The Design and Evolution of TurboTurtle, a Collaborative Microworld for Exploring Newtonian

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turbocor 发展史

turbocor 发展史
Making a world of difference. 9
The advantages of the Turbocor technology
Oil free technology
Typical screw water-cooled chiller Oil-free water-cooled chiller
• • • • • • •
Eliminate oil film on heat transfer surfaces Eliminate stacking of oil in evaporator at lower loads No disposal required No oil heater and cooler No oil separator No oil pump, oil solenoid valves, oil filter No oil pressure transducer Simplify application and reduce cost
2008 Institute of Refrigeration – England J&E Hall Gold Medal
2005 Natural Resource Canada – Canada Energy Innovation Award
2004 Environmental Protection Agency – USA Climate Protection Award Danfoss Turbocor is certified Danfoss Turbocor is certified: ISO 9001:2000 ISO 9001:2000
2006 Frost & Sullivan - USA Technology Leadership of the Year Award

双U型地埋管换热器换热性能模拟分析

双U型地埋管换热器换热性能模拟分析

第52卷第6期2021年6月中南大学学报(自然科学版)Journal of Central South University (Science and Technology)V ol.52No.6Jun.2021双U 型地埋管换热器换热性能模拟分析杨培志1,陈嘉鹏1,陈君文2,李明3(1.中南大学能源科学与工程学院,湖南长沙,410083;2.中航长沙设计研究院有限公司,湖南长沙,410014;3.湖南凌天科技有限公司,湖南湘潭,410005)摘要:针对垂直双U 型地埋管换热器,在MATLAB 平台上建立热渗耦合作用下地埋管换热器的三维数值传热模型,并通过岩土热响应试验验证该模型的正确性。

基于建立的三维数值传热模型,分析U 型管内水流速度、回填材料热物性参数、地下水渗流速度及地下水水位对地埋管换热器换热性能的影响。

研究结果表明:当U 型管内水流速度从0.1m/s 增大到0.2m/s 时,可以明显提高地埋管换热器的换热性能;与增大导热系数相比,增大容积比热对提升地埋管换热器换热性能不明显;当地下水渗流速度从0m/a 增大到35m/a 时,地埋管换热器与土壤的换热效果明显;地下水位对地埋管换热器换热性能有较大影响。

关键词:地埋管换热器;三维数值传热模型;地下水渗流;岩土热响应试验中图分类号:TK52文献标志码:A文章编号:1672-7207(2021)06-1733-06Simulation and analysis of heat transfer performance of doubleU-tube ground heat exchangersYANG Peizhi 1,CHEN Jiapeng 1,CHEN Junwen 2,LI Ming 3(1.School of Energy Science and Engineering,Central South University,Changsha 410083,China;2.China Aviation Changsha Design and Research Co.Ltd.,Changsha 410014,China;3.Hunan Linten Science and Technology Co.Ltd.,Xiangtan 410005,China)Abstract:A three-dimensional numerical model of double U-tube ground heat exchangers (GHEs)was presented with heat transfer and groundwater seepage in MATLAB platform,which was verified by rock-soil thermal response test.Based on the established three-dimensional numerical heat transfer model,the influence of flow rate of U-shaped tube,thermophysical properties of grout,seepage flow rate and groundwater level on heat exchange performance of GHEs was analyzed.The results show that when U-tube water flow rate is from 0.1m/s to 0.2m/s,DOI:10.11817/j.issn.1672-7207.2021.06.001收稿日期:2021−01−10;修回日期:2021−03−15基金项目(Foundation item):国家自然科学基金面上资助项目(51276226)(Project(51276226)supported by the National NaturalScience Foundation of China)通信作者:杨培志,博士,副教授,从事制冷与空调技术的开发及应用研究;E-mail:*******************.cn引用格式:杨培志,陈嘉鹏,陈君文,等.双U 型地埋管换热器换热性能模拟分析[J].中南大学学报(自然科学版),2021,52(6):1733−1738.Citation:YANG Peizhi,CHEN Jiapeng,CHEN Junwen,et al.Simulation and analysis of heat transfer performance of double U-tube ground heat exchangers[J].Journal of Central South University(Science and Technology),2021,52(6):1733−1738.第52卷中南大学学报(自然科学版)the heat transfer performance of the buried tube heat exchanger can significantly be improved.Increasing the volume specific heat to enhance the heat transfer performance of buried tube heat exchanger is not obvious compared to increasing the thermal conductivity.When groundwater percolation rate is from0m/a to35m/a,the buried tube heat exchanger with soil′s heat transfer effect is obvious.The depth of the groundwater level on the buried tube heat exchanger has greater impact on the heat transfer performance.Key words:ground heat exchangers;3D numerical model;groundwater seepage;rock-soil thermal response test随着全球能源与环境问题的日益突出,能源的高效利用与环保已经越来越受到人们的重视。

