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Planning for distributed wind generation under active management

Planning for distributed wind generation under active management
Planning for distributed wind generation under active management

Planning for distributed wind generation under active management mode

Jietan Zhang a ,?,Hong Fan b ,Wenting Tang a ,Maochun Wang a ,Haozhong Cheng c ,Liangzhong Yao d

a

Qinghai Electric Power Company,Xining,Qinghai Province 810008,China

b

Electric Power and Automation Engineering,Shanghai University of Electric Power,Shanghai 200090,China c

Department of Electrical Engineering,Shanghai Jiao Tong University,No.800,Dongchuan Road,Shanghai 200240,PR China d

Alstom Grid,Stafford ST174LX,UK

a r t i c l e i n f o Article history:

Received 11December 2010

Received in revised form 16October 2012Accepted 20October 2012

Available online 5December 2012Keywords:

Active management

Distributed wind generation Distribution network Planning

Plant growth simulation algorithm Probabilistic optimal power ?ow

a b s t r a c t

In the smart grid (SG),the active management (AM)mode will be applied for the connection and oper-ation of distributed generation (DG),which means real time control and management of DG units and distribution network devices based on real time measurements of primary system parameters.In this paper,a novel bi-level programming model for distributed wind generation (DWG)planning under AM mode is put forward.The model takes the maximum expectation of net bene?t of DWG as the upper level program objective,and takes the minimum expectation of generation curtailment as the lower level pro-gram objective.The impact of active management algorithm on improvement of branch power ?ow and node voltage is taken into account.A hybrid algorithm combining the plant growth simulation algorithm (PGSA)with probabilistic optimal power ?ow (POPF)algorithm is presented to solve the optimal plan-ning of DWG under AM mode.The case studies have been carried out on a 33-node distribution network,and the results verify the rationality of the planning model and the effectiveness of the proposed method.

ó2012Elsevier Ltd.All rights reserved.

1.Introduction

Currently,most distributed generation (DG)connect with the distribution network based on a so-called ‘‘?t and forget’’policy,which is consistent with passive network management [1,2].Un-der this mode,DG is without control in the operation,the task of balancing supply and demand as well as the task of securing fre-quency and voltage has been left solely to large production units,and therefore the positive role of DG on improving branch power ?ow and node voltage is weakened.In some cases the penetration of DG must be controlled strictly,and the bene?t and extension of DG have been con?ned.

Fortunately,smart grid (SG)has the potential to mitigate some of the dif?culties that are posed by high levels of DG [3–9].The ultimate smart grid de?ned by Gharavi and Ghafurian [10]as an electric system that uses information,two-way,cyber-secure com-munication technologies,and computational intelligence in an integrated fashion across electricity generation,transmission,sub-stations,distribution and consumption to achieve a system that is clean,safe,secure,reliable,resilient,ef?cient,and sustainable.Even though there is con?ict,the typical core of de?ning a smart grid consists of a bi-directional power ?ow,i.e.the consumers are also producing to the grid.SG is capable of delivering electricity from suppliers to consumers via a two-way digital technology,

effectively controlling the consumers’energy consumption [11–13].

Active management (AM)is emerging as one of SG operations for the connection and operation of DG.AM means real time con-trol and management of DG units and distribution network devices based on real time measurement of primary system parameters (voltage and current)[14,15].AM mode takes DG as one compo-nent of the distribution network,and active control is taken according to the requirement of the distribution system,that is,DG need to contribute to the task of securing a balance between electricity production and consumer demands [16].The applica-tion of AM is a challenge to the validity of traditional distribution network planning,operation,and commercial https://www.doczj.com/doc/ea18026105.html,work planning and operation should be synchronous when AM is applied in the distribution network:The determination of the connection capacity of DG should consider different operation situations that will appear in the future as well as the positive effect of AM to im-prove the technical level of the network.

In this paper,a novel bi-level programming model for siting and sizing of distributed wind generation (DWG)under AM mode is put forward,which breaks the ‘‘?t and forget’’installation policy of distributed generation in the passive distribution network.The model takes the maximum expectation of net bene?t of DWG as the upper level program objective,and takes the minimum expec-tation of generation curtailment with voltage and thermal constraints as the lower level program objective,taking into account the impact of active voltage management algorithm on improvement of branch power ?ow and node voltage.The plant

0142-0615/$-see front matter ó2012Elsevier Ltd.All rights reserved.https://www.doczj.com/doc/ea18026105.html,/10.1016/j.ijepes.2012.10.024

Corresponding author.

E-mail address:zhangjietan1980@https://www.doczj.com/doc/ea18026105.html, (J.Zhang).

growth simulation algorithm(PGSA)combined with probabilistic optimal power?ow algorithm(POPF)is applied to solve the opti-mal planning of DWG under AM mode.The proposed optimal plan-ning approach has been tested on a33-node distribution system to validate the rationality of the planning model and the effectiveness of the proposed method in the paper.

2.Bi-level planning model for DWG under AM mode

The main barrier for reaching higher levels of DG in distribution networks is the node voltage limit exceeding.Against this back-ground,this paper focuses on three AM schemes that aim to in-crease the power penetration of DG but maintain the network voltage within the statutory limits[14].

(1)Power generation curtailment(GC):GC controls the voltage by

constraining the active power of DG.

(2)On-load-tap-changer voltage control(OLTC):OLTC maintains

the network voltages within de?ned limits by actively changing the tap-changer setting at the primary substation.

