Research of Electric Cable Path Planning Based on Heuristic Optimization Algorithm in Mixed-Land Scenario

In order to improve the reliability of power supply,the sophisticated design of the structure of electric cable network has become an important issue for modern urban distribution networks.In this paper,an electric cable path planning model based on heuristic optimization algorithm considering mixed-land scenario is proposed.Firstly,based on different land samples,the kernel density estimation(KDE)and the analytic hierarchy process(AHP)are used to estimate the construction cost of each unit grid,in order to construct the objective function of comprehensive investment for electric cable loop network.Then,the ant colony optimization(ACO)was improved in pheromone concentration,factor increment and search direction to accelerate the solving speed,and the cable path planning result with minimum construction cost is obtained.Finally,the feeder’s tie line of the cable loop network is planned by the genetic algorithm(GA)to achieve the minimum operating cost.In the case analysis,compared with the traditional method,not only the subjective factors in the process of investment estimation can be avoided,but also the speed of model solving and the quality of the optimal solution are improved.

Large Power Transformer Fault Diagnosis and Prognostic Based on DBNC and D-S Evidence Theory

Power transformer is a core equipment of power system, which undertakes the important functions of power transmission and transformation, and its safe and stable operation has great significance to the normal operation of the whole power system. Due to the complex structure of the transformer, the use of single information for condition-based maintenance (CBM) has certain limitations, with the help of advanced sensor monitoring and information fusion technology, multi-source information is applied to the prognostic and health management (PHM) of power transformer, which is an important way to realize the CBM of power transformer. This paper presents a method which combine deep belief network classifier (DBNC) and D-S evidence theory, and it is applied to the PHM of the large power transformer. The experimental results show that the proposed method has a high correct rate of fault diagnosis for the power transformer with a large number of multi-source data.

Massive Power Device Condition Monitoring Data Feature Extraction and Clustering Analysis using MapReduce and Graph Model

Effective storage,processing and analyzing of power device condition monitoring data faces enormous challenges.A framework is proposed that can support both MapReduce and Graph for massive monitoring data analysis at the same time based on Aliyun DTplus platform.First,power device condition monitoring data storage based on MaxCompute table and parallel permutation entropy feature extraction based on MaxCompute MapReduce are designed and implemented on DTplus platform.Then,Graph based k-means algorithm is implemented and used for massive condition monitoring data clustering analysis.Finally,performance tests are performed to compare the execution time between serial program and parallel program.Performance is analyzed from CPU cores consumption,memory utilization and parallel granularity.Experimental results show that the designed framework and parallel algorithms can efficiently process massive power device condition monitoring data.

A method for power suppliers’optimal cooperative bidding strategies considering network losses

The bidding strategies of power suppliers to maximize their interests is of great importance.The proposed bilevel optimization model with coalitions of power suppliers takes restraint factors into consideration,such as operating cost reduction,potential cooperation,other competitors’bidding behavior,and network constraints.The upper model describes the coalition relationship between suppliers,and the lower model represents the independent system operator’s optimization without network loss(WNL)or considering network loss(CNL).Then,a novel algorithm,the evolutionary game theory algorithm(EGA)based on a hybrid particle swarm optimization and improved firefly algorithm(HPSOIFA),is proposed to solve the bi-level optimization model.The bidding behavior of the power suppliers in equilibrium with a dynamic power market is encoded as one species,with the EGA automatically predicting a plausible adaptation process for the others.Individual behavior changes are employed by the HPSOIFA to enhance the ability of global exploration and local exploitation.A novel improved firefly algorithm(IFA)is combined with a chaotic sequence theory to escape from the local optimum.In addition,the Shapley value is applied to the profit distribution of power suppliers’cooperation.The simulation,adopting the standard IEEE-30 bus system,demonstrates the effectiveness of the proposed method for solving the bi-level optimization problem.