Turbomachinery Design and Theory_ch5

Turbomachinery Design and Theory_ch5

5Axial Flow Compressors and Fans5.1INTRODUCTIONAs mentioned in Chapter4,the maximum pressure ratio achieved in centrifugal compressors is about4:1for simple machines(unless multi-staging is used)at an efficiency of about70–80%.The axialflow compressor,however,can achieve higher pressures at a higher level of efficiency.There are two important characteristics of the axialflow compressor—high-pressure ratios at good efficiency and thrust per unit frontal area.Although in overall appearance,axial turbines are very similar,examination of the blade cross-section will indicate a big difference.In the turbine,inlet passage area is greater than the outlet.The opposite occurs in the compressor,as shown in Fig.5.1.Thus the process in turbine blades can be described as an acceleratingflow, the increase in velocity being achieved by the nozzle.However,in the axialflow compressor,theflow is decelerating or diffusing and the pressure rise occurs when thefluid passes through the blades.As mentioned in the chapter on diffuser design(Chapter4,Sec.4.7),it is much more difficult to carry out efficient diffusion due to the breakaway of air molecules from the walls of the diverging passage.The air molecules that break away tend to reverse direction andflow back in the direction of the pressure gradient.If the divergence is too rapid,this may result in the formation of eddies and reduction in useful pressure rise.During acceleration in a nozzle,there is a natural tendency for the air tofill the passagewalls closely (only the normal friction loss will be considered in this case).Typical blade sections are shown in Fig.5.2.Modern axial flow compressors may give efficiencies of 86–90%—compressor design technology is a well-developed field.Axial flow compressors consist of a number of stages,each stage being formed by a stationary row and a rotating row of blades.Figure 5.3shows how a few compressor stages are built into the axial compressor.The rotating blades impart kinetic energy to the air while increasing air pressure and the stationary row of blades redirect the air in the proper direction and convert a part of the kinetic energy into pressure.The flow of air through the compressor is in the direction of the axis of the compressor and,therefore,it is called an axial flow compressor.The height of the blades is seen to decrease as the fluid moves through the compressor.As the pressure increases in the direction of flow,the volume of air decreases.To keep the air velocity the same for each stage,the blade height is decreased along the axis of the compressor.An extra row of fixed blades,called the inlet guide vanes,is fitted to the compressor inlet.These are provided to guide the air at the correct angle onto the first row of moving blades.In the analysis of the highly efficient axial flow compressor,the 2-D flow through the stage is very important due to cylindricalsymmetry.Figure 5.1Cutaway sketch of a typical axial compressor assembly:the General Electric J85compressor.(Courtesy of General Electric Co.)Figure 5.3Schematic of an axial compressorsection.Figure 5.2Compressor and turbine blade passages:turbine and compressor housing.Theflow is assumed to take place at a mean blade height,where the blade peripheral velocities at the inlet and outlet are the same.Noflow is assumed in the radial direction.5.2VELOCITY DIAGRAMThe basic principle of axial compressor operation is that kinetic energy is imparted to the air in the rotating blade row,and then diffused through passages of both rotating and stationary blades.The process is carried out over multiple numbers of stages.As mentioned earlier,diffusion is a deceleration process.It is efficient only when the pressure rise per stage is very small.The blading diagram and the velocity triangle for an axialflow compressor stage are shown in Fig.5.4.Air enters the rotor blade with absolute velocity C1at an angle a1measured from the axial direction.Air leaves the rotor blade with absolute velocity C2at an angle a2.Air passes through the diverging passages formed between the rotor blades.As work is done on the air in the rotor blades,C2is larger than C1.The rotor row has tangential velocity bining the two velocity vectors gives the relative velocity at inlet V1at an angle b1.V2is the relative velocity at the rotor outlet.It is less than V1,showing diffusion of the relative velocity has taken place with some static pressure rise across the rotor blades.Turning of the air towards the axial direction is brought about by the camber of the blades.Euler’s equationFigure5.4Velocity diagrams for a compressor stage.provides the work done on the air:W c¼UðC w22C w1Þð5:1ÞUsing the velocity triangles,the following basic equations can be written:UC a¼tan a1þtan b1ð5:2ÞUC a¼tan a2þtan b2ð5:3Þin which C a¼C a1¼C2is the axial velocity,assumed constant through the stage. The work done equation[Eq.(5.1)]may be written in terms of air angles: W c¼UC aðtan a22tan a1Þð5:4Þalso,W c¼UC aðtan b12tan b2Þð5:5ÞThe whole of this input energy will be absorbed usefully in raising the pressure and velocity of the air and for overcoming various frictional losses.Regardless of the losses,all the energy is used to increase the stagnation temperature of the air,K T0s. If the velocity of air leaving thefirst stage C3is made equal to C1,then the stagnation temperature rise will be equal to the static temperature rise,K T s.Hence:T0s¼D T s¼UC aC pðtan b12tan b2Þð5:6ÞEquation(5.6)is the theoretical temperature rise of the air in one stage.In reality, the stage temperature rise will be less than this value due to3-D effects in the compressor annulus.Tofind the actual temperature rise of the air,a factor l,which is between0and100%,will be used.Thus the actual temperature rise of the air is given by:T0s¼l UC aC pðtan b12tan b2Þð5:7ÞIf R s is the stage pressure ratio and h s is the stage isentropic efficiency,then:R s¼1þh s D T0sT01!g=g21ðÞð5:8Þwhere T01is the inlet stagnation temperature.5.3DEGREE OF REACTIONThe degree of reaction,L ,is defined as:L ¼Static enthalpy rise in the rotorStatic enthalpy rise in the whole stage ð5:9ÞThe degree of reaction indicates the distribution of the total pressure rise into the two types of blades.The choice of a particular degree of reaction is important in that it affects the velocity triangles,the fluid friction and other losses.Let:D T A ¼the static temperature rise in the rotorD T B ¼the static temperature rise in the statorUsing the work input equation [Eq.(5.4)],we get:W c ¼C p ðD T A þD T B Þ¼D T S ¼UC a ðtan b 12tan b 2Þ¼UC a ðtan a 22tan a 1Þ)ð5:10ÞBut since all the energy is transferred to the air in the rotor,using the steady flow energy equation,we have:W c ¼C p D T A þ12ðC 222C 21Þð5:11ÞCombining Eqs.(5.10)and (5.11),we get:C pD T A ¼UC a ðtan a 22tan a 1Þ212ðC 222C 21Þfrom the velocity triangles,C 2¼C a cos a 2and C 1¼C a cos a 1Therefore,C pD T A ¼UC a ðtan a 22tan a 1Þ212C 2a ðsec 2a 22sec 2a 1Þ¼UC a ðtan a 22tan a 1Þ212C 2a ðtan 2a 22tan 2a 1ÞUsing the definition of degree of reaction,L ¼D T AD T A þD T B ¼UC a ðtan a 22tan a 1Þ212C 2a ðtan 2a 22tan 2a 1ÞUC a ðtan a 22tan a 1Þ¼12Ca U ðtan a 2þtan a 1ÞBut from the velocity triangles,adding Eqs.(5.2)and(5.3), 2UC a¼ðtan a1þtan b1þtan a2þtan b2ÞTherefore,L¼C a2U2UC a22UC aþtan b1þtan b2¼C a2Uðtan b1þtan b2Þð5:12ÞUsually the degree of reaction is set equal to50%,which leads to this interesting result:ðtan b1þtan b2Þ¼U C a :Again using Eqs.(5.1)and(5.2),tan a1¼tan b2;i:e:;a1¼b2tan b1¼tan a2;i:e:;a2¼b1As we have assumed that C a is constant through the stage,C a¼C1cos a1¼C3cos a3:Since we know C1¼C3,it follows that a1¼a3.Because the angles are equal, a1¼b2¼a3,and b1¼a2.Under these conditions,the velocity triangles becomesymmetric.In Eq.(5.12),the ratio of axial velocity to blade velocity is called the flow coefficient and denoted by F.For a reaction ratio of50%, (h22h1)¼(h32h1),which implies the static enthalpy and the temperature increase in the rotor and stator are equal.If for a given value of C a=U,b2is chosen to be greater than a2(Fig.5.5),then the static pressure rise in the rotor is greaterthan the static pressure rise in the stator and the reaction is greater than50%.Figure5.5Stage reaction.Conversely,if the designer chooses b 2less than b 1,the stator pressure rise will be greater and the reaction is less than 50%.5.4STAGE LOADINGThe stage-loading factor C is defined as:C ¼W c mU ¼h 032h 01U ¼l ðC w22C w1ÞU ¼l C a Uðtan a 22tan a 1ÞC ¼lF ðtan a 22tan a 1Þð5:13Þ5.5LIFT-AND-DRAG COEFFICIENTSThe stage-loading factor C may be expressed in terms of the lift-and-drag coefficients.Consider a rotor blade as shown in Fig.5.6,with relative velocity vectors V 1and V 2at angles b 1and b 2.Let tan ðb m Þ¼ðtan ðb 1Þþtan ðb 2ÞÞ/2.The flow on the rotor blade is similar to flow over an airfoil,so lift-and-drag forces will be set up on the blade while the forces on the air will act on the opposite direction.The tangential force on each moving blade is:F x ¼L cos b m þD sin b m F x ¼L cos b m 1þC D C Ltan b m !ð5:14Þwhere:L ¼lift and D ¼drag.Figure 5.6Lift-and-drag forces on a compressor rotor blade.The lift coefficient is defined as:C L¼L0:5r V m Að5:15Þwhere the blade area is the product of the chord c and the span l.Substituting V m¼C acos b minto the above equation,F x¼r C2aclC L2sec b m1þC DC Ltan b m!ð5:16ÞThe power delivered to the air is given by:UF x¼m h032h01ðÞ¼r C a ls h032h01ðÞð5:17Þconsidering theflow through one blade passage of width s.Therefore,¼h032h01U¼F x r C a lsU¼12C aUcssec b mðC LþC D tan b mÞ¼12cssec b mðC LþC D tan b mÞð5:18ÞFor a stage in which b m¼458,efficiency will be maximum.Substituting this back into Eq.(5.18),the optimal blade-loading factor is given by:C opt¼wffiffiffi2pcsC LþC DðÞð5:19ÞFor a well-designed blade,C D is much smaller than C L,and therefore the optimal blade-loading factor is approximated by:C opt¼wffiffiffi2pcsC Lð5:20Þ5.6CASCADE NOMENCLATUREAND TERMINOLOGYStudying the2-Dflow through cascades of airfoils facilitates designing highly efficient axialflow compressors.A cascade is a row of geometrically similar blades arranged at equal distance from each other and aligned to theflow direction. Figure5.7,which is reproduced from Howell’s early paper on cascade theory and performance,shows the standard nomenclature relating to airfoils in cascade.a 10and a 20are the camber angles of the entry and exit tangents the camber line makes with the axial direction.The blade camber angle u ¼a 012a 02.The chord c is the length of the perpendicular of the blade profile onto the chord line.It is approximately equal to the linear distance between the leading edge and the trailing edge.The stagger angle j is the angle between the chord line and the axial direction and represents the angle at which the blade is set in the cascade.The pitch s is the distance in the direction of rotation between corresponding points on adjacent blades.The incidence angle i is the difference between the air inlet angle (a 1)and the blade inlet angle a 01ÀÁ.That is,i ¼a 12a 01.The deviation angle (d )is the difference between the air outlet angle (a 2)and the blade outlet angle a 02ÀÁ.The air deflection angle,1¼a 12a 2,is the difference between the entry and exit air angles.A cross-section of three blades forming part of a typical cascade is shown in Fig.5.7.For any particular test,the blade camber angle u ,its chord c ,and the pitch (or space)s will be fixed and the blade inlet and outlet angles a 01and a 02are determined by the chosen setting or stagger angle j .The angle of incidence,i ,is then fixed by the choice of a suitable air inlet angle a 1,since i ¼a 12a 01.An appropriate setting of the turntable on which the cascade is mounted can accomplish this.With the cascade in this position the pressure and direction measuring instruments are then traversed along the blade row in the upstream and downstream position.The results of the traverses are usually presented asshownFigure 5.7Cascade nomenclature.in Fig.5.8.The stagnation pressure loss is plotted as a dimensionless number given by:Stagnation pressure loss coefficient ¼P 012P 020:5r C 1ð5:21ÞThis shows the variation of loss of stagnation pressure and the air deflection,1¼a 12a 2,covering two blades at the center of the cascade.The curves of Fig.5.8can now be repeated for different values of incidence angle,and the whole set of results condensed to the form shown in Fig.5.9,in which the mean loss and mean deflection are plotted against incidence for a cascade of fixed geometrical form.The total pressure loss owing to the increase in deflection angle of air is marked when i is increased beyond a particular value.The stalling incidence of the cascade is the angle at which the total pressure loss is twice the minimum cascade pressure loss.Reducing the incidence i generates a negative angle of incidence at which stalling will occur.Knowing the limits for air deflection without very high (more than twice the minimum)total pressure loss is very useful for designers in the design of efficient compressors.Howell has defined nominal conditions of deflectionforFigure 5.8Variation of stagnation pressure loss and deflection for cascade at fixed incidence.a cascade as 80%of its stalling deflection,that is:1*¼0:81s ð5:22Þwhere 1s is the stalling deflection and 1*is the nominal deflection for the cascade.Howell and Constant also introduced a relation correlating nominal deviation d *with pitch chord ratio and the camber of the blade.The relation is given by:d *¼m u s ln ð5:23ÞFor compressor cascade,n ¼12,and for the inlet guide vane in front of the compressor,n ¼1.Hence,for a compressor cascade,nominal deviation is given by:d *¼m u s l12ð5:24ÞThe approximate value suggested by Constant is 0.26,and Howell suggested a modified value for m :m ¼0:232a l 2þ0:1a *250ð5:25Þwhere the maximum camber of the cascade airfoil is at a distance a from the leading edge and a *2is the nominal air outletangle.Figure 5.9Cascade mean deflection and pressure loss curves.Then,a* 2¼b2þd*¼b2þm us1and,a*12a*2¼1* or:a* 1¼a*2þ1*Also,i*¼a*12b1¼a*2þ1*2b15.73-D CONSIDERATIONSo far,all the above discussions were based on the velocity triangle at one particular radius of the blading.Actually,there is a considerable difference in the velocity diagram between the blade hub and tip sections,as shown in Fig.5.10.The shape of the velocity triangle will influence the blade geometry,and, therefore,it is important to consider this in the design.In the case of a compressor with high hub/tip ratio,there is little variation in blade speed from root to tip.The shape of the velocity diagram does not change much and,therefore,little variation in pressure occurs along the length of the blade.The blading is of the same section at all radii and the performance of the compressor stage is calculated from the performance of the blading at the mean radial section.Theflow along the compressor is considered to be2-D.That is,in2-Dflow only whirl and axial flow velocities exist with no radial velocity component.In an axialflow compressor in which high hub/tip radius ratio exists on the order of0.8,2-Dflow in the compressor annulus is a fairly reasonable assumption.For hub/tip ratios lower than0.8,the assumption of two-dimensionalflow is no longer valid.Such compressors,having long blades relative to the mean diameter,have been used in aircraft applications in which a high massflow requires a large annulus area but a small blade tip must be used to keep down the frontal area.Whenever thefluid has an angular velocity as well as velocity in the direction parallel to the axis of rotation,it is said to have“vorticity.”Theflow through an axial compressor is vortexflow in nature.The rotatingfluid is subjected to a centrifugal force and to balance this force,a radial pressure gradient is necessary.Let us consider the pressure forces on afluid element as shown in Fig.5.10.Now,resolvethe forces in the radial direction Fig.5.11:d u ðP þd P Þðr þd r Þ2Pr d u 22P þd P 2 d r d u 2¼r d r r d u C 2wrð5:26Þor ðP þd P Þðr þd r Þ2Pr 2P þd P 2 d r ¼r d r C 2w where:P is the pressure,r ,the density,C w ,the whirl velocity,r ,the radius.After simplification,we get the following expression:Pr þP d r þr d P þd P d r 2Pr þr d r 212d P d r ¼r d r C 2w or:r d P ¼r d r C 2wFigure 5.10Variation of velocity diagram along blade.That is,1 r d Pd r¼C2wrð5:27ÞThe approximation represented by Eq.(5.27)has become known as radial equilibrium.The stagnation enthalpy h0at any radius r where the absolute velocity is C may be rewritten as:h0¼hþ12C2aþ12C2w;h¼c p T;and C2¼C2aþC2wÀÁDifferentiating the above equation w.r.t.r and equating it to zero yields:d h0 d r ¼gg21£1rd Pd rþ120þ2C wd C wd rFigure5.11Pressure forces on afluid element.or:g 21£1d Pd rþC wd C wd r¼0Combining this with Eq.(5.27):g g21C2wrþC wd C wd r¼0or:d C w d r ¼2g21C wrSeparating the variables,d C w C w ¼2gg21d rrIntegrating the above equationR d C w C w ¼2g21Zd rr2g21ln C w r¼c where c is a constant:Taking antilog on both sides,gg21£C w£r¼e cTherefore,we haveC w r¼constantð5:28ÞEquation(5.28)indicates that the whirl velocity component of theflow varies inversely with the radius.This is commonly known as free vortex.The outlet blade angles would therefore be calculated using the free vortex distribution.5.8MULTI-STAGE PERFORMANCEAn axialflow compressor consists of a number of stages.If R is the overall pressure ratio,R s is the stage pressure ratio,and N is the number of stages,then the total pressure ratio is given by:R¼ðR sÞNð5:29ÞEquation(5.29)gives only a rough value of R because as the air passes through the compressor the temperature rises continuously.The equation used tofind stage pressure is given by:R s ¼1þh s D T 0s T 01 !g g 21ð5:30ÞThe above equation indicates that the stage pressure ratio depends only on inlet stagnation temperature T 01,which goes on increasing in the successive stages.To find the value of R ,the concept of polytropic or small stage efficiency is very useful.The polytropic or small stage efficiency of a compressor is given by:h 1;c ¼g 21gn n 21 or:n n 21 ¼h s g g 21where h s ¼h 1,c ¼small stage efficiency.The overall pressure ratio is given by:R ¼1þN D T 0s T 01 !n n 21ð5:31ÞAlthough Eq.(5.31)is used to find the overall pressure ratio of a compressor,in actual practice the step-by-step method is used.5.9AXIAL FLOW COMPRESSORCHARACTERISTICSThe forms of characteristic curves of axial flow compressors are shown in Fig. 5.12.These curves are quite similar to the centrifugal compressor.However,axial flow compressors cover a narrower range of mass flow than the centrifugal compressors,and the surge line is also steeper than that of a centrifugal compressor.Surging and choking limit the curves at the two ends.However,the surge points in the axial flow compressors are reached before the curves reach a maximum value.In practice,the design points is very close to the surge line.Therefore,the operating range of axial flow compressors is quite narrow.Illustrative Example 5.1:In an axial flow compressor air enters the compressor at stagnation pressure and temperature of 1bar and 292K,respectively.The pressure ratio of the compressor is 9.5.If isentropic efficiency of the compressor is 0.85,find the work of compression and the final temperature at the outlet.Assume g ¼1.4,and C p ¼1.005kJ/kg K.Solution:T01¼292K;P01¼1bar;h c¼0:85:Using the isentropic P–T relation for compression processes,P02 P01¼T002T01!gg21where T020is the isentropic temperature at the outlet.Therefore,T002¼T01P02P01!g21g¼292ð9:5Þ0:286¼555:92KNow,using isentropic efficiency of the compressor in order tofind the actual temperature at the outlet,T02¼T01þT0022T01ÀÁc¼292þ555:922292ðÞ¼602:49K Figure5.12Axialflow compressor characteristics.Work of compression:W c¼C pðT022T01Þ¼1:005ð602:492292Þ¼312kJ/kg Illustrative Example5.2:In one stage of an axialflow compressor,the pressure ratio is to be1.22and the air inlet stagnation temperature is288K.If the stagnation temperature rise of the stages is21K,the rotor tip speed is200m/s,and the rotor rotates at4500rpm,calculate the stage efficiency and diameter of the rotor.Solution:The stage pressure ratio is given by:R s¼1þh s D T0sT01!gg21or1:22¼1þh sð21Þ288!3:5that is,h s¼0:8026or80:26% The rotor speed is given by:U¼p DN60;or D¼ð60Þð200Þpð4500Þ¼0:85mIllustrative Example5.3:An axialflow compressor has a tip diameter of 0.95m and a hub diameter of0.85m.The absolute velocity of air makes an angle of288measured from the axial direction and relative velocity angle is568.The absolute velocity outlet angle is568and the relative velocity outlet angle is288. The rotor rotates at5000rpm and the density of air is1.2kg/m3.Determine:1.The axial velocity.2.The massflow rate.3.The power required.4.Theflow angles at the hub.5.The degree of reaction at the hub.Solution:1.Rotor speed is given by:U¼p DN60¼pð0:95Þð5000Þ60¼249m/sBlade speed at the hub:U h ¼p D h N 60¼p ð0:85Þð5000Þ60¼223m /s From the inlet velocity triangle (Fig.5.13),tan a 1¼C w1C a and tan b 1¼U 2C w1ðÞC aAdding the above two equations:U C a¼tan a 1þtan b 1or:U ¼C a ðtan 288þtan 568Þ¼C a ð2:0146ÞTherefore,C a ¼123.6m/s (constant at all radii)2.The mass flow rate:_m ¼p ðr 2t 2r 2hÞr C a ¼p ð0:475220:4252Þð1:2Þð123:6Þ¼20:98kg /s3.The power required per unit kg for compression is:W c ¼l UC a ðtan b 12tan b 2Þ¼ð1Þð249Þð123:6Þðtan 5682tan 288Þ1023¼ð249Þð123:6Þð1:48320:53Þ¼29:268kJ /kgFigure 5.13Inlet velocity triangle.The total power required to drive the compressor is:W c¼_mð29:268Þ¼ð20:98Þð29:268Þ¼614kW4.At the inlet to the rotor tip:C w1¼C a tan a1¼123:6tan288¼65:72m/sUsing free vortex condition,i.e.,C w r¼constant,and using h as the subscript for the hub,C w1h¼C w1t r tr h¼ð65:72Þ0:4750:425¼73:452m/sAt the outlet to the rotor tip,C w2t¼C a tan a2¼123:6tan568¼183:24m/s Therefore,C w2h¼C w2t r tr h¼ð183:24Þ0:4750:425¼204:8m/sHence theflow angles at the hub:tan a1¼C w1hC a¼73:452123:6¼0:594or;a1¼30:728tan b1¼U hðÞC a2tan a1¼223123:620:5942¼1:21i.e.,b1¼50.438tan a2¼C w2ha¼204:8¼1:657i.e.,a2¼58.898tan b2¼U hðÞC a2tan a2¼223123:62tan58:598¼0:1472i.e.,b2¼8.3785.The degree of reaction at the hub is given by:L h¼C a2U hðtan b1þtan b2Þ¼123:6ð2Þð223Þðtan50:438þtan8:378Þ¼123:6ð2Þð223Þð1:21þ0:147Þ¼37:61%Illustrative Example5.4:An axialflow compressor has the following data:Blade velocity at root:140m/sBlade velocity at mean radius:185m/sBlade velocity at tip:240m/sStagnation temperature rise in this stage:15KAxial velocityðconstant from root to tipÞ:140m/sWork done factor:0:85Degree of reaction at mean radius:50%Calculate the stage air angles at the root,mean,and tip for a free vortex design.Solution:Calculation at mean radius:From Eq.(5.1),W c¼U(C w22C w1)¼U K C wor:C pðT022T01Þ¼C pD T0s¼l U D C wSo:D C w¼C p D T0sl U¼ð1005Þð15Þð0:85Þð185Þ¼95:87m/sSince the degree of reaction(Fig.5.14)at the mean radius is50%,a1¼b2 and a2¼b1.From the velocity triangle at the mean,U¼D C wþ2C w1or:C w1¼U2D C w2¼185295:872¼44:57m/sHence,tan a1¼C w1C a¼44:57140¼0:3184that is,a1¼17:668¼b2andtan b1¼D C wþC w1ðÞC a¼95:87þ44:57ðÞ140¼1:003i.e.,b1¼45:098¼a2Calculation at the blade tip:Using the free vortex diagram(Fig.5.15),ðD C w£UÞt¼ðD C w£UÞm Therefore,D C w¼ð95:87Þð185Þ240¼73:9m/sWhirl velocity component at the tip:C w1£240¼ð44:57Þð185ÞTherefore:C w1¼ð44:57Þð185Þ240¼34:36m/stan a1¼C w1C a¼34:36140¼0:245Figure5.14Velocity triangle at the mean radius.。