(3)Reactive power compensation(RPC):RPC absorbs reactive

power at the point of DG connection to mitigate voltage rise.

AM mentioned above belongs to the general optimal power ?ow(OPF)problems.The main idea of an OPF applied in the con-text of active distribution networks is to determine the control val-ues of GC,OLTC and RPC schemes that minimize the cost of generation curtailment while satisfying voltage and thermal con-straints[17].In this particular case,the general optimization task is simpli?ed to a problem of minimizing the amount of generation of DWG that has to be curtailed in order to satisfy voltage and ther-mal constraints.

In the active distribution network with AM,the new role of dis-tribution networks requires unbundling of distribution network services and the development of commercial arrangements within which distribution network operators(DNOs)would carry out their responsibilities with the least cost and the highest ef?ciency, by using services from a number of potential providers[18].The fundamental business idea is that the DNO offers an AM service to the DG units allowing them to maximize connected capacity and generated electricity,and the DG owners’income through sell-ing power[19].The planning objective of DWG is to maximize the expectation of net bene?t of DWG by optimizing sites and size of DWG,which is shown as(1):

Max EeB NT?Max EeB SALàC CAPàC OPEàC CONàC AMT

?Max X

N DWG

i?1

ep wàc ràc AMTáEeE DWG;iTáPAer;nT

àX

N DWG

i?1ec etc ftc CONTáW i

!

e1T

where B N is the net bene?t value of planning scheme;B SAL is DWG owners’earnings from selling power;C CAP is the investment cost of DWG;C OPE is the operation cost of DWG;C CON is the connection cost of DG units;C AM is the cost of active management;N DWG is the number of candidate installation sites of DWG;p w is the price of wind power;c r is the unit operation and maintenance cost of DWG;c AM is the per-kWh active management cost of DWG;

E DWG,i is the effective power generated by i th DWG units;PA is the present value factor of uniform annual value;r is the discount rate;n is the service life of DWG;c e is the unit equipment invest-ment of DWG,including prime mover,wind turbine,generator, and auxiliary equipment such as reactive power compensation equipment;c f is the unit installation cost of DWG;c CON is the per-kWh connection charges of DWG units;and W i is the installed capacity of DWG at the i th candidate node.

Siting and sizing of DWG under AM mode is a typical bi-level programming problem,whose upper level program objective is maximum expectation of net bene?t of DWG,and whose lower le-vel program objective is minimum expectation of generation cur-tailment with voltage and thermal constraints.The bi-level programming model can be described as follows:

eP1TMax F?EeB NTe2Ts:t:06W i6W max

i

e3TX

N DWG

i?1

W i6q S max

load

e4TeP2TMin f?

X

P cur

Gi

e5T

s:t:P GiàP LiàP cur

Gi

?P inj

i

eU;h;TTe6T

Q GitQ CiàQ LiàQ cur

Gi

?Q inj

i

eU;h;TTe7T

S ij6S max

ij

e8T

U min

i

6U

i

6U max

i

e9T

P min

Gi

6P cur

Gi

6P max

Gi

e10T

Q min

Ci

6Q

Ci

6Q max

Ci

e11T

T min

k

6T

k

6T max

k

e12T

Q cur

Gi

?feP cur

Gi

Te13T

where W max

i

is the upper limit of installed capacity of DWG permit-

ted at the i th candidate installation node;S max

load

is the peak load of the distribution system;q is the upper limit of the proportion of in-stalled capacity of DWG to the load;P Li,Q Li are the active and reac-tive load at the i th node;P Gi,Q Gi are the active and reactive

generation at the i th node;P cur

Gi

;Q cur

Gi

are active and reactive genera-tion curtailment or increase(if possible)at the i th node;Q Ci is the reactive power generated/absorbed by a reactive compensation

equipment;P inj

i

;Q inj

i

are the active and reactive power injection at the i th node,T k is the tap setting of the tap-changer k;S ij is the load ?ows of branch ij;h is the node voltage angle;and U is the node voltage magnitude.

Eq.(2)is the upper level program objective function,that is max-imum expectation of net bene?t of DWG;Eq.(3)is the installed capacity constraints of DWG at the candidate nodes;Eq.(4)is pen-etration level limit of DWG.Eq.(5)is the lower level program objec-tive function,that is minimum expectation of generation curtailment.The optimization object need subject to not only power?ow equation constraints((6)and(7)),but also the branch thermal constraint(8)and network voltage limits(9).The amount of active generation curtailed will be limited by the capacity of DG connected(10).Reactive power support is limited by the capacity of reactive compensation equipments installed(11).The tap changer setting will be optimized and can vary within the bounds given by(12).Reactive power curtailment may be correlated with the ac-tive power curtailment,which is modeled through(13).

3.Probabilistic optimal power?ow under AM mode

3.1.Probabilistic optimal power?ow

The upper level program objective function of bi-level DWG planning is in the form of expectation.The simulation method can be used to solve this problem,but it will cost large computa-tional complexity,because every lower level program problem namely the OPF corresponding with every period must be calcu-lated.Furthermore,the operation of distribution network is af-fected and disturbed by some probabilistic factors,such as the forecast error of load and DWG output.Therefore,it is necessary to introduce the probabilistic optimal power?ow(POPF).

