小电流接地系统中电压互感器烧毁的原因及防止措施

１小电流接地系统中电压互感器烧毁的原因１．１电压互感器低压侧匝间和相间短路，低压熔断器尚未熔断时，此时电压互感器的励磁电流迅速增大，使高压熔断器熔丝熔断或烧毁电压互感器。１．２由于电压互感器二次侧电缆长期暴露在空气中，绝缘老化，而且其老化部位多在互感器的出口端子与电缆穿管之间，这一段电缆因为被去掉外层保护，内芯塑料层易老化剥落致使铜芯裸露。此时此处发生短路后无任何保护，一旦发生短路首先烧毁的是电压互感器。１．３线路发生单相接地时，非接地相对地电压升高，致使电压互感器的铁心饱和，电感量发生变化，在…     

10 kV电压互感器高压侧熔断器熔断故障浅析

在３５ ｋＶ变电站中，常会遇到 １０ ｋＶ电压互感器高压侧熔断器熔断故障。当出现１０ ｋＶ电压互感器高压熔断器连续熔断故障时，必须查明引起熔断器熔断的故障原因，而不得在未查明故障原因情况下再次更换熔丝，继续投人。笔者对其原因谈点看法，供参考。１ １０ ｋＶ电压互感器内部故障 如线圈发生匝间、层间或相间短路及一相接地等故障，都会引起高压熔断器熔断。２ 二次回路故障 当电压互感器的二次回路及设备发生故障时，可能造成电压互感器过电流。若电压互感器的二次侧熔丝选用的额定熔断电流过大，则可能造成一次侧熔断器熔断。…     

电压互感器断线处理措施

请问电压互感器断线时，应如何处理？ 首先考虑电压互感器所带保护与自动装置，防止误动作，再进行检查。检查时应做好安全措施，保证人身安全。检查一、二次侧熔断器是否熔断，如果一次侧熔断器熔断，应查明原因进行更换；如果二次侧熔断器熔断，应立即更换，若再次熔断，应查明原因，不可将熔断器容量增大。如果熔断器完好，可检查电压互感器回路接头有无松动、断头现象，切换回路有无接触不良现象。     

电压互感器多相熔丝熔断分析

110kV天堂变电站10kV系统为中性点不接地系统，2004年6月15日发生10kV母线电压互感器一次侧三相熔丝熔断的故障。事后检查，中性点所接消谐电阻正常，中性点绝缘正常，励磁特性在正常范围，二次回路绝缘正常，更换高压熔丝后，电压互感器又恢复正常运行。雷击时多相熔丝熔断的原因，只有查清雷击时通过高压熔丝的电流，才能了解导致高压熔丝熔断的机理，才能找出有针对性的办法。     

电压互感器损坏故障及异常分析

1故障情况 2006年6月中下旬，晋中地区雷雨天气频繁，对晋中电网输变电设备造成较大危害，其中修文变电站、北郊变电站、介休变电站，先后多次发生35kV电压互感器损坏、电压互感器一次侧熔断器熔断等故障。     

高压限流熔断器接线端帽的改进

目前35kV变电站一次系统中，室外35kV电压互感器和35kV站用变压器一次侧熔断器，通常使用传统的RW10—35型户外高压限流熔断器。该熔断器主要用于电压互感器及站用变压器短路和过载的保护。当高压限流熔断器熔断后，由于本身结构和固定螺栓锈蚀等原因，更换熔体管十分困难。通过更换新型熔断器接线端帽，就可以解决更换熔体管困难带来的难题。     

更换电压互感器高压熔断器的方法

正在日常工作中,变电站内经常会遇到电压互感器高压熔断器熔断的故障。笔者以某110 kV变电站为例,说明更换35 kV电压互感器高压熔断器的的步骤及注意事项,供参考。1电压互感器高压熔断器熔断的征象某110 kV变电站35 kVⅠ段母线电压互感器V相熔断器熔断,熔断器熔断的征象有如下几点。(1)监控中心通知:遥测、遥信的变化,35 kVⅠ段母线V相电压降低。(2)表计指示变化:通过切换电压互感器电压切换开关,切至UV电压降低,切至VW电压降低,切至     

电压互感器熔断器熔断分析

<正>变电站的电压互感器是电力系统不可缺少的电气设备,其作用是为测量仪表、计量及保护装置提供电源。运行中,站内电压互感器的一、二次熔断器经常发生熔断现象。电压互感器一旦不能正常工作,不仅可能会少计量电能量,使保护失去电源造成断路器拒动或误动,还可能导致无法实现二次监控等问题,直接威胁着电网安全运行。如果电压互感器熔断器配置不合适,或接地电流过大、时间过长,     

读者信箱

lan0824问:我局的变电站电压互感器的熔丝经常熔断,给线损考核带来很大的麻烦,请问电压互感器的熔丝熔断的原因是什么?三峡夜曲答:T A的内部故障,包括相间短路,绕组绝缘被破坏,会导致一次侧保险熔断;T A的出口与电网的连接导线短路故障,会导致一次侧保险熔断;二次回路的短路故障会导致二次保险熔断;谐振产生的过电压和大电流也会导致T A保险熔断。根据以上几点可能的原因,可以进行具体分析,如果无短路,T A无故障,很有可能是谐振造成,可以采用具有消谐功能的T A。如果不知道到底是一次熔断还是二次熔断,可以测试一下TA二次回路电流大小,…     

电压互感器高压熔丝频繁熔断故障原因探析

针对余杭电网35 kV母线电压互感器高压熔丝频繁熔断故障,结合变电站母线电压互感器的实际情况,分析故障原因,即:铁磁谐振过电压,导致电压互感器熔丝熔断或损伤;电压互感器二次微机消谐装置误动;因电压互感器熔丝受损或熔断后未同时更换三相熔丝。并提出建议在更换熔丝时,尽量选择三相同时更换的方式,消除熔丝三相不平衡带来的熔断隐患等整改意见,以达到消除故障,提高电网安全稳定运行的目的。     

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)