communication. However, such UFLS strategy may sufferfrom some unexpected cyber-attacks such as integrity attacksand denial of service (DoS) attack. The latter DoS attack aimsto degrade the system performance by jamming or breakingthe communication, which is of high probability to happen inpractical power system. To assess the vulnerability of proposeddistributed UFLS algorithm, the effect of DoS attack on distributed average consensus algorithm is theoretically derived,which indicates that the final consensus value can be estimatedby a given attack probability. It is also investigated that such DoSattack does harm to the load shedding amount and finally affectsthe system frequency performance in the active distributionpower system. Several case studies implemented on an IEEE33-bus active distribution power system are conducted to verifythe effectiveness of the theoretical findings and investigate thevulnerability of the considered power system.

Research on Coordinated Development and Optimization of Distribution Networks at All Levels in Distributed Power Energy Engineering

The uncertainty of distributed generation energy has dramatically challenged the coordinated development of distribution networks at all levels.This paper focuses on the multi-time-scale regulation model of distributed generation energy under normal conditions.The simulation results of the example verify the self-optimization characteristics and the effectiveness of real-time dispatching of the distribution network control technology at all levels under multiple time scales.

Operation Control Method of Relay Protection in Flexible DC Distribution Network Compatible with Distributed Power Supply

A novel operation control method for relay protection in flexible DC distribution networks with distributed power supply is proposed to address the issue of inaccurate fault location during relay protection,leading to poor performance.The method combines a fault-tolerant fault location method based on long-term and short-term memory networks to accurately locate the fault section.Then,an operation control method for relay protection based on adaptive weight and whale optimization algorithm(WOA)is used to construct an objective function considering the shortest relay protection action time and the smallest impulse current.The adaptive weight and WOA are employed to obtain the optimal strategy for relay protection operation control,reducing the action time and impulse current.Experimental results demonstrate the effectiveness of the proposed method in accurately locating faults and improving relay protection performance.The longest operation time is reduced by 4.7023 s,and the maximum impulse current is limited to 0.3 A,effectively controlling the impact of large impulse currents and enhancing control efficiency.

Similarity matching method of power distribution system operating data based on neural information retrieval

Operation control of power systems has become challenging with an increase in the scale and complexity of power distribution systems and extensive access to renewable energy.Therefore,improvement of the ability of data-driven operation management,intelligent analysis,and mining is urgently required.To investigate and explore similar regularities of the historical operating section of the power distribution system and assist the power grid in obtaining high-value historical operation,maintenance experience,and knowledge by rule and line,a neural information retrieval model with an attention mechanism is proposed based on graph data computing technology.Based on the processing flow of the operating data of the power distribution system,a technical framework of neural information retrieval is established.Combined with the natural graph characteristics of the power distribution system,a unified graph data structure and a data fusion method of data access,data complement,and multi-source data are constructed.Further,a graph node feature-embedding representation learning algorithm and a neural information retrieval algorithm model are constructed.The neural information retrieval algorithm model is trained and tested using the generated graph node feature representation vector set.The model is verified on the operating section of the power distribution system of a provincial grid area.The results show that the proposed method demonstrates high accuracy in the similarity matching of historical operation characteristics and effectively supports intelligent fault diagnosis and elimination in power distribution systems.

Power Quality Improvement Using ANN Controller For Hybrid Power Distribution Systems

In this work,an Artificial Neural Network(ANN)based technique is suggested for classifying the faults which occur in hybrid power distribution systems.Power,which is generated by the solar and wind energy-based hybrid system,is given to the grid at the Point of Common Coupling(PCC).A boost converter along with perturb and observe(P&O)algorithm is utilized in this system to obtain a constant link voltage.In contrast,the link voltage of the wind energy conversion system(WECS)is retained with the assistance of a Proportional Integral(PI)controller.The grid synchronization is tainted with the assis-tance of the d-q theory.For the analysis of faults like islanding,line-ground,and line-line fault,the ANN is utilized.The voltage signal is observed at the PCC,and the Discrete Wavelet Transform(DWT)is employed to obtain different features.Based on the collected features,the ANN classifies the faults in an effi-cient manner.The simulation is done in MATLAB and the results are also validated through the hardware implementation.Detailed fault analysis is carried out and the results are compared with the existing techniques.Finally,the Total harmonic distortion(THD)is lessened by 4.3%by using the proposed methodology.