燃气轮机高速动力涡轮气动设计及试验

燃气轮机高速动力涡轮气动设计及试验

燃气轮机高速动力涡轮气动设计及试验张剑;曾军;李剑白【摘要】Under the full consideration of the strength and life, the aerodynamic design of a high-speed power turbine and exhaust casing were completed according to design requirements and characteristics of power turbine for a 30 MW gas turbine booster. One dimensional scheme design of two stage high-speed power turbine, 3D blade design and exhaust system design were completed. And the analysis of quasi three-dimensional flow field and full three-dimensional flow performance were also carried out.The power turbine was fit on the gas generator to carry out performance test.The results indicated that the aerodynamic efficiency of the power turbine and total pressure recovery coefficient of exhaust system exceeded design re-quirements.The thermal efficiency of gas turbine was 0.6% higher than design point.%基于30 MW级燃气轮机增压机组动力涡轮设计要求及其研制特点、难点,在注重强度寿命的前提下开展了高速动力涡轮及排气系统的气动设计.完成了两级高速动力涡轮的一维方案设计、叶片造型设计和排气系统设计,并进行了准三维分析和全三维流动评估.动力涡轮直接串装燃气发生器,开展了燃气轮机整机工厂性能试验.试验结果表明:该动力涡轮气动效率和排气段总压恢复系数均超过指标要求,燃气轮机整机热效率超过设计要求0.6个百分点.【期刊名称】《燃气涡轮试验与研究》【年(卷),期】2018(031)002【总页数】6页(P16-21)【关键词】燃气轮机;高速动力涡轮;排气系统;气动设计;试验验证【作者】张剑;曾军;李剑白【作者单位】中国航发四川燃气涡轮研究院,成都610500;中国航发四川燃气涡轮研究院,成都610500;中国航发四川燃气涡轮研究院,成都610500【正文语种】中文【中图分类】TK471 引言目前,我国天然气输送管线使用的燃气轮机(以下简称燃机)均为国外机组,其中干线增压所选用的30 MW级燃机主要是英国Rolls-Royce公司的RB211-6562和美国GE公司的PGT25+。

民用涡扇发动机高高原起动风险规避试验方法

民用涡扇发动机高高原起动风险规避试验方法

收稿日期:2022-11-24基金项目:航空动力基础研究项目资助作者简介:陆思达(1991),男,硕士,工程师。

引用格式:陆思达,王玉东,严红明,等.民用涡扇发动机高高原起动风险规避试验方法[J].航空发动机,2023,49(2):160-167.LU Sida ,WANG Yudong ,YAN Hongming ,et al.Risk avoidance test method for high plateau starting of civil turbofan engine[J].Aeroengine ,2023,49(2):160-167.民用涡扇发动机高高原起动风险规避试验方法陆思达,王玉东,严红明(中国航发商用航空发动机有限责任公司,上海200241)摘要:为了保证民用涡扇发动机在高高原机场首次试飞起动成功,采用建模设计方法,建立了发动机部件级起动模型,包括高海拔气候条件对起动机特性的影响、旋转部件低转速特性延伸和修正、高海拔燃油雾化及点火对燃烧室效率的影响、发动机附件阻力和功率损失、风阻和吸放热等模块,设计了民用涡扇发动机高海拔起动控制规律。

采用仿真和试验分析技术建立了民用涡扇发动机起动方案设计方法和试验调试优化方法,详细分析了起动机能力降低、转子运转阻力增大、燃油喷嘴雾化效果差、部件效率和稳定性降低等4项影响高高原起动成功的因素。

按照循序渐进的原则设计了高高原试飞起动风险规避试验流程。

试验结果表明:设计的民用涡扇发动机高高原起动风险规避试验方法有效,确保了飞机首次转场高高原机场降落后成功起飞。

关键词:民用涡扇发动机;高高原;起动;试飞中图分类号:V231.1文献标识码:Adoi :10.13477/ki.aeroengine.2023.02.021Risk Avoidance Test Method for High Plateau Starting of Civil Turbofan EngineLU Si-da ,WANG Yu-dong ,YAN Hong-ming(AECC Commercial Aircraft Engine Co.,Ltd.,Shanghai 200241,China )Abstract :In order to ensure the successful start of a civil turbofan engine in the first flight test at a high plateau airport ,a compo⁃nent-level starting model for the civil turbofan engine was established ,including the influences of high plateau climatic environment on starter characteristics ,extension and correction of low rotational speed characteristics of the rotating components ,the influences of fuel at⁃omization and ignition to combustion efficiency of high plateau conditions ,engine accessory resistance and power loss ,wind and heat ab⁃sorption/discharge ,etc.Based on the model ,a high plateau starting control scheme was designed for the civil turbofan engine.The starting scheme design and test/commissioning optimization method for civil turbofan engines were established based on simulation and test analy⁃sis technology.Four factors affecting the successful starting of high plateau conditions were analyzed and discussed ,including decreasing starter capacity ,increasing rotor running resistance ,poor atomization quality of fuel nozzles ,and deteriorating component efficiency andstability.Following the principle of gradual progress ,a starting risk avoidance test procedure was developed for the high plateau flight test.The test results show that the designed risk avoidance test method for high plateau starting of civil turbofan engines is effective ,ensuring the successful takeoff of the aircraft after landing at a high plateau airport for the first time.Key words :civil turbofan engine ;high plateau ;starting ;flight test第49卷第2期2023年4月Vol.49No.2Apr.2023航空发动机Aeroengine0引言民航将标高1500~2438m 的机场定义为高原机场,2438m 以上的机场定义为高高原机场[1]。

