和谐型机车主变压器渗漏故障处理的研究

电力机车主变压器是和谐型电力机车上的一个至关重要部件,机车主变压器运行的可靠性和持续性是机车的行车安全的首要保证。电力机车主变压器的运行条件相对恶劣。从多年运行的状况来分析,主变压器的故障率虽然不高,但一旦出现故障就会造成很大损失。文章主要从变压器的实际运行情况出发,阐述了变压器的一些常见故障,其中针对主变压器的渗漏问题进行了系统性分析,并提出了渗漏故障的处理方法。     

农村10 kV配电变压器常见故障分析及防范

农村配电变压器损坏时有发生。为了减少配电变压器故障机率、提高农村电网供电可靠性。就配电变压器常见的故障类型及故障原因进行分析,找出避免和解决配电变压器故障的直观方法,提出必须进行变压器特性试验及综合分析,才能准确可靠地找出故障原因。同时,要重视运行前的测试和运行中的维护,以减少变压器的故障机率。     

农村10kV配电变压器常见故障分析及防范

农村配电变压器损坏时有发生。为了减少配电变压器故障机率、提高农村电网供电可靠性,就配电变压器常见的故障类型及故障原因进行分析,找出避免和解决配电变压器故障的直观方法,提出必须进行变压器特性试验及综合分析,才能准确可靠地找出故障原因。同时,要重视运行前的测试和运行中的维护,以减少变压器的故障机率。     

调度值班员如何诊断和处理变压器的故障

变压器是电力系统的重要设备 ,对于电力系统的调度人员或现场运行管理人员来说 ,掌握电力变压器的运行要求和规定 ,准确诊断变压器的故障或事故原因 ,作出恰当的调度措施或现场处理也是提高用户供电可靠性的重要途径之一。主要探讨调查度值班员要掌握电力变压器运行的哪些要求和规定 ,如何诊断和处理变压器的故障     

变压器故障在线监测研究

在电力系统中,变压器是重要的设备之一,对电网的安全有直接的影响。对变压器进行故障分析和在线监测,是监测变压器状态的主要手段。根据在线监测到的变压器状态及相关参数、信号,对故障的位置及发展趋势进行判断,及时采取措施进行处理,防止故障的进一步扩大化,能够有效地提高电网运行的安全性。介绍变压器常见的故障类型,变压器在线检测的优势、研究现状、研究内容及检测方法,以期供有关研究参考。     

关于电力变压器运行维护及故障处理的分析

电力变压器是电力系统中的重要组成部分,直接关系着电压转换过程的安全性与可靠性,一旦其出现故障,不仅会造成供电问题,更会给供电企业带来经济损失.因此,为保障电力系统的顺利稳定运行,在电力变压器运行过程中,相关工作人员应结合其使用年限、设备特征等多方面的因素,合理对变压器进行检查,及时处理其故障.文章简要分析电力变压器在运行过程中容易出现的问题,结合运行维护的意义,重点探讨处理电力变压器故障的方式.     

220kV变电运行的设备故障处理

在对220kV变电运行的设备故障进行分类总结的基础上,通过选取线路故障、变压器故障、母线故障等3个实例,说明变电运行的设备故障处理步骤以及处理过程中相应步骤的注意点,为运维人员在事故处理方面提供参考和借鉴。     

变电站遥视主变压器风扇运转的方法

<正>主变压器是变电站内的主要电气设备,而变压器的冷却系统又是变压器的重要组成部分,当变压器的冷却系统出现故障时,变压器的温度会直线上升,有时会达到100℃以上,严重影响变压器的正常运行,甚至会造成主变压器的损坏。因此,当主变压器冷却系统出现故障,不能对主变压器进行降温时,应该抓紧时间,尽快处理,才能及时消除故障,保证主变压器的安全、稳定运行。1变电站主变压器散热器风扇全停自从2021年7月以来,     

变压器故障在线监测研究

在电力系统中,变压器是重要的设备之一,对电网的安全有直接的影响。对变压器进行故障分析和在线监测,是监测变压器状态的主要手段。根据在线监测到的变压器状态及相关参数、信号,对故障的位置及发展趋势进行判断,及时采取措施进行处理,防止故障的进一步扩大化,能够有效地提高电网运行的安全性。介绍变压器常见的故障类型,变压器在线检测的优势、研究现状、研究内容及检测方法,以期供有关研究参考。     

