变压器差动保护算法的性能比较与优化研究

旨在对变压器差动保护算法进行性能比较并寻找对应的优化策略,以提高电力系统的稳定性和可靠性。首先介绍差动保护算法原理和常见算法,通过评估不同算法在真实工程应用中的效果,对算法的精确性、灵敏度、鲁棒性等性能指标进行了对比,并揭示现有算法的局限性和存在的问题,其次分析变压器差动保护算法性能的影响因素,最后提出变压器差动保护算法性能优化策略。

双比率差动保护算法的灵敏度和稳定性分析

双比率差动保护由两段折线组成,低斜率段可以灵敏地反映内部故障,使保护可靠动作;而高斜率段可防止在外部穿越性故障情况下,由于TA饱和引起的差动保护误动作。文中运用分流电流系数θ对双比率电流差动保护算法的灵敏度和稳定性进行分析,开发了一种双比率电流差动保护的RTDS软件模型,采用穿越电流为偏置电流的双比率差动算法分析了在内部高阻故障时的灵敏度和外部大电流故障TA饱和时的稳定性,并通过实时数字仿真系统RTDS进行了验证。仿真结果表明:双比率算法较单比率算法,具有外部故障高稳定性,而在内部高阻故障时,也有很高的灵敏度。通过新的坐标平面,可以有针对性地调节制动系数K1、K2,最大限度地发挥判据的效能,很直观地看出制动系数与稳定性和灵敏度的关系。

电力变压器微机差动保护的算法与实现

介绍了一种三绕组变压器差动保护装置,包括基本原理、保护算法、以及工程实现。该装置以DSP为核心,采用电磁兼容技术以及在线故障诊断、实时报警,使该装置能安全、可靠地运行。具有速度快、整定范围宽、准确度高等优点。

云广特高压直流接地极母线差动保护状态识别信号的改进

针对云南—广东特高压直流输电系统(以下简称"云广直流")的2起接地极母线差动保护误动事故,分析了云广直流接地极母线差动保护的差动电流运算逻辑和状态识别原理,指出状态识别信号的误判是导致保护误动的根本原因,从二次回路和软件逻辑两方面提出了优化状态识别信号的措施。在现场实施逻辑改进措施后,云广直流接地极母线差动保护未发生过误动事故。

分布式发电对电力系统保护继电保护的影响

为了保持系统的稳定运行,有必要对现行的继电保护机制深挖细掘,并提出合适的改进策略。针对这一问题,以典型的分布式发电系统为例,提出了一种基于改进的电流差动保护算法,实验结果表明,这种算法能够有效处理分布式发电带来的保护问题,具有很高的应用价值,这对于指导电力系统保护技术的进一步发展,提高系统的安全与稳定性具有重要的参考价值。

An Immune Self-adaptive Differential Evolution Algorithm with Application to Estimate Kinetic Parameters for Homogeneous Mercury Oxidation

A new version of differential evolution （DE） algorithm, in which immune concepts and methods are applied to determine the parameter setting, named immune self-adaptive differential evolution （ISDE）, is proposed to improve the performance of the DE algorithm. During the actual operation, ISDE seeks the optimal parameters arising from the evolutionary process, which enable ISDE to alter the algorithm for different optimization problems and improve the performance of ISDE by the control parameters＇ self-adaptation. The .performance of the proposed method is studied with the use of nine benchmark problems and compared with original DE algorithm ~nd-other well-known self-adaptive DE algorithms. The experiments conducted show that the ISDE clearly outperforms the other DE algorithms in all benchmark functions. Furthermore, ISDE is applied to develop the kinetic model for homogeneous mercury. （Hg） oxidation in flue gas, and satisfactory results are obtained.

Extended Active Contour Algorithm Based on Color Variance

General active contour algorithm, which uses the intensity of the image, has been used to actively segment objects. Because the objects have a similar intensity but different colors, it is difficult to segment any object from the others, Moreover, this algodthm can only be used in the simple environment since it is very sensitive to noise. In tinter to solve these problems. This paper proposes an extended active contour algorithm based on a color variance. In complex images, the color variance energy as the image energy is introduced into the general active contour algorithm. Experimental results show that the proposed active contour algorithm is very effective in various environments.

A numerical error analysis method and its application on a 4RRR parallel kinematic machine

To guarantee the accuracy of error analysis and evaluate the manufacturing tolerance s influence,anumerical error analysis method for parallel kinematic machines (PKMs) is presented in this paper.Quasi-Newton method and genetic algorithm are introduced for the forward kinematic solution.Based onthe inverse and forward kinematic solutions,the end-effector s error calculation procedure is developed.To solve the accuracy problem caused by the length and angular parameters' different units,a normalizationmethod is proposed based on the manufacturing tolerance.Comparison between the error analysis resultscalculated by the traditional method and the numerical method for a 4RRR PKM shows that,this numericalerror analysis method is more accurate,simpler,and can evaluate the machine s real error basedon the manufacturing tolerance.

Harmony search algorithm with differential evolution based control parameter co-evolution and its application in chemical process dynamic optimization

A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.

