Voltage Profile Enhancement and Power Loss Reduction with Economic Feasibility Using Small Capacity Distribution Transformers

Usually,rural areas can be electrified via three-phase distribution transformers with relatively large capacities.In such areas,low voltage lines are used for long distances,which cause power losses and voltage drop for different types of consumers.Reducing losses and improving voltage profiles in rural distribution networks are significant challenges for electricity distribution companies.However different solutions were proposed in the literature to overcome these challenges,most of them face difficulties when applied in the conventional distribution network.To address the above issues,an applicable solution is proposed in this paper by installing a number of small-capacity distribution transformers instead of every single large-capacity transformer in rural areas.The proposed approach is implemented in the branch network of Al-Hoqool village,which belongs to the Nineveh distribution network.The network has been inspected on-site,drawn,and analyzed using the electrical systems analysis program(ETAP).The analysis showed that using the single-phase pole-mounted transformers can improve the voltage in the network’s end by 29%and enhance the voltage profile for all consumers.The analysis has also demonstrated that the modification can reduce the total power losses by 78%compared to the existing network.Concerning the economic aspect,the payback period for the proposed network is assigned to be 20 months.

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.

Revisiting the Curie-Von Schweidler Law for Dielectric Relaxation and Derivation of Distribution Function for Relaxation Rates as Zipf’s Power Law and Manifestation of Fractional Differential Equation for Capacitor

The classical power law relaxation, i.e. relaxation of current with inverse of power of time for a step-voltage excitation to dielectric—as popularly known as Curie-von Schweidler law is empirically derived and is observed in several relaxation experiments on various dielectrics studies since late 19th Century. This relaxation law is also regarded as “universal-law” for dielectric relaxations;and is also termed as power law. This empirical Curie-von Schewidler relaxation law is then used to derive fractional differential equations describing constituent expression for capacitor. In this paper, we give simple mathematical treatment to derive the distribution of relaxation rates of this Curie-von Schweidler law, and show that the relaxation rate follows Zipf’s power law distribution. We also show the method developed here give Zipfian power law distribution for relaxing time constants. Then we will show however mathematically correct this may be, but physical interpretation from the obtained time constants distribution are contradictory to the Zipfian rate relaxation distribution. In this paper, we develop possible explanation that as to why Zipfian distribution of relaxation rates appears for Curie-von Schweidler Law, and relate this law to time variant rate of relaxation. In this paper, we derive appearance of fractional derivative while using Zipfian power law distribution that gives notion of scale dependent relaxation rate function for Curie-von Schweidler relaxation phenomena. This paper gives analytical approach to get insight of a non-Debye relaxation and gives a new treatment to especially much used empirical Curie-von Schweidler (universal) relaxation law.

Non-Stationary Random Process for Large-Scale Failure and Recovery of Power Distribution

This work applies non-stationary random processes to resilience of power distribution under severe weather. Power distribution, the edge of the energy infrastructure, is susceptible to external hazards from severe weather. Large-scale power failures often occur, resulting in millions of people without electricity for days. However, the problem of large-scale power failure, recovery and resilience has not been formulated rigorously nor studied systematically. This work studies the resilience of power distribution from three aspects. First, we derive non-stationary random processes to model large-scale failures and recoveries. Transient Little’s Law then provides a simple approximation of the entire life cycle of failure and recovery through a queue at the network-level. Second, we define time-varying resilience based on the non-stationary model. The resilience metric characterizes the ability of power distribution to remain operational and recover rapidly upon failures. Third, we apply the non-stationary model and the resilience metric to large-scale power failures caused by Hurricane Ike. We use the real data from the electric grid to learn time-varying model parameters and the resilience metric. Our results show non-stationary evolution of failure rates and recovery times, and how the network resilience deviates from that of normal operation during the hurricane.