S_（11）-200/10型10 kV配电变压器电动吊芯检修装置的研制

正1创新背景配电变压器故障目前主要有2种;一是常见轻型故障,如渗漏油或导电杆损坏;二是内部短路故障,如绕组烧毁。对于轻型故障,进行吊芯检修处理可以在最短的时间内进行现场维修,及时解决问题,使配电变压器重新投入运行。     

Relationship between stable carbon isotope discrimination and water use efficiency under regulated deficit irrigation of pear-jujube tree

To investigate the relationship between stable carbon isotope discrimination (Δ) of different organs and water use efficiency (WUE) under different water deficit levels, severe, moderate and low water deficit levels were treated at bud burst to leafing, flowering to fruit set, fruit growth and fruit maturation stages of field grown pear-jujube tree, and leaf stable carbon isotope discrimination (Δ_L) at different growth stages and fruit stable carbon isotope discrimination (Δ_F) at fruit maturation stage were measured. The results indicated that water deficit had significant effect on Δ_L at different growth stages and Δ_F at fruit maturation stage. As compared with full irrigation, the average Δ_L at different growth stages and Δ_F at fruit maturation stage were decreased by 1.23% and 2.67% for different water deficit levels, respectively. Δ_L and Δ_F among different water deficit treatments had significant difference at the same growth stage (P < 0.05). Under different water deficit conditions, significant relationships between the Δ_L and WUE_i (photosynthesis rate/transpiration rate, P_n/T_r), WUE_n (photosynthesis rate/stomatal conductance of CO_2, P_n/g_s), WUE_y (yield/crop water consumption, Y/ET_c) and yield, or between the Δ_F and WUE_y and yield were found, respectively. There were significantly negative correlations of Δ_L with WUE_i, WUE_n, WUE_y and yield (P < 0.01) at the fruit maturation stage, or Δ_L with WUE_i and WUE_n (P < 0.01) over whole growth stage, respectively. Δ_F was negatively correlated with WUE_y, WUE_n and yield (P < 0.05), but positively correlated with ET_c (P < 0.01) over the whole growth stage. Thus Δ_L or Δ_F can compare WUE_n and WUE_y, so the stable carbon isotope discrimination method can be applied to evaluate the water use efficiency of pear-jujube tree under the regulated deficit irrigation.     

Root biomass, crop response and water-yield relationship of mustard (Brassica juncea L.) grown under combinations of irrigation and nutrient application

A 3-year study was carried out to assess the root biomass production, crop growth rate, yield attributes, canopy temperature and water-yield relationships in Indian mustard grown under combinations of irrigation and nutrient application for revealing the dynamic relationship of crop yield (Y) and seasonal evapotranspiration (ET). Three post-sowing irrigation treatments viz. no irrigation (I ₁), one irrigation at flowering (I ₂) and two irrigations one each at rosette and flowering stage (I ₃), three nutrient treatments viz. no fertilizer or manure (F ₁), 100% recommended NPK i.e., 60 kg N, 13.1 kg P and 16.6 kg K ha⁻¹ (F ₂) and 100% recommended NPK plus farmyard manure @ 10 Mg ha⁻¹ (F ₃) were tested in a split-plot design. Root biomass was significantly greater in I ₃ than I ₂ and I ₁, and in F ₃ than F ₂ and F ₁. The I ₃ × F ₃, I ₂ × F ₃ and I ₃ × F ₂ combinations maintained significantly greater crop growth rate, plant height, yield components, ET and crop yield and better plant water status in terms of canopy temperature, canopy-air temperature difference (CATD) and relative leaf water content (RLWC). Number of siliqua plant⁻¹ and seeds siliqua⁻¹ were the major contributors to the seed yield. Marginal analysis of water production function was used to establish Y–ET relationship. The elasticity of water production (E _wp) provides a means to assess relative changes in Y and ET, and gives an indication of improvement of Y due to nutrient application. The ET–Y relationships were linear with marginal water use efficiency (WUE_m) of 3.09, 4.23 and 3.95 kg ha⁻¹ mm⁻¹ in F ₁, F ₂ and F ₃, respectively, and the corresponding E _wp were 0.63, 0.71 and 0.61. This implies that the scope for improving yield and WUE with 100% NPK was little compared with 100% NPK + farmyard manure. The crop yield was highest in I ₃ × F ₃ combination, and the similar yield was obtained in I ₂ × F ₃ and I ₃ × F ₂ combinations. Application of organic manure along with 100% NPK fertilizers maintained greater crop growth rate, better water relation in plants, yield attributes and saved one post-sowing irrigation.     