核聚变涡轮发动机 燃料

核聚变涡轮发动机 燃料

核聚变涡轮发动机燃料英文回答:Nuclear Fusion Turbine Engine Fuel.A nuclear fusion turbine engine (NFTE) is a type of engine that uses nuclear fusion to generate thrust. Nuclear fusion is a process in which two atomic nuclei are combined to form a single, heavier nucleus, releasing a great amount of energy. This energy can be used to heat a working fluid, such as hydrogen, which is then expanded through a turbine to generate thrust.The fuel used in an NFTE is typically a mixture of deuterium and tritium. Deuterium is a naturally occurring isotope of hydrogen that has one proton and one neutron in its nucleus. Tritium is a radioactive isotope of hydrogen that has one proton and two neutrons in its nucleus. When deuterium and tritium are combined, they undergo nuclear fusion to form helium, releasing a great amount of energy.The amount of fuel required for an NFTE depends on a number of factors, including the size of the engine, the thrust required, and the efficiency of the engine. A small NFTE may only require a few kilograms of fuel, while a large NFTE may require several tons of fuel.中文回答:核聚变涡轮发动机燃料。

机械设计类英文文献及翻译

机械设计类英文文献及翻译

机械设计类英文文献及翻译Mechanical Design Literature:1. Title: "Mechanical design of an innovative wind turbine blade"Authors: A. Smith, B. JohnsonJournal: Renewable EnergySynopsis: This paper presents the mechanical design of a novel wind turbine blade. The design involves the utilization of advanced materials and structural analysis techniques to improve the efficiency and durability of the blade. The results show promising performance and potential for future applications in the wind energy industry.Translation: "一种创新风力发电机叶片的机械设计"期刊:可再生能源摘要:本文介绍了一种新型风力发电机叶片的机械设计。

该设计利用先进材料和结构分析技术,以提高叶片的效率和耐久性。

结果显示出良好的性能和未来在风能产业中的潜力。

2. Title: "Design and performance analysis of a robotic exoskeleton for rehabilitation"Authors: C. Wang, D. LiJournal: Robotics and Autonomous SystemsSynopsis: This study focuses on the mechanical design and performance analysis of a robotic exoskeleton for rehabilitation purposes. The exoskeleton is designed to assist patients with mobility impairments in their daily activities. The paper discusses the design considerations, kinematic analysis, and performance evaluation of the exoskeleton, providing insightsfor future improvements in rehabilitation robotics.Translation: "一种用于康复的机器人外骨骼的设计和性能分析"期刊:机器人与自主系统摘要:本研究针对一种用于康复目的的机器人外骨骼进行了机械设计和性能分析。

Interleavers for Unpunctured Symmetric Turbo Codes

Interleavers for Unpunctured Symmetric Turbo Codes

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ISIT2000, Sorrento, Italy, June 25{30, 2000
Interleavers for Unpunctured Symmetric Turbo Codes
Dept. Comms. & Computer Eng. Dept. Comms. & Computer Eng. University of Malta University of Malta Msida MSD 06, Malta Msida MSD 06, Malta E-mail: jabrif@.mt E-mail: vjbutt@.mt
Johann A. Bri a
Victor Buttigieg
lem is considered for relatively large block sizes, where the e ect of trellis termination is less marked. An optimised interleaver design technique based on simulated annealing is proposed { performance is significantly better than the Berrou-Glavieux interleaver without an increase in delay.
BER
Abstract | The Turbo code interleaver design prob-
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Uniform (Unterminated) Rectangular (21x49)

Geometric Modeling

Geometric Modeling

Geometric ModelingGeometric modeling is a crucial aspect of computer-aided design (CAD) and computer graphics. It involves the creation of digital representations of objects and environments using mathematical algorithms and geometric techniques. These models are used in various fields such as engineering, architecture, animation, and virtual reality. Geometric modeling plays a significant role in the design and visualization of complex structures, the simulation of physical phenomena, and the creation of realistic computer-generated imagery. One of the primary challenges in geometric modeling is achieving accuracy and precision in representing real-world objects and scenes. This requires the use of advanced mathematical concepts such as calculus, linear algebra, and differential geometry. Geometric modeling also involves the use of computational algorithms to generate and manipulate geometric shapes, surfaces, and volumes. These algorithms need to be efficient and robust to handle large-scale and intricate models while maintaining visualfidelity and integrity. Another important aspect of geometric modeling is the representation of 3D objects in a 2D space, which is essential for visualization and rendering. This process involves techniques such as projection, rasterization, and rendering, which are used to convert 3D geometric data into 2D images for display on screens or print. Achieving realistic and visually appealing representations requires careful consideration of lighting, shading, and texture mapping, which are fundamental in computer graphics and visualization. Inaddition to the technical challenges, geometric modeling also raises issuesrelated to usability and user experience. Designing intuitive and user-friendly interfaces for creating and manipulating geometric models is crucial for enabling efficient and effective design workflows. This involves considerations such as interactive manipulation, real-time feedback, and intuitive control mechanisms, which are essential for empowering users to express their creative ideas and concepts. Furthermore, geometric modeling has a significant impact on the manufacturing and production processes. The digital models created through geometric modeling are used for computer-aided manufacturing (CAM) and numerical control (NC) machining, enabling the production of precise and complex parts and assemblies. This integration of geometric modeling with manufacturing technologieshas revolutionized the way products are designed, prototyped, and manufactured, leading to advancements in efficiency, quality, and innovation. From an academic perspective, geometric modeling is a multidisciplinary field that draws from mathematics, computer science, and engineering. Researchers and educators in this field are constantly exploring new methods and techniques for geometric modeling, pushing the boundaries of what is possible in terms of representing and manipulating geometric data. This includes areas such as parametric modeling, geometric constraints, and procedural modeling, which are essential for enabling flexible and adaptable design processes. In conclusion, geometric modeling is a complex and multifaceted field with far-reaching implications for various industries and disciplines. It encompasses technical challenges related to accuracy, efficiency, and visualization, as well as considerations of usability, manufacturing, and academic research. As technology continues to advance, geometric modeling will play an increasingly critical role in shaping the way we design, create, and interact with the world around us.。

前苏联核电1000MW四极汽轮发电机设计制造技术与运行效果

前苏联核电1000MW四极汽轮发电机设计制造技术与运行效果

前苏联核电1000MW四极汽轮发电机设计制造技术与运行效果2010.№2 12前苏联核电1000MW四极汽轮发电机设计制造技术与运行效果李伟力1,罗应立2,孙玉田3,Я.Б.Данилевич4,崔红凤2(1.哈尔滨理工大学,哈尔滨150040;2.华北电力大学,北京102206;3.哈尔滨大电机研究所,哈尔滨150040;4.俄罗斯科学院硅酸盐化学研究院,圣彼得堡199034)[摘要]本文介绍了前苏联核电汽轮发电机和汽轮机生产的厂家以及圣彼得堡“电力”工厂和哈尔科夫重型电机制造厂生产核电发电机的相关情况,对“电力”工厂生产的ТВВ-1000-4四极汽轮发电机的定转子结构特点、样机试验、机械特性所做的工作进行了较深入的阐述,并对南乌克兰核电站汽轮发电机的运行情况进行了介绍。

[关键词]核电四极汽轮发电机;结构特点;机械特性[中图分类号]TM311[文献标识码]A[文章编号]1000-3983(2010)02-0012-06Summar y on Ma nufactur e and Oper ation of1000MW Nuclear Power Four-polesTurbogenera tor in the Former Soviet UnionLI Wei-li1,LUO Ying-li2,SUN Yu-tian3,J.Danilevich4,CUI Hong-feng2(1.Harbin University of Science and Technology,Harbin150040,China;2.North China Electric Power University,Beijing102206,China;3.Harbin Institute of Large Electrical Machinery,Harbin150040,China;4.Russian Academy of Sciences Institute of Silicate Chemistry,St.Petersburg,199034,Russia)Abstract:This paper introduces the nuclear power turbogenerator and steam turbine manufacturersof the former Soviet Union.Related situation about the nuclear power generator manufactured by St.Petersburg"Power"Factory and Kharkov Heavy Motor Factory is introduced.The stator and rotorstructural features,prototype test and mechanical characteristics ofТВВ-1000-4four-polesturbogenerator manufactured by the"Power"Factory,are deeply elaborated,and operation of thenuclear turbogenerator is also introduced.Key Wor ds:nuclear four-poles turbogenerator;structural characteristics;mechanical property1概述国家核电发展专题规划(2005~2020年)提出,我国的核电发展指导思想和方针是:统一技术路线,注重安全性和经济性,坚持以我为主,中外合作,通过引进国外先进技术,进行消化、吸收和再创新,实现核电站工程设计、设备制造和工程建设与运营管理的自主化。

涡轮机械与推进系统出版项目书目

涡轮机械与推进系统出版项目书目

英文回答:The purpose of the book is to provide a systematic introduction to the basic principles, design methods and applications of turbine machinery and propulsion systems in areas such as aerospace, ships and vehicles. Turbo mechanics play an important role in facilitating the operation of transport vehicles as important equipment for the use of hydrodynamic power—driven machinery. The book highlights the design and application techniques for turbine engines and turbine pressors and details the design methods and engineering applications for turbine pumps and turbinepressors. Through this book, engineers, researchers and students are able to gain insight into the relevant knowledge of turbine machinery and propulsion systems and provide important theoretical support and technical guidance for the development of transport technology in the country.本书旨在系统介绍涡轮机械与推进系统在航空航天、船舶和汽车等领域的基本原理、设计方法和应用技术。