J.Zhang et al./Electrical Power and Energy Systems47(2013)140–146141

The main object of POPF is to obtain the probability distribution function of state variables according to the probabilistic factors such as the load and DWG output[20,21].The main methods of POPF include the semi-invariant method[20],?rst-order second-moment method[22]and point estimate method[21,23–26]. According to the number of the estimate point,the point estimate method is divided into two-point estimate method[23,25],three-point estimate method[26],and multiple-point estimate method [21,27].To solve the POPF problem under AM mode,this paper im-proved the three-point estimate method in[26].

3.2.Theory of the point estimate method

The main idea of the point estimate method is based on Taylor-series expansion with the function Z=h(X)corresponding with probabilistic variable X of n dimension.m?n times evaluation are performed with Z at m points using the high order moment of X,and the probabilistic density of Z can be obtained[24].

Take the function Z=h(X1,X2,...,X n)as an example,which is composed with n dimension probabilistic variable(X1,X2,...,X n), m points will be selected with every probabilistic variable X k (k=1,2,...,n).To simplify the problem,supposed the correlation coef?cient q ij between each variable is zero.Supposed the average value and standard deviation are l k and r k respectively,and the probability taking point x k,i from X k is p k,I,then:

x k;i?l ktn k;i r ke14T

X n k?1X m

i?1

p

k;i

?1e15T

X m i?1p

k;i

?

1

n

e16T

where n is the authority index.

Supposed k k,j is the ratio between the j th order center moment M j(X k)and the j th power of the standard deviation r k.

k k;j?M jeX kT

ekTj

e17T

If j=1,k k,j=0;if j=2,k k,j=1;if j=3,k k,j is called the skewness coef?cient of X k;else if j=4,k k,j is called the kurtosis coef?cient of X k.

Expand Z at the average value of X k(k=1,2,...,n)using the multivariate function Taylor-series expansion,and evaluate Z at m point with k k,i in turn,we can get:

X m i?1p

k;i

áen k;iTj?k k;je18TSolving(16)–(18)combinedly,the relation between the

bility of x k viz.p k and the authority index n can be obtained, evaluate points x k can be constructed,and the estimate every order moment of Z can be calculated.

EeZ lT%

X n

k?1X m

i?1

p

k;i

á?hel1;l2;...;x k;i;...;l nT l

where if l=1,E(Z)is the average value of Z;if l=2,E(Z)is dard deviation of Z.

r Z?

?????????????????????????????EeZ2TàEeZT2 q

When m=3,three points(one point is the average value one is in the left neighborhood,and the other one is in neighborhood)can be used to evaluate the probabilistic and the method is called three-point estimate method Both the resolution expression of n and p k can be

the fourth order moment of X k through3PEM.

n k;i?k k;3teà1T3ài

????????????????????

k k;4à3k2k;3

q

;i?1;2

n k;3?0

p

k;i

?eà1T3ài

en k;ien k;1àn k;2TT

;i?1;2

p

k;3

?1àp k;1àp k;2?1à1

k k;4àk2

k;3

8

>>>

>>>

><

>>>

>>>

>:

e21T

3.3.Semi-invariant of load and DWG output

The stochastic component of node load power is induced by load forecasting error or random?uctuation of load,and it can be expressed as random variable obeying standard normal distri-bution.Its?rst order semi-invariant equals its expected value, and the second order semi-invariant is the square variance,and the third and high order semi-invariant is zero.

Supposed PDF of wind speed obeys two parameter Weibull dis-tribution,it can be expressed as follows:

feVT?

k

c

V

c

kà1

expà

V

c

k

"#

e22T

where c and k are scale parameter and shape parameter respec-tively;V is the wind speed at the height of the hub of wind turbine.

The cumulative distribution function of wind speed is:

FeVT?1àexpà

V

c

k

"#

e23TThe piecewise function can be expressed as(see Fig.1):

P geVT?

006V6V ci

geVTV ci

P r V r

0V co6V

8

>>>

<

>>>

:

e24T

where V ci is the cut-in wind speed;V co is the cut-out wind speed;V r is the rated wind speed;P r is the rated output power of DWG.When wind speed is between V ci and V r,DWG output can be represented as g(V)which is a function of wind speed and called wind turbine output characteristic.

It can be seen that the cumulative distribution function of DWG active power is continuous in interval(0,P r),but it is discrete when P g=0and P g=P r.Discretization method can be applied to calculate every order moments of DWG active output,and then calculate every order semi-invariants.The discretization method is shown in Fig.2.The wind speed in interval(V ci,V r)is segmented into n

Fig.1.Typical DWG output power versus wind speed.

142J.Zhang et al./Electrical Power and Energy Systems47(2013)140–146

a m?HeP rTáeP rTmt

X n

i?1H iáP m

gi

e25T

Every order semi-invariant can be calculated based on the rela-tionship between the moment and semi-invariant[28]:

K1?a1

K mt1?a mt1à

X m

j?1C j

m

a j K màjt1

9

>=

>;e26T

where C j

m

is the combinatorial number taking j(j6m)elements from m(m>0)different elements.

3.4.Calculating procedures of POPF based on the three-point estimate method

The main calculating procedures of probabilistic optimal power ?ow under AM mode based on three-point estimate method are expressed as follows:

(1)Calculate semi-invariants of the probabilistic variables of

load power according to the probability distribution of load.

(2)Calculate semi-invariants of DWG output using discretiza-

tion method,and then calculate the third order and fourth order semi-invariants of nodal injection power.