Midday measurements of leaf water potential and stomatal conductance are highly correlated with daily water use of Thompson Seedless grapevines

A study was conducted to determine the relationship between midday measurements of vine water status and daily water use of grapevines measured with a weighing lysimeter. Water applications to the vines were terminated on August 24th for 9 days and again on September 14th for 22 days. Daily water use of the vines in the lysimeter (ET_LYS) was approximately 40 L vine⁻¹ (5.3 mm) prior to turning the pump off, and it decreased to 22.3 L vine⁻¹ by September 2nd. Pre-dawn leaf water potential (Ψ_PD) and midday Ψ_l on August 24th were −0.075 and −0.76 MPa, respectively, with midday Ψ_l decreasing to −1.28 MPa on September 2nd. Leaf g _s decreased from ~500 to ~200 mmol m⁻² s⁻¹ during the two dry-down periods. Midday measurements of g _s and Ψ_l were significantly correlated with one another (r = 0.96) and both with ET_LYS/ET_o (r = ~0.9). The decreases in Ψ_l, g _s, and ET_LYS/ET_o in this study were also a linear function of the decrease in volumetric soil water content. The results indicate that even modest water stress can greatly reduce grapevine water use and that short-term measures of vine water status taken at midday are a reflection of daily grapevine water use.     

A preliminary study of an alternative controlled drainage strategy in surface drainage ditches: Low-grade weirs

This study examined hydrological characteristics of low-grade weirs, an alternative controlled drainage strategy in surface drainage ditches. Chemographs of vegetated and clear scraped (control) replicates of weir vs. non-weir treatments were compared to determine differences in time to peak (T_p) and time to base (T_b). Drainage ditches T_p and T_b were affected by both vegetation and weir presence. The order of treatment efficiency for T_p was observed to be: non-vegetated non-weir < vegetated non-weir < non-vegetated weir < vegetated weir. Furthermore, T_b for each ditch was the reverse relationship from T_p where vegetated weir > non-vegetated weir > vegetated non-weir > non-vegetated non-weir. Low-grade weirs increase chemical retention time (vegetated and clear scraped), the average time a molecule of contaminant remains in the system. Future research in water quality improvement and weir management will yield useful information for non-point source pollutant reduction.     

Alternative models for predicting the foliage—Air temperature difference of well irrigated wheat under variable meteorological conditions. I. Derivation of parameters II. Accuracy of predictions

Summary One means of using infrared measurements of foliage temperature (T _f ) for scheduling irrigations requires the use of meteorological data to predict the foliage-air temperature difference for a comparable well-watered crop (T _f ^* – T _a ). To determine the best method for making this prediction, parameters for models of increasing complexity for predicting (T _f ^* – T _a ) were derived for wheat using two sets of field data collected in 1982 and 1983.The simplest model with vapor pressure deficit (VPD) as the sole predictor accounted for 64% of observed variance in (T _f ^* – T _a ). The next model with both VPD and net radiation (R _n ) as predictors accounted for 74%. The most complex model predicted (T _f ^* – T _a ) from the crop energy balance. In addition to VPD and R _n it included parameters for the effects of air temperature (T _a ), aerodynamic resistance (r _a ) and the canopy resistance of a well-watered crop (r _cp ) and accounted for 70% of the variance.Accuracy of these alternative models was tested against an independent set of field data collected in 1984. The single variable model with VPD as sole predictor accounted for 17% of the variance in observed values of (T _f ^* – T _a ). This increased to 47% when the effect of R _n was included by using the two variable model and was increased further to 65% when the additional variables of T _a , r _a and r _cp were included by use of the energy balance model. When the complexity of the model was measured by its number of variables there was a close relationship between complexity and the accuracy of the predictions. Reasons for the residual variability are discussed. The need for improved instrumentation for meteorological measurements was indicated.     