区域综合能源系统两阶段鲁棒博弈优化调度

区域综合能源系统两阶段鲁棒博弈优化调度

DOI: 10.3785/j.issn.1008-973X.2021.01.021区域综合能源系统两阶段鲁棒博弈优化调度李笑竹,王维庆(新疆大学 可再生能源发电与并网技术教育部工程研究中心,新疆 乌鲁木齐 830047)摘 要:在区域综合能源系统的基本架构上,为了提升系统经济性与可再生能源并网能力,研究混合储能、冷热电联供机组(CCHP )、能量转换装置在多能互补下的两阶段优化运行模型. 利用虚拟能量厂(VEP ),平抑发、用电不确定性;采用鲁棒理论,构建灵活调整边界的不确定合集;引入条件风险理论,构建考虑多种不确定关系耦合下基于Copula-RCVaR 的能量管理风险模型. 针对上述模型特点,提出基于滤子技术的多目标鲸鱼算法进行求解. 分析不同可再生能源渗透率及集群效应对系统收益结果和运行策略的影响. 结果表明,引入虚拟能量厂可以提高利润1.9%,在保证稳定运行的前提下合理选择荷、源不确定变量的置信概率,可以提高利润5.9%.关键词: 区域综合能源系统(RIES );鲁棒理论;两阶段优化;收益损失风险;多目标优化算法中图分类号: TM 73 文献标志码: A 文章编号: 1008−973X (2021)01−0177−12Bi-level robust game optimal scheduling of regionalcomprehensive energy systemLI Xiao-zhu, WANG Wei-qing(Engineering Research Center of Ministry of Education for Renewable Energy Generation and Grid Connection Technology ,Xinjiang University , Urumqi 830047, China )Abstract: The two-stage optimal operation strategy model of hybrid energy storage, combined cooling, heating andpower (CCHP) units and energy conversion device was analyzed based on the basic framework of regional integrated energy system (RIES) in order to improve the system economy and the grid connection capacity of large-scale connected renewable energy under the RIES with multiple energy complementary. Virtual energy plant (VEP) was used to stabilize the uncertainty of power generation and consumption. The robust theory was used to construct the uncertain aggregate to adjust the boundary flexibly, and conditional risk theory was introduced to construct the risk model of RIES energy management based on Copula-RCVaR. A multi-objective whale optimal algorithm based on filter technology was proposed to solve the above complex model. The influence of different renewable energy penetration rate and their cluster effect on the income result and operation strategy of RIES was analyzed. Results show that the profit of RIES can be increased by 1.9% by introducing VEP. The profit of RIES can be increased by 5.9% by selecting a reasonable confidence probability of the uncertain variables for load and source based on the premise of ensuring the stable operation.Key words: regional integrated energy system (RIES); robust theory; bi-level optimization; revenue and loss risk; multi-objective optimization algorithm天然气的冷热电联供系统(combined cooling,heating and power ,CCHP )是连接电网与气网的耦合系统,也是区域综合能源系统(regional integ-rated energy system ,RIES )中最具发展前景的一种运营模式[1]. 目前,RIES 的研究多以优化不同效益目标,得到系统各设备的运行策略为主. Wei 等[2]收稿日期:2020−05−19. 网址:/eng/article/2021/1008-973X/202101021.shtml基金项目:国家自然科学基金资助项目(51667020,52067020);新疆自治区实验室开放课题资助项目(2018D4005).作者简介:李笑竹(1990—),女,博士生,从事电力系统能量管理及经济调度等研究. /0000-0003-0443-0449.E-mail :****************通信联系人:王维庆,男,教授. /0000-0001-6520-5507. E-mail :************.cn第 55 卷第 1 期 2021 年 1 月浙 江 大 学 学 报(工学版)Journal of Zhejiang University (Engineering Science)Vol.55 No.1Jan. 2021构建电转气的峰值负荷转移模型,从理论上证明了电气耦合系统具有较好的削峰填谷的效果;Guandalini等[3]对电气耦合系统进行了评价,结果证明,该系统可以提高可再生能源的可调度性;张儒峰等[4]提出合理利用弃风的电-气综合能源系统,实现互联系统之间的双向耦合;Qu等[5]利用电转气实现电力系统与天然气系统的双向能量流动,是促进风电消纳平滑功率需求的有效途径.上述文献均未考虑发、用电波动性对系统带来的收益损失风险. 张虹等[6-8]引入CVaR计算一定收益下系统要承担的收益风险,但均将CVaR转化为离散情况下最差CVaR进行求解,该方法结果的主观性强. 上述研究均仅考虑单维不确定变量,不适用于同时考虑多种不确定关系耦合下的建模与分析.综合需求响应利用冷热负荷的惯性特征,是平衡新电改下各市场主体利益诉求的绝佳手段[9],但RIES中考虑需求响应的调度方法较少涉及. 张虹等[6]让需求侧互动资源主动提供用电意愿,根据系统调度灵活选择用电行为;王文超等[9]将电价型需求响应应用于系统优化运行中;徐业琰等[10]通过电价型、激励型和博弈方法协同作用,实现对用户侧的联合调度. 来自于荷、源双侧(如风电、光伏、负荷等)的多重不确定性是RIES运行时面临的主要挑战. 在描述发电与用电不确定性上,场景法[11]、点估计法[12]、随机机会约束规划[13]、模型预测[14]都有较好的应用,但随机法与点估计法均需要实际中的大量样本数据,且场景法结果受场景个数的制约,机会约束规划难以保证求解效率与精度.鉴于以上分析,本文建立基于Copula-RCVaR 的区域综合能源系统两阶段鲁棒博弈优化调度模型. Copula-RCVaR模型能够对多个不确定变量耦合、不同决策需求下系统的收益损失风险进行分析与评估. 考虑综合需求响应,利用CCHP机组和虚拟能量厂(virtual energy plant,VEP)平抑RIES 内发电、用电波动性. 采用鲁棒理论,对系统内不确定变量建立不确定性合集,剖析不确定变量与系统经济性、保守性的动态相依关系,探索在不同决策需求下最经济可靠的调度方案. 针对模型特点,利用基于滤子技术的多目标鲸鱼算法进行求解. 以修改的IEEE33节点配电网与CCHP系统耦合形成RIES为例,验证模型能够在保证安全稳定的前提下,平衡各层主体利益,实现电力经济的可持续性发展.1 RIES的建模1.1 RIES的结构及运行方式如图1所示为RIES结构及运行方式示意图.在经典CCHP系统组成的RIES中,加入能量集线器与冷/热/电储能装置. 燃汽轮机是系统中的主要源动设备,发电量与RIES在能量交易中心向上级电网的购电量(包括在日前市场与实时市场的购电)共同承担系统负荷用电,通过余热转换装置与锅炉向系统内用户提供热负荷需求,系统的冷负荷需求由电制冷机和吸收式制冷机提供,电制冷机由电能驱动,吸收式制冷机由热能驱动.系统中,内燃气轮机和锅炉运行所需的天然气由RIES在能量交易中心向上级气网购得(仅在实时市场). 为了减少天然气的消耗,在系统中加入可再生能源电站(图1中的风电场),承担系统内部分电负荷与热负荷需求,可再生能源发电不接受调控且不计发电成本. RIES在日前市场向上级电网购买电量,能量盈余或亏空通过实时市场与上级电、气网的能量交换,调控CCHP机组组风电场图 1 RIES结构及运行示意图Fig.1 Structure and operation of RIES178浙江大学学报(工学版)第 55 卷合出力、VEP 、各能量转换装置得到平衡. 如图1所示,VEP 包括各储能系统与各种类型的可控负荷. 其中可控负荷根据特性分为以下4类[15]. 1)常规负荷(CL ),具有较大的随机性与波动性,且不可调控. 2)迎峰负荷(LSI ),切负荷量较低,一般为该类型总量的15%,补偿价格指数较高. 3)避峰负荷(LSII ),该类型负荷用电灵活性较大,切负荷量较高,为总量的30%,且补偿价格指数较低. 以上3种类型仅有电负荷CL-e/LSI-e/LSII-e. 4)可转移负荷(TL ),在不影响使用舒适度的前提下转移,补偿价格系数较低,但转移前、后的负荷总量不变,分为TL-h/TL-c ,表示热/冷负荷.该模型将RIES 与VEP 作为电力系统中不同的市场主体,针对运营体系及特点,采用双层多目标鲁棒优化对混合系统进行建模. 其中RIES 位于上层,VEP 位于下层. 优化时,先由RIES 向VEP 发送调度计划,VEP 在满足自身运行约束的前提下调控管辖内的可控资源(各储能系统、可控负荷)对该计划实行初步响应;将自身优化的结果反馈至上层,RIES 根据反馈结果进一步调整计划. 过程中,上、下两层信息互相更新与传递,在尽可能满足各系统电力需求的前提下,经济性、社会性最好. CCHP 机组与VEP 的参与可平抑发电与用电的波动性,将盈余电量在实时市场较稳定地外送,使RIES 获利,该运营模式在一定程度上可以提高可再生能源的并网能力. 由于冷/热网中的冷/热惯性,使得冷/热负荷中的不确定性能够被各自传输管道中的管存能力缓解[16],模型只考虑发、用电不确定性.1.2 CCHP 建模CCHP 装置互相耦合,与上级电、气网共同实现对RIES 能源的供应,各装置按如下方式建模.1)燃汽轮机. 出力与耗气量为二次函数.y GT t P e GT t G GT t y GT t 式中:a 1、b 1、c 1为燃汽轮机的耗气常数;、、为t 时刻燃气轮机的运行状态变量、出力和耗气量,其中=1为运行. 燃气轮机应满足P e GT min P e GT max R e GT U R e GT D T on GT T o ffGT式(2)为发电功率约束,式(3)为爬坡约束,式(4)为最小启停时间约束. 式中:、为出力上、下界限;、分别为向上和向下最大爬坡功率,、分别为最小开机和停机时间.2) 余热回收装置. 该装置输出热量与燃汽轮机的出力有关:P h WHR t 式中:a 2、b 2、c 2为耗量系数,为转换的可用热量.3) 电制冷机、吸收式制冷机和锅炉.P c ASR t P e ASR t P c ABS t P h ABS t P h B t G B t 式中:ηABS 、ηASR 分别为吸收式制冷机与电制冷机的效率,ηB 为锅炉热效率,、分别为电制冷机的制冷量与耗电量,、分别为吸收式制冷机的制冷量与吸热量,、分别为锅炉的1.3 数学模型1.3.1 上层模型 C e b C re tP e L t P h L t P c L t P e −s L t P VEP −e i ,tP VEP −h i ,t P VEP −c i ,t式中:ηt 为日前市场电量购买比例;C t S-e 、C t S-h 、C t S-c分别为电、热、冷能出售价格;、分别为日前、实时市场向上级电网的购电价格;C g 为向上级气网的购气价格;、、分别为t 时刻电、热、冷负荷;为电负荷的预测值,、、为RIES 对第i 个VEP 下达的调度计划,上第 1 期李笑竹, 等:区域综合能源系统两阶段鲁棒博弈优化调度[J]. 浙江大学学报:工学版,2021, 55(1): 177–188.179P VEP −e i ,tP grid t标e 、h 、c 表示VEP 类型,>0表示向系统注入能量;为系统与上级电网之间的电量交换,P t grid >0表示RIES 向上级电网售电,反之为购电;C VEP 为VEP 运行成本,由下层模型计算得出返回至上层;C conv 、C ek 为转换装置运行成本及旋转备N e LK W i K L i γW i γL i P u W i ,t P e −u L i ,t 式中:S WHR 、S ABS 、S ASR 分别为余热回收装置、吸收式制冷机、电制冷机的成本系数,N W 、分别为风电站及常规电负荷总数,/、/、Δ/Δ分别为风电/常规电负荷的旋转备用惩罚系数、功率偏差系数及各功率偏差上限.2)目标函数2. RIES 的收益损失风险最小值min f 1.2,详细见2章的风险能量管理模型,此处不赘述.P VEP −e i ,tP VEP −h i ,tP VEP −c i ,tN e v N h v N c v式中:、、分别为通过下层模型优化返回至上层,第i 个虚拟电、热、冷厂在t时刻的调度功率;、、分别为各虚拟电、热、冷厂的个数.上层模型除式(2)~(4)、(7)外,还需满足如P grid tP grid max P gridmin 为了防止RIES 与上级电网之间的联络线功率毛刺过多,使其能够运行平稳,将离散成10的整数倍,设置上、下功率界限为、,最大爬升功率为120 kW ,最小保持功率时间为2 h.1.3.2 下层模型 VEP 将RIES 下达的调用计划分解至各个可控单元上,使得两层之间的调度计划偏差最小,VEP 达到最大的经济效益与社会效益.1)目标函数1. 调度计划偏差最小.P VEP −e i ,t P VEP −h i ,t P VEP −c i ,t式中:、、由上层模型优化所得并传递至下层.2)目标函数2. 经济效益最好,调度成本最小.3)目标函数3. 社会效益最高,受文献[15]中以用电舒适度表征虚拟电厂社会效益方式的启发,以用能舒适度来表征VEP 的社会效益,即负荷切出率和转移率较低,社会效益较好.λe LSI λe LSII λh LT λc LT Lim LSI i ,max Lim LSII i ,max P max −h LT i P max −c LT iP e LSI i ,t P e LSII i ,t P h LT i ,t P c LT i ,t 式中:、、、分别为各类型负荷占该类总负荷比,、、、分别为各类型可控负荷的总量. 从式(17)可以看出,min f 2,3的取值为[0, 1.0],当各可控负荷在调度周期内完全不调用时,、、、均180浙 江 大 学 学 报(工学版)第 55 卷为0,此时用电舒适度最高,min f 2,3=1;当各可控负荷调度总量达到上限时,用电舒适度最低,min f 2,3=0.下层优化模型须满足各储能系统的相关约束. 其中储电约束如下.P e −ch ESS tP e −diss ESS t ρe ESS ηe c ηe d式中:SOC min 、SOC max 分别表示最小、最大充电状态,、分别为最大充、放电功率,、、分别为自放电率、充电率、放电率.储冷储热系统运行方式相同,储热为例,约束如下:P h −ch ESS t P h −diss ESS t 式中:、为最大充放电量.LSI 、LSII 运行方式类似,以LSI 为例,运行约束如下:可转移的冷热负荷运行类似,以热负荷为例:2 风险能量管理建模对1.3.1节上层模型的目标函数2进行建模. 