(3)Calculate k k,j through(17).

(4)Select three estimating points for every probabilistic vari-

able,and calculate the corresponding authority index n k,I and the probability p k,I of each point.Furthermore,deter-mine three probabilistic variables x k,i(i=1,2,3)through

(14).

(5)Calculate the optimal power?ow for every probabilistic

variables x k,I,and save the result.

(6)Substitute the optimal power?ow results into(16)–(19),

and calculate the statistical characteristic values of state variables.

4.Algorithm of the bi-level program model including DWG

4.1.Plant growth simulation algorithm

The plant growth simulation algorithm,which characterizes the growth mechanism of plant phototropism,is a bionic random algo-rithm.It takes the feasible region of integer programming as the growth environment of a plant and determines the probability to grow a new branch at different nodes of a plant according to the change of the objective function.

By simulating the growth process of plant phototropism,a probability model is established in[29].In the model,a function g(S)is introduced to describe the environment of the node S on a plant.A plant grows from its root S0.The smaller the value of g(S),the better the environment of the node for growing a new branch.Supposed after growing M times,there are k nodes S M1, S M2,...,S Mk on the trunk,which means the function g(S)of the nodes S M1,S M2,...,S Mk satisfy g(S Mi)

P Mi?geS0TàgeS MiT

D M

;i?1;2;...;k

D M?

X k

i1

?geS0TàgeS MiT

8

>><

>>:e27TFrom(27),we can derivate

P k

i?1

P Mi?1,which means that the morphactin concentrations P M1,P M2,...,P Mk of the nodes S M1,S M2, ...,S Mk form a state space shown in Fig.3.

Selecting a random number d in the interval[0,1],it must be among one of P M1,P M2,...,P Mk shown in Fig.3,then the correspond-ing node called the preferential growth node will take priority of growing a new branch in the next step.In other words,S MT will take priority of growing a new branch if the selected d satis?es 06d6

P T

i?1

P MieT?1Tor

P Tà1

i?1

P Mi6d6

P T

i?1

P MieT?2;3;...;kT. Such process is repeated until there is no new branch to grow, and then the plant?nishes growth.

4.2.Bi-level DWG planning using PGSA

In some papers,the hybrid algorithm based on Monte-Carlo simulation(MCS)and meta-heuristic algorithms was applied to

greatly.The algorithm put

PGSA with POPF,which can

lem due to the large calculation

In the bi-level planning for

and size of DWG.The growth

sequence,such as f m1;m2;...;m

the number of candidate nodes.

node is m i P r.If m i=0,it means

order to keep consistent with

(27),set the object function g(á)

minimization form.

With the growth of the

nodes is continuously increasing.

nodes,the difference of their

smaller.This means the

and the randomicity of plant

convergence performance of

an upper limit N max

S

is set to the

iteration,if the scale of growth

compute P ave,namely the

the growth nodes,and abandon

concentrations are smaller than

sponding with one planning

on three-point estimate

the planning scheme,and the

tained.Feedback the

level,the upper-level program

The method realizes the global

mechanism of plant

The?owchart of planning for

combined with POPF algorithm

tions to the main steps are as

(1)Input the original data

(2)Generate initial growth

sponding solutions satisfy

solution if it does not

(3)Calculate the object

nodes,and take the node

S MT as the initial value of

erential growth node S B,

viz.g(S)min=g(S MT).

(4)Starting from the

lated plant grow towards both the positive and negative side of the coordinate axis,and produce some new growth nodes.

(5)Carry out the check of constraints for every new growth node

and compare with the morphactin concentration of the pref-erential growth node S B.If the nodes do not satisfy the con-straints,nor are their morphactin concentrations larger, abandon them and add the others into the growth node set.

(6)Calculate the lower-level program objective of the planning

scheme corresponding with every new growth node using the three-point estimate POPF method.

(7)Feedback the lower-level program objective to the upper

level,and calculate the upper-level program objective.Find the minimal object function value of the new growth nodes, and compare it with g(S)min.If it is smaller than g(S)min,then replace S min and g(S)min with it.

(8)Compare the scale of growth node set N S with N max

S

.If N S is

smaller than N max

S

,continue the next step;otherwise aban-don some nodes and continue the next step.

(9)Judge whether the stopping criterion is satis?ed.There are

two stopping criterions,the maximal consecutive iterative number and the given precision.If either of the stopping cri-terion is satis?ed,stop growth process and output the?nal results.Otherwise,continue the next step.

(10)Calculate the morphactin concentrations of all growth

nodes,and form a new morphactin concentration state space.

(11)Select a random number in the interval[0,1],and determine

the preferential growth node for the next iteration,and goto

(4).

5.Case study

The proposed model is applied into the Baran and Wu33-node distribution system,as shown in Fig.5[30].

The example is a12.66-kV system,and the peak loads are 5010kW and2510kvar.Supposed all the load nodes obey stan-dard normal distribution,and the square variance is0.1.The type of wind turbine is Mod-0;its rating power is100kW;the wind tur-bine is connecting with the distribution network through a trans-former whose transformer ratio is0.69/12.66;the power factor is 0.9lagging.The cut-in wind speed,cut-out wind speed and the rated wind speed are4.3m/s,17.9m/s,and7.7m/s respectively. The hub of wind turbine is30m high.