A Wind Power Prediction Framework for Distributed Power Grids

To reduce carbon emissions,clean energy is being integrated into the power system.Wind power is connected to the grid in a distributed form,but its high variability poses a challenge to grid stability.This article combines wind turbine monitoring data with numerical weather prediction(NWP)data to create a suitable wind power prediction framework for distributed grids.First,high-precision NWP of the turbine range is achieved using weather research and forecasting models(WRF),and Kriging interpolation locates predicted meteorological data at the turbine site.Then,a preliminary predicted power series is obtained based on the fan’s wind speed-power conversion curve,and historical power is reconstructed using variational mode decomposition(VMD)filtering to form input variables in chronological order.Finally,input variables of a single turbine enter the temporal convolutional network(TCN)to complete initial feature extraction,and then integrate the outputs of all TCN layers using Long Short Term Memory Networks(LSTM)to obtain power prediction sequences for all turbine positions.The proposed method was tested on a wind farm connected to a distributed power grid,and the results showed it to be superior to existing typical methods.

An Algorithm for Short-Circuit Current Interval in Distribution Networks with Inverter Type Distributed Generation Based on Affine Arithmetic

During faults in a distribution network,the output power of a distributed generation(DG)may be uncertain.Moreover,the output currents of distributed power sources are also affected by the output power,resulting in uncertainties in the calculation of the short-circuit current at the time of a fault.Additionally,the impacts of such uncertainties around short-circuit currents will increase with the increase of distributed power sources.Thus,it is very important to develop a method for calculating the short-circuit current while considering the uncertainties in a distribution network.In this study,an affine arithmetic algorithm for calculating short-circuit current intervals in distribution networks with distributed power sources while considering power fluctuations is presented.The proposed algorithm includes two stages.In the first stage,normal operations are considered to establish a conservative interval affine optimization model of injection currents in distributed power sources.Constrained by the fluctuation range of distributed generation power at the moment of fault occurrence,the model can then be used to solve for the fluctuation range of injected current amplitudes in distributed power sources.The second stage is implemented after a malfunction occurs.In this stage,an affine optimization model is first established.This model is developed to characterizes the short-circuit current interval of a transmission line,and is constrained by the fluctuation range of the injected current amplitude of DG during normal operations.Finally,the range of the short-circuit current amplitudes of distribution network lines after a short-circuit fault occurs is predicted.The algorithm proposed in this article obtains an interval range containing accurate results through interval operation.Compared with traditional point value calculation methods,interval calculation methods can provide more reliable analysis and calculation results.The range of short-circuit current amplitude obtained by this algorithm is slightly larger than those obtained using the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Therefore,the proposed algorithm has good suitability and does not require iterative calculations,resulting in a significant improvement in computational speed compared to the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Furthermore,the proposed algorithm can provide more reliable analysis and calculation results,improving the safety and stability of power systems.

Comprehensive Benefit Evaluation of SZ Distributed Photovoltaic Power Generation Project Based on AHP-Matter-Element Extension Model

With the introduction of the“dual carbon goals,”there has been a robust development of distributed photovoltaic power generation projects in the promotion of their construction.As part of this initiative,a comprehensive and systematic analysis has been conducted to study the overall benefits of photovoltaic power generation projects.The evaluation process encompasses economic,technical,environmental,and social aspects,providing corresponding analysis methods and data references.Furthermore,targeted countermeasures and suggestions are proposed,signifying the research’s importance for the construction and development of subsequent distributed photovoltaic power generation projects.

Exploring a New Lifetime Distribution for Modelling the Waiting Time of Bank Customers

The fitting of lifetime distribution in real-life data has been studied in various fields of research. With the theory of evolution still applicable, more complex data from real-world scenarios will continue to emerge. Despite this, many researchers have made commendable efforts to develop new lifetime distributions that can fit this complex data. In this paper, we utilized the KM-transformation technique to increase the flexibility of the power Lindley distribution, resulting in the Kavya-Manoharan Power Lindley (KMPL) distribution. We study the mathematical treatments of the KMPL distribution in detail and adapt the widely used method of maximum likelihood to estimate the unknown parameters of the KMPL distribution. We carry out a Monte Carlo simulation study to investigate the performance of the Maximum Likelihood Estimates (MLEs) of the parameters of the KMPL distribution. To demonstrate the effectiveness of the KMPL distribution for data fitting, we use a real dataset comprising the waiting time of 100 bank customers. We compare the KMPL distribution with other models that are extensions of the power Lindley distribution. Based on some statistical model selection criteria, the summary results of the analysis were in favor of the KMPL distribution. We further investigate the density fit and probability-probability (p-p) plots to validate the superiority of the KMPL distribution over the competing distributions for fitting the waiting time dataset.