鉴于发电、用电的不确定性,RIES 收益具有风险特征.2.1 CVaR 理论概述CVaR 度量损失的平均情况可以描述尾部风险[6],CVaR 为式中:E (.)为期望函数;x ∈ΩD 为决策变量;y ∈ΩR 为随机变量,概率密度函数为f PDF (y ),f c-l (x ,y )为RIES 的收益损失函数,且E (|f c -l (x ,y )|)<+∞;C α为损失值的阈值;VaR 为在给定置信度β下,RIES 可能遭受的最大损失值. 引入辅助函数计算CVaR ,表示如下:式中:[t ]+=max {t , 0}.2.2 Copula 函数在RIES 中,考虑发电与用电的双重不确定性,根据Copula 函数的性质[16],根据单个随机变量的概率密度函数,可得多个随机变量耦合关系下的联合概率密度函数. 建立2种随机变量情况[17]式中:F 1(y I )、F 2(y II )、f 1(y I )、f 2(y II )分别为随机变量y I 、y II 的累计概率密度函数与概率密度函数;ΩRI 、ΩRII 由鲁棒优化理论进行构建,分别为描述风电、常规电负荷随机性的不确定合集.2.3 随机变量的处理及决策以风电出力为例,利用鲁棒理论,对各时段的输出功率构建加法不确定合集:P e −s W i ,t P e W i ,t P e −u W i ,t γW i ,t式中:、Δ分别为风电场i 在t 时段的预测出力与出力偏差;Δ为出力偏差的上限;第 1 期李笑竹, 等:区域综合能源系统两阶段鲁棒博弈优化调度[J]. 浙江大学学报:工学版,2021, 55(1): 177–188.181ΓW ,t ΓW ,t δW i ,t γW i ,t P e W i ,t 为出力偏差系数;||·||∞为无穷范数;||·||1 ≤表示1范数约束对应不确定变量的空间集群效应,既在某个调度时段各风电场的出力偏差不可能同时达到最大,由此引入空间约束参数来调整不确定合集的边界. 若=||,Δ独立且服从正态分布,记期望和方差为0和σW *,利用Lindeberg-式中:Φ−1(·)为正态分布密度函数的反函数,αW 为风电置信概率.通过构造拉格朗日函数与线性对偶理论可知,考虑在t 时段的最极端情况,风电场出力达到不确定合集下限. 此时仅有一个风电场出力的偏e 同理建立用电不确定性合集,可得空间约束参数与极端功率情况,如下:P e W i ,t P e L i ,t 为了定量分析RIES 的收益风险,建立基于Copula-RCVaR 的多能流收益风险模型. 模型中,x 为上层目标的决策变量,随机变量y I 为风电出力偏差Δ,y II 为常规电负荷偏差Δ,定义系统运行时的损失函数为利润函数的负数,f c-l (x ,y )=−f 1.1,上层模型的目标函数2(min f 1.2)为式(29)的形式.3 模型的求解3.1 多目标鲸鱼优化算法鲸鱼算法(WOA )具有参数设置少、寻优性能强等特点,在求解精度和收敛速度上均优于粒子群算法PSO [18],已成功应用于大规模优化问题上.标准WOA 存在不能有效平衡全局与局部搜索能力,导致在迭代后期算法的多样性丧失,收敛能力不足的问题,如在文献[18]测试问题F2和F21上,算法在迭代最终收敛. 提出相关的改进策略,改进的鲸鱼算法(improved WOA ,IWOA )伪代码如下.算法:IWOA输入:Np (种群规模);D (维度);G (最大迭代次数);A_constant; X (初始种群)输出:x *(最优个体)1.F ←计算X 适应度;x *←从X 中选择最优个体;2.while (迭代停止条件不满足) do3. 通过式(34)、(35)更新a , A , C , l ;4. if |A |≥A_constant5. 在X 中随机选择不同5个个体(x r1, x r2, x r3, x r4, x r5);6. 通过式(36)更新X ;7. else 在X 中随机选择不同2个个体(x r1,x r2);8. 通过式(37)更新X ;end if9. 越界处理;计算F ;更新x *;end while 10. return x *式中:G iter 、G max 分别为当前迭代次数与最大迭代次数;r 为(0,1.0)的随机数;系数A 、C 均由收敛因子a 计算,随着迭代次数由2减小到0;l 为螺旋系数. 设置探索固定值A_constant ,当A ≥ A_con-stant 时执行全局搜索,反之为局部. 借助差分进化算法中个体的合作与竞争指导优化搜索,分别进行螺旋运动和直线运动,更新方式如下:多目标鲸鱼算法借鉴NSGAII 中的精英保留策略,利用外部存档保存进化过程中已经发现的非占优解. 当外部存档超出设定的最大容量时,采用拥挤熵的方式对Pareto 解集进行裁剪[19]. 该方法考虑相邻解的分布情况,能够合理反映非支配解之间的拥挤程度. 从问题的实际出发,需要得到一个满足各个目标的解,使用模糊数学的方式提取最优折中解,选择线性函数作为隶属度函数.3.2 复杂约束条件处理针对RIES 两阶段风险能量管理模型中复杂182浙 江 大 学 学 报(工学版)第 55 卷的等式与不等式约束,采用滤子技术对约束条件进行处理. 构造由目标函数与约束违反度组成的[20]式中:g i(Y)、h n(Y)分别为不等式与等式约束,m、n为对应的个数. 借助Pareto理论,在最小值问题上有如下定义.定义1 若F(Y i)≤F(Y j),G(Y i)≤G(Y j),则称滤子(F(Y i)),G(Y i))支配(F(Y j),G(Y j)).定义2 滤子集内的滤子互不支配.将上层模型中各集线器能量约束(式(12)~(14))与目标函数构造滤子对;其他约束均可以作为边界条件,直接利用元启发式算法处理. 下层模型储电侧电荷约束(18)与目标函数构造滤子对;可以转移冷热负荷、储能系统的可持续运行约束(20)、(22)、(25),采用动态可松弛约束处理方式[21]. 以储电为例,计算约束违反程度记为εESS-e,根据边界条件计算松弛度,根据松弛度确定调整量;其他约束可以作为边界条件.3.3 求解流程模型整体求解包括约束处理流程,如图2所示.图 2 优化调度模型的求解流程图Fig.2 Flow chart of solution process4 结果与讨论4.1 算例说明以修改的IEEE33节点配电网与CCHP系统耦合形成RIES,CCHP内设备及参数见表1、2. 表中,P max、P min分别为功率的上、下界,η为能效,C c为成本价格,GT为燃气轮机,WHR为余热回收装置,ABS为吸收式制冷机,ASR为电制冷机,表 1 CCHP内设备参数设置1Tab.1 Parameter setting 1 of each device in CCHP设备a i b i c i P max /kWP min /kWT on/offGT/hR eGTU/D/(kW·h−1)GT 2.15 2.210.1119040380 WHR27.0−3.300.7460000−−表 2 CCHP内设备参数设置2Tab.2 Parameter setting 2 of each device in CCHP 设备ηC c /(美元·kW−1)P max /kW GT−−−WHR−0.01674−ABS0.700.0122000 ASR 3.080.0152000 BO0.85−500第 1 期李笑竹, 等:区域综合能源系统两阶段鲁棒博弈优化调度[J]. 浙江大学学报:工学版,2021, 55(1): 177–188.183BO 为锅炉. RIES 包含3个虚拟能量厂,分别实现RIES 内电、热、冷负荷的需求响应,虚拟能量厂的相关参数如表3所示. 表中,VEP-e 、VEP-h 、VEP-c 分别表示电、热、冷的虚拟能量厂,P t 为占比,SOC 为容量,P ESS 为最大充放电功率,SOC pu 为归一化后的容量. 配电网中1为根节点,与上级电网相连,节点15接入总容量为55 MW 的风电厂群. 区域内电、冷、热负荷及风电出力预测见图3.图中,P L 为预测电荷. 电负荷的85%购自日前市场,设购买价格为0.4 kW·h/美元,电能在实时市场的交易价格与用电量有关,如图4所示,天然气购买价格为0.22 Kcf·h/美元. RIES 的电、热、冷售价见图4. 图中,C c 为价格. 风电、常规电负荷的惩罚系数为0.65、0.60 kW/美元.4.2 鲁棒决策分析鲁棒优化是在不确定变量的极端情况下系统进行的优化调度. 根据2.3节的分析,可以推出系统在所考虑的极端情况之外运行的概率:为了分析风电与负荷的置信概率与总数和系统运行在所考虑极端情况外的概率P OE 的关系,分别针对单个不确定变量与多不确定变量互相耦合的情况进行研究. 图5中,αW 、αL 分别为风电置信概率和常规电负荷置信概率,N W 、N L 分别为风电场数量和常规电负荷总数. 如图5(a )所示为单图 3 风电出力及各负荷的日前预报曲线Fig.3 Daily forecast of wind power output and load图 4 价格趋势图Fig.4 Price trend chart0.20.40.60.81.00.10.20.30.40.50.60.70.20.40.60.81.0P OEP 图 5 在极端情况外运行的概率关系Fig.5 Relation of operating outside extreme scenario表 3 虚拟能量厂相关参数设置Tab.3 Parameter setting of VEP类型参数数值VEP-e VEP-h VEP-c LSI P t20%−−LSI ξe LSI /(kW·h·美元−1)0.7−−LSII P t30%−−LSII ξe LSII /(kW·h·美元−1)0.45−−LT P t−25%20%LT P LT min ,t−00LT P LT max ,t−0.50.5LT ξLT /(kW·h·美元−1)−0.40.4ESS SOC/kW 250500500ESS P ESS /kW 100200200ESS ρ, ηc , ηd 1%, 0.9, 0.9−−ESS SOC pu0.2~0.9−−ESSξESS /(kW·h·美元−1)0.450.50.5184浙 江 大 学 学 报(工学版)第 55 卷个不确定变量(以风电为例),如图5(b )、(c )所示分别为2个不确定变量耦合. 图5(a )中,常规电负荷总数、置信概率固定分别为20、0.6;图5(b )中,风电常规电负荷总数均为15;图5(c )中,风电常规电负荷置信概率均为15.从图5(a )可以看出,不确定变量的置信概率增大,超出极端情况的概率降低;不确定变量总个数减小,该概率升高. 多个不确定变量耦合下超出极端情况概率的等高线间距增加且不等,说明该情况下不确定变量对系统的影响更加复杂.较图5(c )、(b )中小概率等高线包含区域较小,置信概率对系统超出极端情况的概率影响较明显.4.3 互动性分析基于建立的Copula-RCVaR 模型,对以下4个算例进行分析. 算例1:RIES 含虚拟冷/热/电厂;算例2:RIES 仅含虚拟热厂与虚拟冷厂;算例3:RIES 仅含虚拟电厂;算例4:RIES 完全不含虚拟能量厂,可调度仅为燃气轮机与锅炉. 设发电与用电偏差服从正态分布(预测精度为68.27%),考虑空间集群效应,总数量均为20,置信概率均为0.6. 运行结果见表4,虚拟能量厂优化方案见图6.表4中,B RIES 为RIES 利润,D VEP-e 、D VEP-h 、D VEP-c 分别为VEP-e 、VEP-h 、VEP-c 调度偏差功率,C VEP-e 、C VEP-h 、C VEP-c 分别为VEP-e 、VEP-h 、VEP-c 调度成本,S VEP-e 、S VEP-h 、S VEP-c 分别为归一化后的VEP-e 、VEP-h 、VEP-c 社会成本. 图6中,P 为功率,LSI-e 、LSII-e 分别表示迎峰电负荷和避峰电负荷,ESS-e 表示储电系统,LT-h 表示可转移热负荷,ESS-h 表示储热系统,LT-c 表示可转移冷负荷,ESS-c 表示储冷系统.从表4可以看出,随着不同类型VEP 的加入,对更多种类的可调度资源与储能装置集中管理,系统内包含的可调度资源种类增加,调度变得更加灵活,偏差随之减小,情况1(虚拟冷、热、电厂全参与的情况)下的偏差较情况3(仅有虚拟电厂参与的情况)下减小6%. 虚拟冷/热厂中包含的可控负荷主要为TL-h/TL-c ,基于该类型负荷转移前后负荷总量不变的强约束条件,使得可转移负荷数量增加,RIES 与VEP 之间的偏差大大降低. 随着可调控资源数量的增加,分摊了VEP 在调控时的经济与社会成本,各类可控资源充分全面参与调度,VEP 的经济运行成本在VEP 全参与下较仅有虚拟电厂时减少36.3%,较虚拟冷、热厂参与时分别减少17.1%、6%;社会成本相应提高,用户的用电舒适度增高;RIES 利润逐渐增加,图 6 各算例下虚拟能量厂优化方案Fig.6 Optimization plan of VEP of each case表 4 各算例下的运行结果Tab.4 Operation result of each case算例B RIES 利润/(105美元)D VEP-e /MW D VEP-h /MW D VEP-c /MW C VEP-e /(103 美元)C VEP-h /(103 美元)C VEP-c /(103 美元)S VEP-e S VEP-h S VEP-c 算例18.62 6.008.54 2.23 2.87 4.75 1.910.810.610.71算例28.53−17.20 6.17− 5.56 1.97−0.530.60算例38.50 6.36−− 3.04−−0.77−−算例48.46−−−−−−−−−第 1 期李笑竹, 等:区域综合能源系统两阶段鲁棒博弈优化调度[J]. 浙江大学学报:工学版,2021, 55(1): 177–188.185VEP 全参与下的经济成本较不含VEP 降低1.9%.从图6可以看出,在用电高峰时段(11时—13时、19时—22时),VEP 向RIES 注入能量,保证供需与电量平衡;RIES 将盈余电量以较高的实时电价,在能量交易中心通过实时市场较平稳外送至上级电网,在保证大电网稳定运行的前提下解决负荷集中地区的高峰用电需求. 在低耗电时期,VEP 向RIES 吸收能量,以满足自身区域内可控资源的运行需求. 对比图6中各算例VEP 的调度方案可知,VEP 全参与下的计划较其他2种方式更平稳,图6(a )的累积调度相对集中在[−600,600] kW ,与表4的结果吻合.4.4 运行结果敏感性分析4.4.1 不确定变量置信概率的影响 分析各不确定合集的置信概率对RIES 利润、收益损失风险的影响. 在相同风险阈值下,CVaR 置信度为0.95;不确定变量的预测精度均为68.27%;风电场、常规电负荷总数分别为20、32,不同置信概率α下的RIES 利润、收益损失风险见表5. 表中,收益损失风险为归一化后的数值. 可以看出,随着置信概率的不断减小,不确定合集区间逐渐收缩,系统所需旋转备用成本不断减小,RIES 利润随之升高;系统的收益损失风险为仅考虑系统不确定合集内的不确定性计算而来,由于不确定合集收缩,RIES 收益损失风险逐渐减小,意味着系统运行时面临的风险逐渐减小. 盲目减小置信概率,会使得系统运行在极端情况外的概率大大增加,当置信概率降至20%时,该概率为100%. 当置信概率为30%~45%时,RIES 利润增加最快,收益损失风险下降最快;当置信概率为45%~60%时,极端情况外运行概率处于可接受的低概率段.如图7所示为当α=55.5%时,上层与下层的Pareto 有效前沿. 图中,CVaR RIES 为RIES 收益风险,D B 为RIES 利润的相反数. 可以看出,利用改进的多目标鲸鱼算法得到的Pareto 解集较均匀地分布在Pareto 前沿上,具有较好的分布性. Pareto 解集中的每一点对应在该利润与收益损失风险下的RIES 及各VEP 的优化运行策略. 系统调度员可以根据实际中的不同情况,平衡RIES 风险与利润、各VEP 的偏差与成本进行决策,寻找合适的最优折中解.为了说明Pareto 最优解集为有效解,当α=55.5%时双层模型中各目标函数的收敛情况如图8所示. 图中,D VEP 为调度偏差功率,N it 为迭代次数.图 7 α=55.5% 时的 Pareto 有效前沿Fig.7 Pareto frontier for α=55.5%表 5 不同置信概率下的结果比较Tab.5 Results with different confidence probabilitiesα/%空间约束参数B RIES /(105美元)CVaR RIES P OE /%ΓW ,tΓe L ,t6019.230.28.220.982 50.0255.517.627.48.450.911 80.094514.521.68.710.784 5 1.11309.714.69.280.536 124.2320 5.98.69.530.351 3100.00100.590.899.660.351 3100.00186浙 江 大 学 学 报(工学版)第 55 卷。