高压管汇材料疲劳性能测试及P-S-N模型曲线的拟合

高压管汇作为压裂设备中的主要易损件之一,其失效危害较大。它的失效原因主要是疲劳、冲蚀、腐蚀或者材料缺陷引起的刺漏和爆裂,其中尤以疲劳失效最不可预估。目前,对于高压管汇材料的疲劳性能研究不够深入,为解决高压管汇材料疲劳寿命的准确描述问题,以某国产高压管汇材料为例,进行了一系列疲劳试验,并基于试验数据,采用多种分布模型和不同S-N模型进行拟合分析,得出综合评价拟合能力最强的P-S-N模型。结果表明,该材料在中长疲劳寿命区,Weibull三参数模型在7级应力水平下综合评价能力最好;在存活率分别为50%、90%、99%、99.9%时,指数S-N模型的拟合系数均大于0.98,拟合能力最好。得出的P-S-N模型曲线可以为高压管汇的疲劳寿命以及安全设计提供依据。

Spatial Distribution of Mulberry Thrips,Pseudodendrothrips mori Niwa (Thysanoptera:Thripidae)

Pseudodendrothrips mori is a serious pest to mulberry trees and its infestation affects the qualitative and quantitative characteristics of mulberry leaves consumed by silkworm. The spatial distribution of mulberry thrips within plant and orchard was assessed using Taylor＇s power law and Morisita＇s index of dispersion. The results showed that P.mori populations were localized in certain parts of the trees and fields. Distribution of thrips within plant showed that the larval instars were located on lower canopy （leaves 5-10 from top） of trees but adults preferred the upper canopy （leaves 1-5 from top）. The thrips density did not vary significantly among the leaf direction inside the trees. The thrips tended to be more accumulated on the trees located in East, South and North than in Center and West of orchard. The distributions of P.mori adults and larvae on the leaves were aggregated.

基于T-S模糊逻辑的混合储能孤岛直流微电网功率分配控制

在含混合储能的直流微电网中,传统阻容下垂控制无法解决由线路电阻和负荷功率波动导致的系统功率分配失衡问题。为此,提出一种基于Takagi-Sugeno(T-S)模糊逻辑的自适应阻容下垂控制方法以实现混合储能的分频分配。根据蓄电池和超级电容的物理特性,建立单个蓄电池支路输出电压、蓄电池组间输出功率差额和阻性下垂系数之间的T-S模糊逻辑关系,以及单个超级电容支路输出功率及其变化率、超级电容组间功率差额和容性下垂系数之间的T-S模糊逻辑关系,并由此构建基于T-S模糊逻辑的阻容下垂控制器。推导含混合储能的直流微电网中各部分的平均阻抗模型,并采用阻抗比分析法对微电网的小信号稳定性进行研究。MATLAB/Simulink仿真结果表明,基于T-S模糊逻辑的阻容下垂控制可保证在线路电阻和负荷功率波动情况下系统功率的合理分配。

Vertical Profile of Wind Speed in the Atmospheric Boundary Layer and Assessment of Wind Resource on the Bobo Dioulasso Site in Burkina Faso

This study investigates both the characteristics of the vertical wind profile at the Bobo Dioulasso site located in the Sudanian climate zone in Burkina Faso during a day and night convective wind cycle and the estimation and variability of the wind resource. Wind data at 10 m above ground level and satellite data at 50 m altitude in the atmospheric boundary layer were used for the period going from January 2006 to December 2016. Based on Monin-Obukhov theory, the logarithmic law and the power law made it possible to characterize the wind profile. On the study site, the atmosphere is generally unstable from 10:00 to 18:00 and stable during the other periods of the day. Wind extrapolation models were tested on our study site. Fitting equations proposed are always in agreement with the data, contrary to other models assessed. Based on these equations, the profile of a day and night cycle wind cycle was established by extrapolation of wind data measured at 10 m above the ground. Lastly, the model of the power law based on the stability was used to generate data on wind speed from 20 m to 50 m based on data from 10 m above the ground. Weibull function was used to characterize wind speed rate distribution and to calculate wind energy potential. The average annual power density on the site is estimated at 53.13 W/m2 at 20 m and at 84.05 W/m2 at 50 m, or 36.78% increase. Considering these results, the Bobo-Dioulasso site could be appropriate to build small and medium-size turbines to supply the rural communities of the Bobo Dioulasso region with electricity.