NOVEL AIRCRAFT ELECTRICAL POWER DISTRIBUTION SYSTEM BASED ON DISTRIBUTED COMPUTER

As a matured technique used in many fields,the distributed computer system is still a new management method for the aeronautical electrical power distribution system in our country. In this paper, a novel aircraft electrical power distribution system based on the distributed computer system is proposed. The principles, features and structure of the aircraft electrical power distribution system and the distributed computer system named electrical load management system (ELMS) are studied. The ELMS composed of four electrical load management centers (ELMCs) and two power source processors (PSPs) operates in the 1553B buses. Principles of the ELMCs and the PSPs are introduced. With the application of the distributed computer system, the aircraft electrical power distribution system is simple, adaptable and flexible.

A Parallel Approach for Real-Time Power Flow in Distribution Networks

The new reality of smart distribution systems with use of generation sources of small and medium sizes brings new challenges for the operation of these systems. The complexity and the large number of nodes requires use of methods which can reduce the processing time of algorithms such as power flow, allowing its use in real time. This paper presents a known methodology for calculating the power flow in three phases using backward/forward sweep method, and also considering other network elements such as voltage regulators, shunt capacitors and sources of dispersed generation of types PV （active power and voltage） and PQ （active and reactive power）. After that, new elements are introduced that allow the parallelization of this algorithm and an adequate distribution of work between the available processors. The algorithm was implemented using a multi-tiered architecture; the processing times were measured in many network configurations and compared with the same algorithm in the serial version.

Synthetical Efficiency-based Optimization for the Power Distribution of Power-split Hybrid Electric Vehicles

Now the optimization strategies for power distribution are researched widely, and most of them are aiming to the optimal fuel economy and the driving cycle must be preknown. Thus if the actual driving condition deviates from the scheduled driving cycle, the effect of optimal results will be declined greatly. Therefore, the instantaneous optimization strategy carried out on-line is studied in this paper. The power split path and the transmission efficiency are analyzed based on a special power-split scheme and the efficiency models of the power transmitting components are established. The synthetical efficiency optimization model is established for enhancing the transmission efficiency and the fuel economy. The identification of the synthetical efficiency as the optimization objective and the constrain group are discussed emphatically. The optimization is calculated by the adaptive simulated annealing （ASA） algorithm and realized on-line by the radial basis function （RBF）-based similar models. The optimization for power distribution of the hybrid vehicle in an actual driving condition is carried out and the road test results are presented. The test results indicate that the synthetical efficiency optimization method can enhance the transmission efficiency and the fuel economy of the power-split hybrid electric vehicle （HEV） observably. Compared to the rules-based strategy the optimization strategy is optimal and achieves the approximate global optimization solution for the power distribution. The synthetical efficiency optimization solved by ASA algorithm can give attentions to both optimization quality and calculation efficiency, thus it has good application foreground for the power distribution of power-split HEV.

The Optimization Study about Fault Self-Healing Restoration of Power Distribution Network Based on Multi-Agent Technology

In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network,a fault recovery method based on multi-objective optimization algorithm is proposed.The optimization of the power distribution network fault system based on multiagent technology realizes fast recovery of multi-objective fault,solve the problem of network learning and parameter adjustment in the later stage of particle swarm optimization algorithm falling into the local extreme value dilemma,and realize the multi-dimensional nonlinear optimization of the main grid and the auxiliary grid.The system proposed in this study takes power distribution network as the goal,applies fuzzy probability algorithm,simplifies the calculation process,avoids local extreme value,and finally realizes the energy balance between each power grid.Simulation results show that the Multi-Agent Technology enjoys priority in restoring important load,shortening the recovery time of power grid balance,and reducing the overall line loss rate of power grid.Therefore,the power grid fault self-healing system can improve the safety and stability of the important power grid,and reduce the economic loss rate of the whole power grid.