jameswatt 英文介绍

jameswatt 英文介绍

James Watt (1736–1819) was a Scottish inventor, mechanical engineer, and chemist whose improvements to the steam engine played a pivotal role in the Industrial Revolution. Here is an English introduction to James Watt:James Watt, born on January 19, 1736, in Greenock, Scotland, was a prominent figure of the Industrial Revolution. He is best known for his significant contributions to the development of the steam engine, which revolutionized the efficiency and power of engines used in various industries.Watt's interest in mechanics and engineering led him to enhance Thomas Newcomen's steam engine design. In 1769, he patented a separate condenser that greatly improved the efficiency of steam engines by preventing energy loss. This innovation marked a crucial advancement in the utilization of steam power for industrial purposes.Collaborating with the entrepreneur Matthew Boulton, Watt established the firm Boulton and Watt, where they manufactured and sold steam engines. Their engines became widely adopted, transforming industries such as mining, textiles, and transportation. The Watt steam engine became a cornerstone of the Industrial Revolution, fueling economic growth and technological progress during the 18th and 19th centuries.James Watt's impact extended beyond engineering. He also contributed to the standardization of measurement units, introducing the concept of horsepower to quantify the power output of engines. Watt's legacy is honored by the unit of power, the watt, which is named in his honor.James Watt passed away on August 25, 1819, leaving behind a lasting legacy as a pioneering engineer whose innovations continue to influence modern machinery and power systems.。

C++程序设计(part1)

C++程序设计(part1)

IEEE John von Neumann Medal
ACM 1947 Association of Computing Machinery Turing Award 1966 A.J. Perlis Richard Hamming Donald E.Knuth John Backus Peter Naur Barbara Liskov Amir Pnueli Edgar F. Codd Andrew Chi-Chih Yao ,2000 姚期智 随机数生成、 随机数生成、密码学与通信复杂度 Charles Thacker Alto at Xerox PARC
高级程序设计C++ 高级程序设计
Advanced Programming in C++ (part 1)
南京大学软件学院 郑滔 zt@
ENIAC EDVAC
Ole-Johan Dahl Kristen Nygaard
Father of OO programming Father of Simula
Programming Paradigm
Functional Paradigm
Mathematics and the theory of functions Lisp(atom, list,cons,…) app:Emacs
Logical
Automatic proofs within artificial intelligence Based on axioms, inference rules, and queries prolog
Generic Programming Efficient, Reusable
参考书
Samples

Turbomachinery and Fluid Dynamics

Turbomachinery and Fluid Dynamics

Turbomachinery and Fluid Dynamics Turbomachinery and fluid dynamics are two interconnected fields that play a crucial role in various industries, including aerospace, automotive, power generation, and oil and gas. Turbomachinery refers to the study and design of turbomachines, which are devices that transfer energy between a rotor and a fluid. These devices include turbines, compressors, and pumps, and they are essential for converting energy from one form to another. On the other hand, fluid dynamics is the study of how fluids move and the forces acting on them. It is a fundamental aspect of turbomachinery, as the performance of turbomachines is heavily influenced by the behavior of the fluid they are designed to handle. One of the key challenges in turbomachinery and fluid dynamics is achieving optimalefficiency and performance while minimizing losses and maximizing energy transfer. This requires a deep understanding of the complex interactions between the fluid and the machine, as well as the ability to design and optimize the geometry of the turbomachine to achieve the desired performance. Engineers and researchers in this field often face the daunting task of balancing various design constraints, such as aerodynamic efficiency, structural integrity, and manufacturability, to develop turbomachines that meet the demanding requirements of modern industries. In addition to performance considerations, another important aspect of turbomachinery and fluid dynamics is the impact on the environment. With increasing concerns about climate change and environmental sustainability, there is a growing emphasis on developing more efficient and environmentally friendly turbomachinery systems. This includes reducing emissions, improving fuel efficiency, and minimizing the environmental footprint of turbomachinery operations. Engineers and researchers are continuously exploring new technologies and design strategies to address these challenges and contribute to a more sustainable future. Furthermore, turbomachinery and fluid dynamics also play a critical role in the advancement of renewable energy technologies. For example, wind turbines and hydroelectric turbines are prime examples of turbomachines that harness the power of fluid dynamics to generate clean and renewable energy. The design and optimization of these turbomachines are essential for maximizing energy extraction from natural resources while minimizing environmental impact. As the world transitions towardsa more sustainable energy landscape, turbomachinery and fluid dynamics will continue to be at the forefront of innovation and progress in renewable energy technologies. From a research perspective, turbomachinery and fluid dynamics present a myriad of opportunities for exploration and discovery. The complex and nonlinear nature of fluid flow poses numerous challenges and opens up new avenues for scientific inquiry. Researchers are constantly pushing the boundaries of knowledge in areas such as turbulence modeling, flow control, and multiphase flow phenomena to unlock new insights and develop advanced technologies. The interdisciplinary nature of turbomachinery and fluid dynamics also fosters collaboration between different fields, such as mechanical engineering, aerospace engineering, and computational fluid dynamics, leading to a rich and diverse research landscape. In conclusion, turbomachinery and fluid dynamics are integral components of various industries and technologies, with far-reaching implications for performance, sustainability, and innovation. The challenges and opportunities in this field are vast and diverse, requiring a multidisciplinary approach and a relentless pursuit of knowledge and excellence. As we continue to push the boundaries of what is possible, turbomachinery and fluid dynamics will undoubtedly remain at the forefront of technological advancement and scientific discovery.。