Anomaly Detection and Pattern Differentiation in Monitoring Data from Power Transformers

Aiming at the problem of abnormal data generated by a power transformer on-line monitoring system due to the influences of transformer operation state change,external environmental interference,communication interruption,and other factors,a method of anomaly recognition and differentiation for monitoring data was proposed.Firstly,the empirical wavelet transform(EWT)and the autoregressive integrated moving average(ARIMA)model were used for time series modelling of monitoring data to obtain the residual sequence reflecting the anomaly monitoring data value,and then the isolation forest algorithm was used to identify the abnormal information,and the monitoring sequence was segmented according to the recognition results.Secondly,the segmented sequence was symbolised by the improved multi-dimensional SAX vector representation method,and the assessment of the anomaly pattern was made by calculating the similarity score of the adjacent symbol vectors,and the monitoring sequence correlation was further used to verify the assessment.Finally,the case study result shows that the proposed method can reliably recognise abnormal data and accurately distinguish between invalid and valid anomaly patterns.

Application of Hankel Dynamic Mode Decomposition for Wide Area Monitoring of Subsynchronous Resonance

In recent years,subsynchronous resonance(SSR)has frequently occurred in DFIG-connected series-compensated systems.For the analysis and prevention,it is of great importance to achieve wide area monitoring of the incident.This paper presents a Hankel dynamic mode decomposition(DMD)method to identify SSR parameters using synchrophasor data.The basic idea is to employ the DMD technique to explore the subspace of Hankel matrices constructed by synchrophasors.It is analytically demonstrated that the subspace of these Hankel matrices is a combination of fundamental and SSR modes.Therefore,the SSR parameters can be calculated once the modal parameter is extracted.Compared with the existing method,the presented work has better dynamic performances as it requires much less data.Thus,it is more suitable for practical cases in which the SSR characteristics are timevarying.The effectiveness and superiority of the proposed method have been verified by both simulations and field data.

Multi-area Frequency-constrained Unit Commitment for Power Systems with High Penetration of Renewable Energy Sources and Induction Machine Load

The increasing penetration of renewable energy sources(RESs)brings great challenges to the frequency security of power systems.The traditional frequency-constrained unit commitment(FCUC)analyzes frequency by simplifying the average system frequency and ignoring numerous induction machines(IMs)in load,which may underestimate the risk and increase the operational cost.In this paper,we consider a multiarea frequency response(MAFR)model to capture the frequency dynamics in the unit scheduling problem,in which regional frequency security and the inertia of IM load are modeled with high-dimension differential algebraic equations.A multi-area FCUC(MFCUC)is formulated as mixed-integer nonlinear programming(MINLP)on the basis of the MAFR model.Then,we develop a multi-direction decomposition algorithm to solve the MFCUC efficiently.The original MINLP is decomposed into a master problem and subproblems.The subproblems check the nonlinear frequency dynamics and generate linear optimization cuts for the master problem to improve the frequency security in its optimal solution.Case studies on the modified IEEE 39-bus system and IEEE 118-bus system show a great reduction in operational costs.Moreover,simulation results verify the ability of the proposed MAFR model to reflect regional frequency security and the available inertia of IMs in unit scheduling.

Effects of Contaminations on Corona Pulse Inception Characteristics of HVDC Conductor

Contaminations adhering on HVDC transmission line will change its corona characteristics to generate electromagnetic pollution. The corona-induced radio interference and audible noise become important factors influencing the configuration and costs of transmission project. For understanding the effects of contaminations on the corona pulse characteristics of an HVDC transmission line,a corona cage was adopted to experimentally investigate corona pulse inception voltage and corona pulse characteristics of the conductors with different contaminations on surfaces. The contaminations include simulated contaminations,carbon powder,cement and fine sand. The results show that when conductor is covered with contaminations,the positive polarity corona pulses have high amplitude and low frequency,while the negative polarity corona pulses have low amplitude and incremental high frequency components. The corona pulse inception voltage presents a negatively exponential decrease with the increase of contamination density,showing a saturation trend. Fine sand shows the greatest effect on the corona pulse inception voltage with positive polarity,while cement shows the least effect. A function of corona inception voltage and surface contamination density is given. This study may provide reference for design of transmission lines.