Research on Multi-Scale Modeling of Grid-Connected Distributed Photovoltaic Power Generation

The complexity of distribution network model mainly depends on the model scale of grid-connected distributed photovoltaic (PV) power generation. Therefore, the simulation performance of multi-scale PV model is the key factor of the simulation accuracy in the specific operating scenarios of distribution network. In this paper, a multi-scale model of grid connected PV distributed generation system is proposed based on the mathematical model of grid-connected distributed PV power generation. It is analyzed that differences of simulation performance, such as adaptability of simulation step size, accuracy of output and the effect on voltage profile of distribution network, between PV models with different scales in IEEE 33 node example. Simulation results indicate that the multi-scale model is effective in improving the accuracy and efficiency of simulation under different operating conditions of distribution network.

A WEIGHTED FEATURE REDUCTION METHOD FOR POWER SPECTRA OF RADAR HRRPS

Feature reduction is a key process in pattern recognition. This paper deals with the feature reduction methods for a time-shift invariant feature, power spectrum, in Radar Automatic Target Recognition (RATR) using High-Resolution Range Profiles (HRRPs). Several existing feature reduction methods in pattern recognition are analyzed, and a weighted feature reduction method based on Fisher's Discriminant Ratio (FDR) is proposed in this paper. According to the characteristics of radar HRRP target recognition, this proposed method searches the optimal weight vector for power spectra of HRRPs by means of an iterative algorithm, and thus reduces feature dimensionality. Compared with the method of using raw power spectra and some existing feature reduction methods, the weighted feature reduction method can not only reduce feature dimensionality, but also improve recognition performance with low computation complexity. In the recognition experiments based on measured data, the proposed method is robust to different test data and achieves good recognition results.

Controller Design for Electric Power Steering System Using T-S Fuzzy Model Approach

Pressure ripples in electric power steering （EPS） systems can be caused by the phase lag between the driver s steering torque and steer angle, the nonlinear frictions, and the disturbances from road and sensor noise especially during high-frequency maneuvers. This paper investigates the use of the robust fuzzy control method for actively reducing pressure ripples for EPS systems. Remarkable progress on steering maneuverability is achieved. The EPS dynamics is described with an eight-order nonlinear state-space model and approximated by a Takagi-Sugeno （T-S） fuzzy model with time-varying delays and external disturbances. A stabilization approach is then presented for nonlinear time-delay systems through fuzzy state feedback controller in parallel distributed compensation （PDC） structure. The closed-loop stability conditions of EPS system with the fuzzy controller are parameterized in terms of the linear matrix inequality （LMI） problem. Simulations and experiments using the proposed robust fuzzy controller and traditional PID controller have been carried out for EPS systems. Both the simulation and experiment results show that the proposed fuzzy controller can reduce the torque ripples and allow us to have a good steering feeling and stable driving.

Wind Power Potential in Interior Alaska from a Micrometeorological Perspective

The wind power potential in Interior Alaska is evaluated from a micrometeorological perspective. Based on the local balance equation of momentum and the equation of continuity we derive the local balance equation of kinetic energy for macroscopic and turbulent systems, and in a further step, Bernoulli’s equation and integral equations that customarily serve as the key equations in momentum theory and blade-element analysis, where the Lanchester-Betz-Joukowsky limit, Glauert’s optimum actuator disk, and the results of the blade-element analysis by Okulov and Sorensen are exemplarily illustrated. The wind power potential at three different sites in Interior Alaska (Delta Junction, Eva Creek, and Poker Flat) is assessed by considering the results of wind field predictions for the winter period from October 1, 2008, to April 1, 2009 provided by the Weather Research and Forecasting (WRF) model to avoid time-consuming and expensive tall-tower observations in Interior Alaska which is characterized by a relatively low degree of infrastructure outside of the city of Fairbanks. To predict the average power output we use the Weibull distributions derived from the predicted wind fields for these three different sites and the power curves of five different propeller-type wind turbines with rated powers ranging from 2 MW to 2.5 MW. These power curves are represented by general logistic functions. The predicted power capacity for the Eva Creek site is compared with that of the Eva Creek wind farm established in 2012. The results of our predictions for the winter period 2008/2009 are nearly 20 percent lower than those of the Eva Creek wind farm for the period from January to September 2013.