4.Flowchart of planning for DWG under AM mode using PGSA combined with POPF.

144

There are seven candidate nodes in the distribution system,and the wind speed distribution parameters at 10m are shown in Table 1.The penetration level limit of DWG is 50%;the upper limit of installed capacity of DWG at the candidate nodes is 1MW.The unit investment of DWG is 850$/kW;the unit installation cost of DWG is 200$/kW;the unit operation and maintenance cost of DWG is 10$/MWh.The service life of DWG is 20years,and dis-count rate is 0.1.The price of wind power is 95$/MWh.The node

voltage range is from 0.9to 1.05.The maximum capacity of branches between node 0and node 5is 5.6MW,and that of other branches is 3MW.The detailed data may be referred to [31].

The bi-level DWG planning optimal solution under AM mode is shown in Table 2,and which is compared with the chance con-strained programming solution of DWG under the passive mode [31].

It can be seen from Table 2that the optimal planning scheme of bi-level planning model is same with that of chance constrained programming when both con?dence level of voltage constraints (b u )and transmission capacities constraints (b l )are 0.8.In the above optimal planning scheme,besides 8DWG are installed at the node 30,10DWG are installed at both the node 17and node 5.It means the numbers of DWG at the node 17and node 5have reached the upper limit.The reason is that the higher the capacity factor,the more generated energy of DWG,and the more net ben-e?t expectation of DWG.For the optimal planning scheme satis?es the optimal power ?ow constraints of the lower level,the node voltage and the branch power ?ow are not violated.However,the maximum constraint violation probability of the chance con-strained programming scheme reach 14.40%and 0.42%respec-tively.This proves that AM mode can improve the node voltage and branch ?ow distributing effectively,and will enhance the pen-etration level limit of DG in distribution network.At the same time,AM is with the cost of decreasing generator output,therefore,the objective (8.0467?106$)is a bit smaller than that of chance con-strained programming model (8.0643?106$),but it also increases 9.46%compared with the optimal planning scheme objective with con?dence level of 1.00under passive mode (7.3512?106$).

Under the conventional passive mode,if the node voltage and branch power ?ow limits are to be avoided in the chance con-strained programming schemes,that is both con?dence level

of

Table 1

Wind speed distribution parameters (10m high).Node no.5101417212430Va (m/s) 4.9 3.5 3.9 5.8 4.1 3.8 4.4k 1.96 1.72 1.81 2.26 1.95 1.69 1.85c

5.54

3.96

4.41

6.55

4.6

4.27

4.94

Table 2

Comparison of the optimum solutions of different DWG planning models.Planning model

Bi-level planning

Chance constrained programming [20]Constraints b u /0.81b L

/

0.8

1

Optimal planning scheme 5(10),17(10),30(8)5(10),17(10),30(8)5(9),14(1),17(7),21(2),24(3),30(6)Objective (106$)

8.04678.06437.3512The largest node voltage off-limit probability (%)

/14.40(17)0The largest branch power ?ow off-limit probability (%)

/

0.42(l1)

Table 3

Comparison of 3PEM and Monte Carlo simulation method (the optimal scheme).Item

Method 3PEM

MCS (1000times)MCS (10,000times)Node No.Average value Standard deviation Average value Standard deviation Average value Standard deviation

Active power (MW)

0 3.90730.7412 3.93580.7386 3.8912

0.732250.42940.42270.42620.42200.42800.4223170.56170.42270.54760.41950.57200.4188300.28170.32520.27250.32160.28580.3249Reactive power (MVar)

0 1.80360.0558 1.80370.0548 1.80300.0555170.40980.01910.40570.02060,4054

0.0201320.41670.01510.41720.01600.4172

0.0162Node voltage (p.u)

0 1.01210.0116 1.012800119

1.01200.011810.99840.00930.99890.00970.99830.009620.99240.00760.99290.00810.99240.007930.98680.00600.98730.00640.98680.006340.97360.00330.97380.00370.97360.003750.97160.00290.97190.00320.97170.003260.96830.00170.96850.00180.96850.001870.96600.00330.96610.00300.96630.003080.96440.00620.96440.00580.96470.00589

0.96420.0067

0.96410.0064

0.96450.0064

Average calculating time (s)

24.29

126.96

1378.70

Energy Systems 47(2013)140–146145

b u and b l are set1.00,the optimal planning scheme is(5(9),14(1), 17(7),21(2),24(3),30(6)).Those DWG installed at the nodes with higher capacity factors(node17,node5and node30)have trans-formed to those nodes with lower capacity factors,which causes the objective decreases8.6%.That shows the predominance of AM in the other side.

Table3compares3PEM with the Monte Carlo method in evalu-ating the optimal planning scheme(5(10),17(10),30(8)),including active power,reactive power,node voltage,and computing time.It can be seen that the computing precision of3PEM is close to that of MCS(10,000times).However,the computing time of3PEM has shortened obviously.The average computing time of one3PEM computation is24.29s,which is19.1%of that of MCS(1000times), and1.8%of MCS(10,000times).

6.Conclusion

In this paper a bi-level programming model for siting and sizing of distributed wind generation under AM mode is presented.The model takes the maximum expectation of net bene?t of DWG as the upper level program objective,and takes the minimum expec-tation of generation curtailment as the lower level program objec-tive.Aiming at the character of bi-level probabilistic planning,the hybrid algorithm combining PGSA with POPF is applied to solve the planning model.The3PEM POPF algorithm is used to evaluate the planning schemes,and realizes the global optimization through the growth mechanism of plant phototropism.The following con-clusions can be obtained.