Water production functions of wheat (Triticum aestivum L.) irrigated with saline and alkali waters using double-line source sprinkler system

Expected yield losses as a function of quality and quantity of water applied for irrigation are required to formulate guidelines for the effective utilisation of marginal quality waters. In an experiment conducted during 2004-2006, double-line source sprinklers were used to determine the separate and interactive effects of saline and alkali irrigation waters on wheat (Triticum aestivum L.). The study included three water qualities: groundwater (GW; electrical conductivity of water, ECw 3.5 dS m⁻¹; sodium adsorption ratio, SAR 9.8 mmol L⁻¹; residual sodium carbonate, RSC, nil) available at the site, and two synthesized waters, saline (SW; ECw 9.4 dS m⁻¹, SAR 10.3 mmol L⁻¹; RSC nil) and alkali (AW; ECw 3.7 dS m⁻¹, SAR 15.1 mmol L⁻¹; RSC 9.6 meq. L⁻¹). The depths of applied SW, AW, and GW per irrigation ranged from 0.7 to 3.5 cm; the depths of applied mixtures of GW with either SW (MSW) or AW (MAW) ranged from 3.2 to 5 cm. Thereby, the water applied for post-plant irrigations using either of GW, SW or AW ranged between 15.2 and 34.6 cm and 17.1 and 48.1 cm during 2004-2005 and 2005-2006, respectively and the range was 32.1-37.0 and 53.1-60.0 cm for MSW or MAW. Grain yields, when averaged for two years, ranged between 3.08 and 4.36 Mg ha⁻¹, 2.57 and 3.70 Mg ha⁻¹ and 2.73 and 3.74 Mg ha⁻¹ with various quantities of water applied using GW, SW and AW, respectively, and between 3.47 and 3.75 Mg ha⁻¹ and 3.63 and 3.77 Mg ha⁻¹ for MSW and MAW, respectively. The water production functions developed for the two sets of water quality treatments could be represented as: RY = 0.528 + 0.843(WA/OPE) − 0.359(WA/OPE)² − 0.027ECw + 0.44 × 10⁻²(WA/OPE) × ECw for SW (R² = 0.63); RY = 0.446 + 0.816(OPE/WA) − 0.326(WA/OPE)² − 0.0124RSC − 0.55 × 10⁻⁴(WA/OPE) × RSC for AW (R² = 0.56). Here, RY, WA and OPE are the relative yields in reference to the maximum yield obtained with GW, water applied for pre- and post-plant irrigations (cm), and open pan evaporation, respectively. Crop yield increased with increasing amount of applied water for all of the irrigation waters but the maximum yields as obtained with GW, could not be attained even with increased quantities of SW and AW. Increased frequency of irrigation with sprinklers reduced the rate of yield decline with increasing salinity in irrigation water. The sodium contents of plants increased with salinity/alkalinity of sprinkled waters as also with their quantities. Simultaneous decrease in potassium contents resulted in remarkable increase in Na:K ratio.     

Effects of deficit irrigation on the yield and yield components of drip irrigated cotton in a mediterranean environment