Hybrid Differential Evolution for Estimation of Kinetic Parameters for Biochemical Systems

Determination of the optimal model parameters for biochemical systems is a time consuming iterative process. In this study, a novel hybrid differential evolution （DE） algorithm based on the differential evolution technique and a local search strategy is developed for solving kinetic parameter estimation problems. By combining the merits of DE with Gauss-Newton method, the proposed hybrid approach employs a DE algorithm for identifying promising regions of the solution space followed by use of Gauss-Newton method to determine the optimum in the identified regions. Some well-known benchmark estimation problems are utilized to test the efficiency and the robustness of the proposed algorithm compared to other methods in literature. The comparison indicates that the present hybrid algorithm outperforms other estimation techniques in terms of the global searching ability and the con- vergence speed. Additionally, the estimation of kinetic model parameters for a feed batch fermentor is carried out to test the applicability of the proposed algorithm. The result suggests that the method can be used to estimate suitable values of model oarameters for a comolex mathematical model.

Novel Control Vector Parameterization Method with Differential Evolution Algorithm and Its Application in Dynamic Optimization of Chemical Processes

Two general approaches are adopted in solving dynamic optimization problems in chemical processes, namely, the analytical and numerical methods. The numerical method, which is based on heuristic algorithms, has been widely used. An approach that combines differential evolution （DE） algorithm and control vector parameteri- zation （CVP） is proposed in this paper. In the proposed CVP, control variables are approximated with polynomials based on state variables and time in the entire time interval. Region reduction strategy is used in DE to reduce the width of the search region, which improves the computing efficiency. The results of the case studies demonstrate the feasibility and efficiency of the oroposed methods.

WLS filter for reducing atmospheric effects in spaceborne SAR tomography

A new approach was presented to eliminate the atmosphere-induced phase error utilizing only the single look complex(SLC) synthetic aperture radar(SAR) image set. This method exploited the space-invariance characteristic of phase error components contained in image pixels and estimates the phase error using the weighted least-squares(WLS) filter. Actually, this sort of method can be classified as autofocus algorithm which was generally applied in airborne SAR 2-D imaging to compensate the phase error introduced by airplane's nonideal motion. Real data processing, which is relevant to Honda center and Angel stadium of Anaheim test-sites and acquired by Envisat-ASAR during the period from June 2004 to October 2007, was carried out to evaluate this WLS estimation algorithm. Experimental results show that the phase error estimated from WLS filter is very accurate and the focusing quality along NSR dimension is improved prominently via phase correction, which verifies the practicability of this new method.

Geometric precision evaluation methodology of multiple reference station network algorithms

To evaluate the performance of real time kinematic (RTK) network algorithms without applying actual measurements, a new method called geometric precision evaluation methodology (GPEM) based on covariance analysis was presented. Three types of multiple reference station interpolation algorithms, including partial derivation algorithm (PDA), linear interpolation algorithms (LIA) and least squares condition (LSC) were discussed and analyzed. The geometric dilution of precision (GDOP) was defined to describe the influence of the network geometry on the interpolation precision, and the different GDOP expressions of above-mentioned algorithms were deduced. In order to compare geometric precision characteristics among different multiple reference station network algorithms, a simulation was conducted, and the GDOP contours of these algorithms were enumerated. Finally, to confirm the validation of GPEM, an experiment was conducted using data from Unite State Continuously Operating Reference Stations (US-CORS), and the precision performances were calculated according to the real test data and GPEM, respectively. The results show that GPEM generates very accurate estimation of the performance compared to the real data test.

Application of linear active disturbance rejection control for photoelectric tracking system

Dynamic characteristics and tracking precision are studied in the photoelectric tracking system and a linear active disturbance rejection control( LADRC) scheme is proposed for position loop. A current and speed controller is designed by a transfer function model,which is obtained by adaptive differential evolution. Model error,friction and nonlinear factor existing in position loop are treated as ‘disturbance',which is estimated and compensated by generalized proportional integral( GPI)observer. Comparative results are provided to demonstrate the remarkable performance of the proposed method. It turns out that the proposed scheme is successful and has superior features,such as quick dynamic response,low overshoot and high tracking precision. Furthermore,with the proposed method,friction is suppressed effectively.

TWO IMPROVED ALGORITHMS AND IMPLEMENTATION FOR A SINGULARLY PERTURBED PROBLEM ON MOVING MESHES

This paper applies a difference scheme to a singularly perturbed problem. The authors provide two algorithms on moving mesh methods by using Richardson extrapolation which can improve the accuracy of numerical solution. In traditional algorithms of moving meshes, the initial mesh is a uniform mesh. The authors change it to Bakhvalov-Shishkin mesh, and prove that it improves efficiency by numerical experiments. Finally, the results of the two algorithms are analyzed.

Multidiscipline collaborative optimization of differential steering system of electric vehicle with motorized wheels

Based on the multidiscipline design optimization theory, a multidiscipline collaborative optimization model of the differential steering system of electric vehicle with motorized wheels is built, with the steering economy as the main system and the steering road feel, the steering flexibility and the mechanic character of the steering sensors as the subsystems. Considering the coupled relationship of each discipline, the main system is optimized by the multi-island algorithm and the subsystems are optimized by the sequential quadratic programming algorithm. The simulation results show that the steering economy can be optimized by the collaborative optimization, and that the system can get good steering road feel, good steering flexibility and good mechanic character of the steering sensors.