采用弯扭叶片提高汽轮机运行性能

采用弯扭叶片提高汽轮机运行性能

第17卷,总第93期1999年1月,第1期节能技术E NERGY CONSERVATION TECHNOLOGYVol.17,Sum No.93Feb 1999,No.1采用弯扭叶片提高汽轮机运行性能哈尔滨工业大学 黄洪雁 韩万今 冯国泰 王仲奇摘 要 本文介绍了适用于涡轮设计的一套计算体系,并对某机组进行了数值模拟,计算结果表明,采用弯叶片后,机组性能得到明显提高。

关键词 汽轮机 弯扭叶片Increasing Performance of Turbomachineryby Using Curving BladesHuang Hongyan Han Wanjing Feng Guotai Wang ZhongqiHarbin Institute of TechnologyAbstract In this paper,a numerical system suitable for turbomachine design is introduced.The numerical simulation of a real turbomachinery is also presented.The results show that the capacity of this turbine is improved when curving blades are used.Key words Turbomachinery,Curving blade收稿日期 1998-12-21 收修改稿日期 1998-12-28黄洪雁 哈尔滨工业大学能源科学与工程学院 博士1 引言对有限的能源资源进行无限度的开采使人们越来越重视能源的合理利用,努力提高大型火电蒸汽轮机装置的经济性。

对于这类大型机组,其高压级叶片较短,横向二次流比较大,二次流损失一般占总损失的50%~60%,在低压级,除了横向二次流外,径向压力梯度大,径向串流、掺混比较严重,径向二次流占主导地位。

19-工业冷冻霍尔简介

19-工业冷冻霍尔简介

设计出第一台 CO2双级压缩 机
研发出新的 “Veebloc” 压 缩机
推出Scada 监控系统
1889
1911
1936
1950
1978
1989
2006
1882
霍尔制造出第 一台冷风机
1910
为伦敦新国家 溜冰宫殿提供 地板制冷设备
1922
制造出第一台 “高速”氨压 缩机
1940
推出 Monobloc 压缩机系列
欢 迎
霍尔·中国
J&E Hall International History
霍尔国际历史
Founded during the Industrial Revolution by John Hall in 1785 in Dartford 1785年,工业革命期间,由约翰· 霍尔在达特福德(英国英格兰东南部城市)成立 J&E Hall has more than 200 years of fine engineering 霍尔拥有超过200年的卓越工程技术
单螺杆压缩机
霍尔技术研发中心
HallService 服务&维护 霍尔英国 霍尔中国
霍尔研发
为新设备的测试做准备
霍尔研发
机组测试
J & E Hall Worldwide
霍尔全球
J & E Hall United Kingdom 霍尔英国 J & E Hall North America 霍尔北美 J & E Hall Europe 霍尔欧洲 J & E Hall Middle East 霍尔中东 J & E Hall Latin America 霍尔拉丁美洲 J & E Hall South East Asia 霍尔南亚

微波驱动超导量子比特产生Greenberger-Horne-Zeilenger态

微波驱动超导量子比特产生Greenberger-Horne-Zeilenger态

微波驱动超导量子比特产生Greenberger-Horne-Zeilenger态伍方舟;夏立新【期刊名称】《湖南科技学院学报》【年(卷),期】2013(34)8【摘要】In this paper, we present a scheme that based on superconducting qubit system to generate GHZ state through microwave-driven cross resonant technology. Our scheme is more facilitative to manipulate than the conventional schemes, the qubut is always in the optimum spot, no additional flux lines to adjust superconducting qubits’ transition frequency, and therefore it avoids the obstacle of spectral crowding and extended the coherence time.% 提出一个基于超导量子比特系统,利用微波驱动交叉共振技术制备GHZ态的方案。

本方案操控比传统方案更简单,量子比特始终处于最佳工作点,不需要额外的磁通来调节跃迁频率,避免了频谱拥挤,延长了相干时间。

【总页数】3页(P21-23)【作者】伍方舟;夏立新【作者单位】河南科技大学物理与工程学院,河南洛阳 471023;河南科技大学物理与工程学院,河南洛阳 471023【正文语种】中文【中图分类】O413.1【相关文献】1.两超导电荷量子比特与压缩相干态相互作用的纠缠特性 [J], 廖庆洪;刘晔;Muhammad Ashfaq Ahmad2.通过双Raman作用在超导量子干涉器件中实现多比特GHZ态 [J], 詹志明;刘晓东;张立辉;石文星;李星3.用微波-超导量子比特系统实现一位通用量子逻辑门 [J], 蔡十华;胡菊菊4.非马尔科夫环境下耦合超导量子比特纠缠态的纠缠消相干 [J], 嵇英华;徐林5.基于超绝热捷径技术快速制备超导三量子比特Greenberger-Horne-Zeilinger 态 [J], 于宛让;计新因版权原因,仅展示原文概要,查看原文内容请购买。

侯欢外文翻译

侯欢外文翻译

淮阴工学院毕业设计(论文)外文资料翻译系(院):电子与电气工程学院专业:电气工程及其自动化姓名:侯欢学号:1101205531外文出处:IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 30, NO 3. MAY/JLrNE 1994附件:外文资料翻译译文指导教师评语:签名:年月日电子增强的低压电动机保护与控制摘要:无论今天还是将来电子增强都会是电动机保护和控制的主要研发方向。

现今机电系统都是局限于简单的保护模式其中有典型的的一对一关系像输入(例如,电流)和反应(例如,偏转)。

而微计算机芯片,其不断增加的处理速度和程序指令集给设计师在工具和自由打包多重保护模式以及自定义保护提供了更好的方法。

这种计算能力,使设计人员能够发展现代多功能电动机保护系统,其中包括以前仅通过复杂的硬连线控制电路的控制功能。

设计师现在可以重新审视电机保护性的要求并提供独特的解决方案。

另外,它也可以取代一些高层次的可编程控制器的解决方案并与专用控制器建立成一个更用户友好的,个体的电动机保护包。

同样的包可以提供广泛的数据通信链路给工厂管理系统。

这样的一个电机保护和控制系统针对电机的应用需求,在过去往往是超越实用性范围的。

一、电机保护一般我们采取三步来改进电动机保护和控制。

第一步是从物理的角度来研究保护电机。

第二步是研究目前的电机保护和控制的方法,并确定他们的长处和弱点。

第三步,采取新的保护和控制系统,并确定现代技术是否可以提供一些更好的解决方案。

二、电机物理绕组故障是电机的主要故障之一,所以一个保护装置的最基本功能是必须能够保护电机绕组。

如今电机使用的大多数绝缘系统在本质上是有机的,因此,绝缘系统受到过热催化使电机绝缘系统遭到破坏。

这些热量是由于电流通过绕组产生的,而且热量是电流的平方函数。

在一般情况下,过多的热量与电机两个方面的性能相关。

第一个涉及的瞬态过载其发生在250%和1000%的满负荷电流之间。

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The Design and Evolution of TurboTurtle, a Collaborative Microworld for Exploring Newtonian Physics
Andy Cockburn
Department of Computer Science Department of Computer Science University of Canterbury University of Calgary Christchurch, New Zealand Calgary, Canada andy@ saul@cpsc.ucalgary.ca November 22, 1995
2 The Educational Foundations behind TurboTurtle
Papert called computer supported microworlds incubators for knowledge" when he described the potential of computer aided learning CAL to encourage exploration and thus self-education by children Papert, 1980. His educational philosophies stem from Piaget's work on learning1 which, simplistically, state that much of children's learning occurs without being taught: children construct their skills and understanding from seeds of knowledge. Many accepted Papert's beliefs on the educational value of exploratory learning as established fact Maddux, 1985. Yet not all educators agree with Papert. In sharp contrast to microworlds, most CAL systems are highly prescriptive. They direct students through small increments of information, and test whether the student has mastered the material before advancing. The advantage derived from such directed learning is that teachers make the learning goals explicit, and that students can advance at their own pace. Exploratory systems such as microworlds, on the other hand, have little or no notion of predetermined trails that students must
பைடு நூலகம்
Newtonian universe. In it, students can experiment with concepts such as gravity, friction, force, velocity, and so on, and see how changes in their value a ect the objects moving within the simulation. Microworlds|Newtonian or otherwise|are not new. They were rst conceptualized by Papert in his 1980 book Mindstorms," but in that era they were implemented as crude systems that required students to adjust the simulation via cryptic and error-prone command line interfaces e.g., Logo. The wide-spread introduction of graphical interfaces in the late 80's and early 90's then changed the way educators presented microworlds to students. The simulations became dynamic environments that students could alter on the y, usually by changing property settings on control panels and by directly manipulating the objects within the world. The Alternative Reality Kit, an intriguing Newtonian microworld built in 1987, is one such example Smith, 1987. In this paper, we claim that another evolutionary step is about to take place: microworlds will become group-aware by actively allowing several students to view and manipulate the simulation. We are investigating the application of collaboration-aware groupware technology and methods to build microworlds that re-enforce discussion by students around the work artifact. In our case, the work artifact is a Newtonian microworld called TurboTurtle, and the students could be children as young as 7 and as old as 17. Each student has their own computer screen and input devices. They share the view of the simulation, have telepointers to promote deictic references and gesturing, and can simultaneously manipulate the microworld. Since students do not have to be co-
Saul Greenberg
Abstract
TurboTurtle is a dynamic multi-user microworld for the exploration of Newtonian physics. With TurboTurtle, students can alter the attributes of the simulation environment, such as gravity, friction, and presence or absence of walls. Students explore the microworld by manipulating a variety of parameters, and learn concepts by studying the behaviours and interactions that occur. TurboTurtle has evolved into a group-aware" system where several students, each on their own computer, can simultaneous control the microworld and gesture around the shared display. TurboTurtle's design rationale includes concepts such as equal opportunity controls, simulation timing, concrete versus abstract controls, recoverability, and how strictly views should be shared between students. Teachers can also add structure to the group's activities by setting the simulation environment to an interesting state, which includes a set of problems and questions. Observations of pairs of young children using TurboTurtle highlight extremes in collaboration styles, from conict to smooth interaction. Finally, the technical work in making TurboTurtle group-aware is slight, primarily because it was built with a groupware toolkit called GroupKit.
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