(1)The planning objective of DWG under AM mode is optimiza-

tion the sites and size of DWG,and get the maximum expec-tation of net bene?t taken into account branch power?ow and node voltage constraints.This is a bi-level programming problem,and the bi-level expectation programming model presented by this paper is reasonable.

(2)It can be seen from the case study results that AM mode can

bring into play the positive effect of DG on improving the branch power?ow and node voltage compared with passive mode.AM mode will increase the power penetration limit of DWG without violation constraints,and it is one effective management mode of smart grid for the connection and operation of DG.

(3)The solution method combined PGSA and POPF can solve the

bi-level probabilistic programming effectively.The POPF based on3PEM is more effective and less computation account than Monte-Carlo simulation method.

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WorldWind系列四:功能分析——Show Planet Axis、Show Position、Show Cross Hairs功能 来源:博客园作者:无痕客 今天主要看了Show Planet Axis、Show Position 、Show Cross Hairs 功能,主要是它们在菜单调用方式上都是很类似。代码如下: 显示位置信息 private void menuItemShowPosition_Click(object sender, System.EventAr gs e) { World.Settings.ShowPosition = !World.Settings.ShowPositio n; this.toolBarButtonPosition.Pushed = World.Settings.ShowPo sition; this.menuItemShowPosition.Checked = World.Settings.ShowPo sition; this.worldWindow.Invalidate(); } //显示中心十字标 private void menuItemShowCrosshairs_Click(object sender, System.Even tArgs e) { //控制中心十字标显示与否 World.Settings.ShowCrosshairs = !World.Settings.ShowCross hairs; this.menuItemShowCrosshairs.Checked = World.Settings.Show Crosshairs; this.worldWindow.Invalidate(); } 从上面的代码看,我们只能惊叹代码封装的很好,同样都调用 this.worldWindow.Invalidate();难道Invalidate()函数万能?!请参考我的Invalidate()方法学习(资料收集),原来该方法是界面区域失效,发送了重绘事件,将会调用WorldWindow.cs中重载了的OnPaint()。OnPaint方法里主要是调用了 Render()方法。所以我们的关键是看Render()中如何实现上面三个功能。(其实Render()中实现的功能很多,主要是控制界面绘制方面的,以后还会提到它的) Render()实现上面三个功能也大量使用了DirectX和Direct 3D方面的知识,请网上搜索学习相关知识或参看我的Direct3D学习(资料收集)。 显示中心十字线功能

程序流程图规范 1.引言 国际通用的流程图形态和程序: 开始(六角菱型)、过程(四方型)、决策(菱型)、终止(椭圆型)。在作管理业务流程图时,国际通用的形态:方框是流程的描述;菱形是检查、审批、审核(一般要有回路的);椭圆一般用作一个流程的终结;小圆是表示按顺序数据的流程;竖文件框式的一般是表示原定的程序;两边文件框式的一般是表示留下来的资料数据的存储。 2.符号用法 程序流程图用于描述程序内部各种问题的解决方法、思路或算法。 图1-1 标准程序流程图符号 1)数据:平行四边形表示数据,其中可注明数据名、来源、用途或其 它的文字说明。此符号并不限定数据的媒体。 2)处理:矩形表示各种处理功能。例如,执行一个或一组特定的操作,

从而使信息的值,信息形式或所在位置发生变化,或是确定对某一流向的选择。矩形内可注明处理名或其简要功能。 3)特定处理:带有双纵边线的矩形表示已命名的特定处理。该处理为 在另外地方已得到详细说明的一个操作或一组操作,便如子例行程序,模块。矩形内可注明特定处理名或其简要功能。 4)准备:六边形符号表示准备。它表示修改一条指令或一组指令以影 响随后的活动。例如,设置开关,修改变址寄存器,初始化例行程序。 5)判断:菱形表示判断或开关。菱形内可注明判断的条件。它只有一 个入口,但可以有若干个可供选择的出口,在对符号内定义各条件求值后,有一个且仅有一个出口被激活,求值结果可在表示出口路径的流线附近写出。 6)循环界限:循环界限为去上角矩形或去下角矩形,分别表示循环的 开始和循环的结束。一对符号内应注明同一循环标识符。可根据检验终止循环条件在循环的开始还是在循环的末尾,将其条件分别在上界限符内注明(如:当A>B)或在下界限符内注明(如:直到C

WorldWind WorldWind软件终极教程 2009年05月05日 1.新手上路篇 1.介绍: World Wind(以下简称“ WW ”)是一款可以让用户通过从太空视角全面观察地球表面的软件。WW以他优秀的卫星图库与地形资料,通过3D技术的应用,让用户拥有身临其境的感觉,这一切就象是真的一样。事实上你可以浏览世界上任何的角落,想象一下从高空观赏纵横交错的ANDES(安第斯山脉)山脉,进入美国大峡谷,从空中如飞机般的跃过ALPS(阿尔卑斯山 ) 以及走入非洲的撒哈拉沙漠 2.安装 2.1 下载 要想使用WW这款软件,首先肯定是要得到这款软件。目前WW通过几次版本的提升,已经由原来的共享变为了免费,如果你想要了解WW的最新信息以及下载WW,你可以方便的从本站或者官方网站中取得资料( 相比国外服务器的速度而言,当然是国内本土的下载速度更快一些了) 。 2.2 安装