Power Law for the Rates of Different Numbers of Chronic Diseases among Elderly Chinese People

Chronic disease is an important factor that affect the health of elderly people. We analyzed the 2006 and 2010 data from the Chinese Urban and Rural Elderly Population Surveys, which are nationally representative surveys of elderly people aged 60 years and above. We found that there existed a typical power-law distribution for the rates of different numbers of chronic diseases among elderly Chinese people. A Kolmogorov-Smirnov test indicated that the result was robust, and the power exponents were approximately ?2.5. In addition, a paired t-test was conducted, which demonstrated that the rates of different numbers of chronic diseases did not have significant urban-rural differences, time differences or gender differences.

Exploring the Impact of Factors Affecting the Lifespan of HIVs/AIDS Patient’s Survival: An Investigation Using Advanced Statistical Techniques

This study investigates the impact of various factors on the lifespan and diagnostic time of HIV/AIDS patients using advanced statistical techniques. The Power Chris-Jerry (PCJ) distribution is applied to model CD4 counts of patients, and the goodness-of-fit test confirms a strong fit with a p-value of 0.6196. The PCJ distribution is found to be the best fit based on information criteria (AIC and BIC) with the smallest negative log-likelihood, AIC, and BIC values. The study uses datasets from St. Luke hospital Uyo, Nigeria, containing HIV/AIDS diagnosis date, age, CD4 count, gender, and opportunistic infection dates. Multiple linear regression is employed to analyze the relationship between these variables and HIV/AIDS diagnostic time. The results indicate that age, CD4 count, and opportunistic infection significantly impact the diagnostic time, while gender shows a nonsignificant relationship. The F-test confirms the model's overall significance, indicating the factors are good predictors of HIV/AIDS diagnostic time. The R-squared value of approximately 72% suggests that administering antiretroviral therapy (ART) can improve diagnostic time by suppressing the virus and protecting the immune system. Cox proportional hazard modeling is used to examine the effects of predictor variables on patient survival time. Age and CD4 count are not significant factors in the hazard of HIV/AIDS diagnostic time, while opportunistic infection is a significant predictor with a decreasing effect on the hazard rate. Gender shows a strong but nonsignificant relationship with decreased risk of death. To address the violation of the assumption of proportional hazard, the study employs an assumption-free alternative, Aalen’s model. In the Aalen model, all predictor variables except age and gender are statistically significant in relation to HIV/AIDS diagnostic time. The findings provide valuable insights into the factors influencing diagnostic time and survival of HIV/AIDS patients, which can inform interventions aimed at reducing transmission and improving early diagnosis and treatment. The Power Chris-Jerry distribution proves to be a suitable fit for modeling CD4 counts, while multiple linear regression and survival analysis techniques provide insights into the relationships between predictor variables and diagnostic time. These results contribute to the understanding of HIV/AIDS patient outcomes and can guide public health interventions to enhance early detection, treatment, and care.

Exploring the Impact of Factors Affecting the Lifespan of HIVs/AIDS Patient’s Survival: An Investigation Using Advanced Statistical Techniques