Model heat source using actual distribution of laser power density for simulation of laser processing

The model of heat source(MHS) which reflects the thermal interaction between materials and laser during processing determines the accuracy of simulation results. To acquire desirable simulations results, although various modifications of heat sources in the aspect of absorption process of laser by materials have been purposed, the distribution of laser power density(DLPD) in MHS is still modeled theoretically. However, in the actual situations of laser processing, the DLPD is definitely different from the ideal models. So, it is indispensable to build MHS using actual DLPD to improve the accuracy of simulation results. Besides, an automatic modeling method will be benefit to simplify the tedious pre-processing of simulations. This paper presents a modeling method and corresponding algorithm to model heat source using measured DLPD. This algorithm automatically processes original data to get modeling parameters and provides a step MHS combining with absorption models. Simulations and experiments of heat transfer in steel plates irradiated by laser prove the mothed and the step MHS. Moreover, the investigations of laser induced thermal-crack propagation in glass highlight the signification of modeling heat source based on actual DLPD and demonstrate the enormous application of this method in the simulation of laser processing.

A Method for Improving Power Distribution Characteristics of Space Time Block Codes

Improving power distribution characteristics of space time block codes(STBCs),namely peak to average power ratio(PAPR),average to minimum power ratio(Ave/min),and probability of transmitting"zero"by antenna,makes easier their practical implementation.To this end,this study proposes to multiply full diversity STB C with a non-singular matrix in multiple input multiple output(MIMO)or multiple input single output(MISO)systems with linear or maximum likelihood(ML)receivers.It is proved that the obtained code achieves full diversity and the order of detection complexity does not change.The proposed method is applied to different types of STBCs.The bit error rate(BER)and power distribution characteristics of the new codes demonstrate the superiority of the introduced method.Further,lower and upper bounds on the BER of the obtained STBCs are derived for all receivers.The proposed method provides trade-off among PAPR,spectral efficiency,energy efficiency,and BER.

Objective assessment of the effect of pupil size upon the power distribution of multifocal contact lenses

AIM： To analytically assess the effect of pupil size upon the refractive power distributions of different designs of multifocal contact lenses.METHODS： Two multifocal contact lenses of center-near design and one multifocal contact lens of center-distance design were used in this study. Their power profiles were measured using the NIMO TR1504 device （LAMBDA-X, Belgium）. Based on their power profiles, the power distribution was assessed as a function of pupil size. For the high addition lenses, the resulting refractive power as a function of viewing distance （far, intermediate, and near） and pupil size was also analyzed.RESULTS： The power distribution of the lenses was affected by pupil size differently. One of the lenses showed a significant spread in refractive power distribution, from about ？3 D to 0 D. Generally, the power distribution of the lenses expanded as the pupil diameter became greater. The surface of the lens dedicated for each distance varied substantially with the design of the lens.CONCLUSION： In an experimental basis, our results show how the lenses power distribution is affected by the pupil size and underlined the necessity of careful evaluation of the patient’s visual needs and the optical properties of a multifocal contact lens for achieving the optimal visual outcome.

Models and Methods for Urban Power Distribution Network Planning

The models, methods and their application experiences of a practical GIS(geographic information system)-based computer decision-making support system of urban power distribution network planning with seven subsystems,termed CNP,are described.In each subsystem there is at least one or one set of practical mathematical methobs.Some new models and mathematical methods have been introduced.In the development of CNP the idea of cognitive system engineering has been insisted on,which claims that human and computer intelligence should be combined together to solve the complex engineering problems cooperatively.Practical applications have shown that not only the optimal plan can be automatically reached with many complicated factors considered, but also the computation,analysis and graphic drawing burden can be released considerably.

Repulsive firefly algorithm-based optimal switching device placement in power distribution systems

To achieve optimal configuration of switching devices in a power distribution system,this paper proposes a repulsive firefly algorithm-based optimal switching device placement method.In this method,the influence of territorial repulsion during firefly courtship is considered.The algorithm is practically applied to optimize the position and quantity of switching devices,while avoiding its convergence to the local optimal solution.The experimental simulation results have showed that the proposed repulsive firefly algorithm is feasible and effective,with satisfying global search capability and convergence speed,holding potential applications in setting value calculation of relay protection and distribution network automation control.

Grey series time-delay predicting model in state estimation for power distribution networks

A new combined model is proposed to obtain predictive data value applied in state estimation for radial power distribution networks. The time delay part of the model is calculated by a recursive least squares algorithm of system identification, which can gradually forget past information. The grey series part of the model uses an equal dimension new information model (EDNIM) and it applies 3 points smoothing method to preprocess the original data and modify remnant difference by GM(1,1). Through the optimization of the coefficient of the model, we are able to minimize the error variance of predictive data. A case study shows that the proposed method achieved high calculation precision and speed and it can be used to obtain the predictive value in real time state estimation of power distribution networks.