相比较Google Earth来说NASA的安装方式并不是特别的友好,甚至是有些麻烦。 在你下载完其总共100多M的软件包后,先不要着急直接安装。因为你现在需要确认以下几件事情: 1. 电脑中是否安装了MS DX 9C( 要安装并顺利运行 NASA WW 电脑中首先需要具 备DX9) 2. 显卡驱动是否安装正确,没有任何错误 ( 这里并不要求你的显卡具备支持 DX9 的渲染特效的功能,但是至少是可以对 DX 渲染方式可以正确处理 ) 3. 操作系统可以是 Win9X、Win ME、 Win2000 、Winxp 其中的任何一个(暂时只 有兼容MS与MAC两种版本的WW) 4. 系统配置不低于 : 700 MHz 或更高主频的CPU 128 MB 以上内存 1 GB 以上的硬盘容量 显卡只要支持DX即可 确认了之后,便可以进行对WW的安装了。 初始过程中WW会首先要求用户( 强制 )安装一个DX的插件,使DX可以达到WW 的要求,其后一路下一步就可以搞定了。 3.配置文件

40首古诗词译文及赏析 1、汉江临泛/ 汉江临眺 唐代:王维 楚塞三湘接,荆门九派通。 江流天地外,山色有无中。 郡邑浮前浦,波澜动远空。 襄阳好风日,留醉与山翁。 译文 汉江流经楚塞又折入三湘,西起荆门往东与九江相通。远望江水好像流到天地外,近看山色缥缈若有若无中。 岸边都城仿佛在水面浮动,水天相接波涛滚滚荡云空。襄阳的风光的确令人陶醉,我愿在此地酣饮陪伴山翁。 鉴赏 此诗可谓王维融画法入诗的力作。 “楚塞三湘接,荆门九派通”,语工形肖,一笔勾勒出汉江雄浑壮阔的景色,作为画幅的背景。春秋战国时期,湖北、湖南等地都属于楚国,而襄阳位于楚之北境,所以这里称“楚塞”。“三湘”,一说湘水合漓水为漓湘,合蒸水为蒸湘,合潇水为潇湘,合称三湘;一说为湖南的湘潭、湘阴、湘乡。古诗文中,三湘一般泛称今洞庭湖南北、湘江一带。“荆门”,山名,在今湖北宜都县西北。“九派”,指长江的九条支流,相传大禹治水,开凿江流,使九派相通。诗人泛舟江上,纵目远望,只见莽莽古楚之地和从湖南方面奔涌而来的“三湘”之水相连接,汹涌汉江入荆江而与长江九派汇聚合流。诗虽未点明汉江,但足已使人想象到汉江横卧楚塞而接“三湘”、通“九派”的浩渺水势。诗人将不可目击之景,予以概写总述,收漠漠平野于纸端,纳浩浩江流于画边,为整个画面渲染了气氛。 “江流天地外,山色有无中”,以山光水色作为画幅的远景。汉江滔滔远去,好像一直涌流到天地之外去了,两岸重重青山,迷迷蒙蒙,时隐时现,若有若无。前句写出江水的流长邈远,后句又以苍茫山色烘托出江势的浩瀚空阔。诗人着墨极淡,却给人以伟丽新奇之感,其效果远胜于重彩浓抹的油画和色调浓丽的水彩。而其“胜”,就在于画面的气韵生动。王世贞说:“江流天地外,山色有无中,是诗家俊语,却入画三昧。”说得很中肯。而“天地外”、“有无中”,又为诗歌平添了一种迷茫、玄远、无可穷尽的意境,所谓“含不尽之意见于言外”。首联写众水交流,密不间发,此联开阔空白,疏可走马,画面上疏密相间,错综有致。 接着,诗人的笔墨从“天地外”收拢,写出眼前波澜壮阔之景:“郡邑浮前浦,波澜动远空。”正当诗人极目远望,突然间风起浪涌,所乘之舟上下波动,眼前的襄阳城郭也随着波浪在江水中浮浮沉沉。风越来越大,波涛越来越汹涌,浪拍云天,船身颠簸,仿佛天空也为之摇荡起来。风浪之前,船儿是平缓地在江面行驶,城郭是静止地立于岸边,远空是不动地悬于天际;风浪忽至,一切都动了起来。这里,诗人笔法飘逸流动。明明是所乘之舟上下波动,却说是前面的城郭在水面上浮动;明明是波涛汹涌,浪拍云天,却说成天空也为之摇荡起来。诗人故意用这种动与静的错觉,进一步渲染了磅礴水势。“浮”、“动”两个动词用得极妙,使诗人笔下之景活起来了,诗也随之飘逸起来了,同时,诗人的一种泛舟江上的怡然自得的心态也从中表现了出来,江水磅礴的气也表现了出来。诗人描绘的景象是泛舟所见,舟中人产生了一种动荡的错觉,这种错觉也正好符合诗句中的汉水的描写,所以这两个词用得极其恰当。 “襄阳好风日,留醉与山翁。”山翁,即山简,晋人。《晋书·山简传》说他曾任征南将军,镇守襄阳。当地习氏的园林,风景很好,山简常到习家池上大醉而归。诗人要与山简共谋一醉,流露出对襄阳风物的热爱之情。此情也融合在前面的景色描绘之中,充满了积极乐观的情绪。尾联诗人直抒胸臆,表达了留恋山水的志趣。 这首诗给读者展现了一幅色彩素雅、格调清新、意境优美的水墨山水画。画面布局,远近相映,疏密相间,加之以简驭繁,以形写意,轻笔淡墨,又融情于景,情绪乐观,这就给人以美的享受。王维同时代的殷璠在《河岳英灵集》中说:“维诗词秀调雅,意新理惬,在泉为珠,着壁成绘。”此诗很能体现这一特色。同时,也