A field study on cotton (Gossypium hirsutum L., cv.) was carried out from 2005 to 2008 in the Çukurova Region, Eastern Mediterranean, Turkey. Treatments were designated as I₁₀₀ full irrigation; DI₇₀, DI₅₀ and DI₀₀ which received 70, 50, and 0% of the irrigation water amount applied in the I₁₀₀ treatment. The irrigation water amount to be applied to the plots was calculated using cumulative pan evaporation that occurred during the irrigation intervals. The effect of water deficit or water stress on crop yield and some plant growth parameters such as yield response, water use efficiencies, dry matter yield (DM), leaf area index (LAI) as well as on lint quality components was evaluated. The average seasonal evapotranspiration ranged from 287 ± 15 (DI₀₀) to 584 ± 80 mm (I₁₀₀). Deficit irrigation significantly affected crop yield and all yield components considered in this study. The average seed cotton yield varied from 1369 ± 197 (DI₀₀) to 3397 ± 508 kg ha⁻¹ (I₁₀₀). The average water use efficiency (WUE_ET) ranged from 6.0 ± 1.6 (I₁₀₀) to 4.8 ± 0.9 kg ha⁻¹ mm⁻¹ (DI₀₀), while average irrigation water use efficiency (WUE_I) was between 9.4 ± 3.0 (I₁₀₀) and 14.4 ± 4.8 kg ha⁻¹ mm⁻¹ (DI₅₀). Deficit irrigation increased the harvest index (HI) values from 0.26 ± 0.054 (I₁₀₀) to 0.32 ± 0.052 kg kg⁻¹ (DI₅₀). Yield response factor (Ky) was determined to be 0.98 based on four-year average. Leaf area index (LAI) and dry matter yields (DM) increased with increasing water use. This study demonstrated that the full irrigated treatment (I₁₀₀) should be used for semiarid conditions with no water shortage. However, DI₇₀ treatment needs to be considered as a viable alternative for the development of reduced irrigation strategies in semiarid regions where irrigation water supplies are limited.     

Evapotranspiration and crop coefficient of Populus euphratica Oliv forest during the growing season in the extreme arid region northwest China

Based on successive observation, fifteen-day evapotranspiration (ET_c) of Populus euphratica Oliv forest, in the extreme arid region northwest China, was estimated by application of Bowen ratio-energy balance method (BREB) during the growing season in 2005. During the growing season in 2005, total ET_c was 446.96 mm. From the beginning of growing season, the ET_c increased gradually, and reached its maximum value of 6.724 mm d⁻¹ in the last fifteen days of June. Hereafter the ET_c dropped rapidly, and reached its minimum value of 1.215 mm d⁻¹ at the end of growing season. The variation pattern of crop coefficient (K_c) was similar to that of ET_c. From the beginning of growing season, the K_c value increased rapidly, and reached its maximum value of 0.623 in the last fifteen days of June. Afterward, with slowing growth of P. euphratica, the value dropped rapidly to the end of growing season. According to this study, the ET_c of P. euphratica forest is affected not only by meteorological factors, but by water content in soil.     

Impacts of climate variability on reference evapotranspiration over 58 years in the Haihe river basin of north China

Physically, evaporative demand is driven by net radiation (R_n), vapour pressure (e_a), wind speed (u₂), and air temperature (T_a), each of which changes over time. By analyzing temporal variations in reference evapotranspiration (ET₀), improved understanding of the impacts of climate change on hydrological processes can be obtained. In this study, variations in ET₀ over 58 years (1950-2007) at 34 stations in the Haihe river basin of China were analyzed. ET₀ was calculated by the FAO Penman-Monteith formula. Calculation of Kendall rank coefficient was done by analyzing the annual and seasonal trends in ET₀ derived from its dependent climate variables. Inverse distance weighting (IDW) was used to analyze the spatial variation in annual and seasonal ET₀, and in each climate variable. An attribution analysis was performed to quantify the contribution of each input variable to ET₀ variation. The results showed that ET₀ gradually decreased in the whole basin over the 58 years at a rate of −1.0 mm yr⁻², at the same time, R_n, u₂ and precipitation also decreased. Changes in ET₀ were attributed to the variations in net radiation (−0.9 mm yr⁻²), vapour pressure (−0.5 mm yr⁻²), wind speed (−1.3 mm yr⁻²) and air temperature (1.7 mm yr⁻²). Looking at all data on a month by month basis, we found that T_a had a positive effect on dET₀/dt (the derivative of reference evapotranspiration to time) and R_n and u₂ had negative effects on dET₀/dt. While changes in air temperature were found to produce a large increase in dET₀/dt, changes in other key variables each reduced rates, resulting in an overall negative trend in dET₀/dt.     