This study investigates the impact of various factors on the lifespan and diagnostic time of HIV/AIDS patients using advanced statistical techniques. The Power Chris-Jerry (PCJ) distribution is applied to model CD4 counts of patients, and the goodness-of-fit test confirms a strong fit with a p-value of 0.6196. The PCJ distribution is found to be the best fit based on information criteria (AIC and BIC) with the smallest negative log-likelihood, AIC, and BIC values. The study uses datasets from St. Luke hospital Uyo, Nigeria, containing HIV/AIDS diagnosis date, age, CD4 count, gender, and opportunistic infection dates. Multiple linear regression is employed to analyze the relationship between these variables and HIV/AIDS diagnostic time. The results indicate that age, CD4 count, and opportunistic infection significantly impact the diagnostic time, while gender shows a nonsignificant relationship. The F-test confirms the model's overall significance, indicating the factors are good predictors of HIV/AIDS diagnostic time. The R-squared value of approximately 72% suggests that administering antiretroviral therapy (ART) can improve diagnostic time by suppressing the virus and protecting the immune system. Cox proportional hazard modeling is used to examine the effects of predictor variables on patient survival time. Age and CD4 count are not significant factors in the hazard of HIV/AIDS diagnostic time, while opportunistic infection is a significant predictor with a decreasing effect on the hazard rate. Gender shows a strong but nonsignificant relationship with decreased risk of death. To address the violation of the assumption of proportional hazard, the study employs an assumption-free alternative, Aalen’s model. In the Aalen model, all predictor variables except age and gender are statistically significant in relation to HIV/AIDS diagnostic time. The findings provide valuable insights into the factors influencing diagnostic time and survival of HIV/AIDS patients, which can inform interventions aimed at reducing transmission and improving early diagnosis and treatment. The Power Chris-Jerry distribution proves to be a suitable fit for modeling CD4 counts, while multiple linear regression and survival analysis techniques provide insights into the relationships between predictor variables and diagnostic time. These results contribute to the understanding of HIV/AIDS patient outcomes and can guide public health interventions to enhance early detection, treatment, and care.

应用T-S模糊方法对铁磁谐振过电压的混沌抑制

抑制和控制铁磁谐振过电压对实现智能电网中重要的"自愈"功能具有重要的意义。为此,运用非线性动力学理论于抑制中性点接地系统所发生的具有混沌效应的铁磁谐振。通过分析铁磁谐振电路所表现出的混沌特性,并针对电力系统中参数无法完全已知的限制,首次提出建立谐振系统的T-S模糊模型,制定合适的模糊规则,并应用平行分布补偿法设计模糊控制器来抑制铁磁谐振过电压,以达到迅速控制的良好效果。另外,通过Lya-punov理论验证了该控制器符合系统稳定性要求。仿真结果也验证了该方法的有效性,同时克服了传统方法对参数完全精确已知的限制。

基于B/S模式的用电营配管理系统

针对用电营配管理系统信息量大、数据类型多的特点 ,提出了一种在 B/ S模式下综合查询的解决方案。通过JDBC接口系统与后台 Oracle数据库连接 ,把用电业扩变更申请、电费统计等数据处理技术与基于 B/ S技术的信息查询和发布系统有机结合。在江西省吉安供电局的应用表明 ,该系统用户类别权限划分清晰、数据查询快捷灵活、用户使用方便、功能易于扩展且客户端免维护。

GPSBIIF-1卫星L1频点QPSK VS CASM信号质量评估

为了评估GPS L1频点信号体制转换前后的空间信号质量,基于高增益天线接收系统采集数据,对相干自适应副载波调制(CASM)调制和QPSK调制信号质量进行对比分析。首先,简要介绍CASM调制模型,利用波形匹配技术求解L1频点授权信号伪码序列。其次,基于星座图分布和极大似然估计分别解决出QPSK和CASM调制信号分量功率分配难题。最后定量地利用相关特性参数中的S曲线过零点偏差(SCB)和相关损失(CL)对比分析L1频点信号体制转换前后各信号分量空间信号质量。该文结果可为不同信号体制下空间信号质量评估对比提供参考。

概率论中的幂律分布

幂律分布用于描述个体相互影响的复杂系统中的数量分布规律,是概率论与数理统计学中最重要的分布之一,然而在教学中甚少对其进行详细的介绍.该文将详细讨论幂律分布的定义及性质、常见的幂律分布以及幂律分布的应用,并结合具体实例通过R软件进行数据分析,给出相关教学内容和教学方法的若干建议.

基于S变换的配电网高阻抗故障检测方法研究

采用S变换对配电网高阻抗故障进行仿真与识别,结果表明基于S变换的配电网高阻抗故障检测方法能够快速、准确地区分出配电网高阻抗故障事件和无故障事件。