Arc characteristics during the instability stage on transverse magnetic field contacts

The arcing process greatly affects the breaking ability after current zero.The instability stage is the transition stage from the ignition to the movement stage,which affects the arc movement characteristics.In this paper,the arc characteristics during the instability stage on spiral-type contacts were investigated using a high-speed video camera.A multi-column parallel instability mode and a single-column instability mode were found during the instability stage.The arc appearance and constriction degree changed rapidly.The arc voltage usually increased accompanied by fluctuations.In addition,it was found that the current significantly influenced the arc mode and duration in the instability stage.With increased peak current,the probability of a single-column instability mode increased,and the fluctuation range and average time decreased.

Investigation of cathode spot characteristics in vacuum under transverse magnetic field (TMF) contacts

With the continuous improvement of current levels in power systems, the demands on the breaking capacity requirements of vacuum circuit breakers are getting higher and higher. The breaking capacity of vacuum breakers is determined by cathode spots, which provide electrons and metal vapor to maintain the arc. In this paper, experiments were carried out on two kinds of transverse magnetic field（TMF） contacts in a demountable vacuum chamber, the behavior of the cathode spots was recorded by a high-speed charge-coupled device（CCD） video camera, and the characteristics of the cathode spots were analyzed through the image processing method. The phenomenon of cathode spot groups and the star-shaped pattern of the spots were both discovered in the experiment. The experimental results show that with the condition of TMF contacts the initial expansion speed of cathode spots is influenced by some parameters, such as the tested current, contact gap, the structure of the contact, the contact diameter, the number of slots, etc. In addition, the influence of the magnetic field on the formation of the cathode spot groups, the distribution, and the dynamic characteristics of the cathode spots were analyzed. It is concluded that the characteristics of the cathode spots are due to the effect of the magnetic field on the near-cathode plasma. The study of the characteristics of cathode spots in this paper would be helpful in the exploration of the physical process of vacuum arcs, and would be of guiding significance in optimizing the design of vacuum circuit breakers.

A Design of 220 kV Line Protection Action Deduction System Based on Numerical Simulation

Accurate conditions monitoring and early wrong action warnings of relay protection in the Smart Substation is the basic guarantee to realize the normal operation of primary and secondary system of the power grid.At present,the traditional operation and maintenance monitoring methods of relay protections have poor timeliness,while some automatic monitoring methods have insufficient early warning performance,and lack the online action deduction function independent of the actual device.In this paper,a design method of integrated action deduction system including protection logic reasoning and software and hardware operation condition is proposed.The system can receive real-time operation information of protection online,simulate different types of faults,and output the recording information of sub modules belongs to the action deduction system.It can realize the online monitoring of device faults such as deducing the correctness of setting values at a certain time in the future,giving the wrong action warnings and predicting the probability of them as well,which effectively improves the operation and maintenance efficiency of the secondary system in the intelligent substation.

Study on the dynamic mechanical properties of winding-block axial structure considering short circuit strain rate effect

Transformers may suffer multiple short-circuit impacts during long-term operation,and axial instability is one of the typical types of serious accidents caused by short-circuit faults.The axial instability form of the winding-block structure is analysed,and the dynamic solution of the winding short-circuit electromagnetic force is obtained by estab-lishing the three-dimensional magnetic-circuit-force multi-physical field coupling simulation model.The influence of strain rate on the cushion block constitutive equation is corrected,and the modified model is verified by short-circuit impact test and quasi-static test.The research results show that for 110 kV 31.5 MVA transformers,the maximum electromagnetic axial resultant force of winding is 363.16 kN,and the ultimate tilt force is 1214.2 kN.The pre-tightening force configuration is accordingly recom-mended to range from 363.16 to 608.28 kN,which is narrowed by 18.49%compared with the static calculation method;Meanwhile,adding a logarithmic strain rate correction term to the classical constitutive equation of the cushion block can achieve a good correction of the stress-strain relationship with the coefficient of determination above 0.99,and the cushion block has a larger elastic modulus under high strain rate load.The research results provide an important theoretical reference for the axial stability structure of transformers.