The effect of soil surface temperature on the crop water stress index

Summary A coupled soil-vegetation energy balance model which treats the canopy foliage as one layer and the soil surface as another layer was validated againt a set of field data and compared with a single-layer model of a vegetation canopy. The two-layer model was used to predict the effect of increases in soil surface temperature (T _s ) due to the drying of the soil surface, on the vegetation temperature (T _v ). In the absence of any change in stomatal resistance the impact of soil surface drying on the Crop Water Stress Index (CSWI) calculated from T _v was predicted. Field data came from a wheat crop growing on a frequently irrigated plot (W) and a plot left un watered (D) until the soil water depletion reached 100 mm. Vegetation and soil surface temperatures were measured by infrared thermometers from tillering to physiological maturity, with meteorological variables recorded simultaneously. Stomatal resistances were measured with a diffusion porometer intensively over five days when the leaf area index was between 5 and 8. The T _v predicted by the single-layer and the two-layer models accounted for 87% and 88% of the variance of measured values respectively, and both regression lines were close to the 11 relationship. Study of the effect of T _s on the CWSI with the two-layer model indicated that the CWSI was sensitive to changes in T _s . The overestimation of crop water stress calculated from the CWSI was predicted to be greater at low leaf area indices and high levels of stomatal resistance. The implications for this bias when using the CWSI for irrigation scheduling are discussed.List of Symbols C Sensible heat flux from the soil-vegetation system (W m^–2) - c _{l shade} Mean stomatal conductance of the shaded leaf area (m s^–1) - c _{l sun} Mean stomatal conductance of the sunlit leaf area (m s^–1) - c _max Maximum stomatal conductance (m s^–1) - c ₀ Minimum stomatal conductance (m s^–1) - C _p Specific heat at constant pressure (J kg^–1 °C^–1) - C _s Sensible heat flux from the soil (W m^–2) - C _v Sensible heat flux from the vegetation (W m^–2) - c _v Bulk stomatal conductance of the vegetation (m s^–1) - CWSI Crop Water Stress Index (dimensionless) - e _a Vapor pressure at the reference height (kPa) - e _b Vapor pressure at the virtual source/sink height of heat exchange (kPa) - e ₀ ^* Saturated vapor pressure at T ₀ (kPa) - e _s Vapor pressure at the soil surface (kPa) - e _v ^* Saturated vapor pressure at T _v (kPa) - G Soil heat flux (Wm^–2) - GLAI Green leaf area index (dimensionless) - GLAI_shade Green shaded leaf area index (dimensionless) - GLAI_sun Green sunlit leaf area index (dimensionless) - k Extinction coefficient for photosynthetically active radiation (dimensionless) - k ₁ Damping exponent for Eq. A 5 (m² W^–1) - LAI Leaf area index (dimensionless) - LE Latent heat flux from the soil-vegetation system (W m^–2) - LE _s Latent heat flux from the soil (W m^–2) - LE _v Latent heat flux from the vegetation (W m^–2) - p _a Density of air (kg m^–3) - PAR_a Photosynthetically active radiation above the canopy (W m^–2) - PAR_u Photosynthetically active radiation under the canopy (W m^–2) - r _a Aerodynamic resistance (s m^–1) - r _b Heat exchange resistance between the vegetation and the adjacent air boundary layer (s m^–1) - r _c Bulk stomatal resistance of the vegetation (s m^–1) - R _n Net radiation above the canopy (W m^–2) - R _s Net radiation flux at the soil surface (W m^–2) - r _st Mean stomatal resistance of leaves in the canopy (s m^–1) - R _v Net radiation absorbed by the vegetation (W m^–2) - r _w Heat exchange resistance between the soil surface and the boundary layer (s m^–1) - S Photosynthetically active radiation on the shaded leaves (W m^–2) - S _d Diffuse photosynthetically active radiation (W m ^–2) - S ₀ Photosynthetically active radiation on a surface perpendicular to the beams (W m^–2) - T _a Air temperature at the reference height (°C) - T _b Temperature at the virtual source/sink height of heat exchange (°C) - T ₀ Aerodynamic temperature (°C) - T _s Soil surface temperature (°C) - T _v Vegetation temperature (°C) - w ₀ Single scattering albedo (dimensionless) - Psychrometric constant (kPa °C) - ₀ Cosine of solar zenith angle (dimensionless)