1. c#中字体显示????,怎么修改,求教,,, 长沙-GIS-唐胡子(32326910) 10:44:40 还在搞这个啊 长沙-GIS-唐胡子(32326910) 10:44:54 这个问题,肯定很多人解决过啊 成都-计算机-zero(287932929) 10:48:10 我将楼主提供的地名包放在add_on和config下,然后将\PluginSDK\TiledPlacenameSet.cs 的读取PlacenameFile的地方编码方式做了修改,将ASCII方式改为Default方式,编译后。 就能正确显示: using (BinaryReader dataFileReader = new BinaryReader(dataFileStream, System.Text.Encoding.ASCII)) 编码方式改为:Default using (BinaryReader dataFileReader = new BinaryReader(dataFileStream, System.Text.Encoding.Default)) 把省区划的xml的UTF-8修改为gb2312; 在shapefilelayer.cs中 private void loadShapeFile(string shapeFilePath) { FileInfo shapeFile = new FileInfo(shapeFilePath); FileInfo dbaseFile = new FileInfo(shapeFile.FullName.Replace(".shp", ".dbf")); System.Random random = new Random(https://www.doczj.com/doc/ea18026105.html,.GetHashCode()); ArrayList metaValues = new ArrayList(); if(m_ShapeTileArgs.DataKey != null && dbaseFile.Exists) { using (BinaryReader dbfReader = new BinaryReader(new BufferedStream(dbaseFile.OpenRead()), System.Text.Encoding.Default ))//修改为default时,name字段显示汉字,但存在乱码,用ASCII时name字段是“???” 1.从ARCGIS中导出的中国政区图shp文件,显示字段为汉字省名称,但是加载后总是以问号显示,把ShapeFileLayer.cs中的 using (BinaryReader dbfReader = new BinaryReader(new BufferedStream(dbaseFile.Op enRead()), System.Text.Encoding.Default )) 3.得到shp文件编码 public System.Text.Encoding GetFileEncoding(string fileFullName) { FileStream fs = new FileStream(fileFullName, FileMode.Open, FileAccess.Read); System.Text.Encoding r = GetType(fs); fs.Close(); return r; }

《会计实务训练与考核》 电算化部分上机指南 目录 第一章财务软件的操作流程 1 第二章系统初始化 2 第三章日常业务处理 7 第四章 UFO报表 13 第五章现金流量表 17 用友财务软件应用指南 用友ERP-U8是由用友软件股份有限公司开发的,是目前国内使用最多的软件,国内用户已近40万家,徐州用户近2000家。用友ERP-U8的产品专门多,包括财务产品、供应链产品、财务业务一体化、WEB购销存、治理驾驶舱等等。本次考核由于时刻和

手工操作内容的限制,我们只选择与手工操作配套的部分,即财务产品中的系统治理、总账系统和UFO报表等。 财务软件的操作流程 第二章系统初始化 一、建立账套

为实施企业建立一整套包括业务处理规则、证、账、表等的一套账。这项工作在系统治理模块下完成。系统治理模块提供了一个系统集中治理的操作平台,包括新建账套、新建年度账、账套修改和删除、账套备份,操作员的建立、角色的划分和权限的分配等功能。系统治理的使用者为企业的信息治理人员:系统治理员(Admin)和账套主管。 第一步用户登录注册; ①选【开始】--【程序】--【用友ERP-U8】--【系统服务】--【系统治理】,进入系统治理模块; ②选【系统】--【注册】,进入登录系统界面。 在“操作员”栏:输入注册身份:admin↙ 在“密码”栏输入密码:密码为空,直接按回车键。 在“账套”栏:选入备选数据源。 第二步设置用户(建账前先指定用户,便于为所建账套指定账套主管); 以系统治理员(Admin)身份注册后, 选【权限】--【用户】,增加两位用户:自己(账套主管)和合作者(负责审核凭证) 第三步建立账套

19观沧海 作者:曹操 东临碣石,以观沧海。 水何澹澹,山岛竦峙。 树木丛生,百草丰茂。 秋风萧瑟,洪波涌起。 日月之行,若出其中。 星汉灿烂,若出其里。 幸甚至哉,歌以咏志。 白话译文: 东行登上碣石山,来观赏那苍茫的海。 海水多么宽阔浩荡,山岛高高地挺立在海边。 树木和百草丛生,十分繁茂, 秋风吹动树木发出悲凉的声音,海中涌着巨大的海浪。 太阳和月亮的运行,好像是从这浩瀚的海洋中发出的。 银河星光灿烂,好像是从这浩瀚的海洋中产生出来的。 我很高兴,就用这首诗歌来表达自己内心的志向。 赏析 借景抒情,把眼前的海上景色和自己的雄心壮志很巧妙地融合在一起。《观沧海》的高潮放在诗的末尾,它的感情非常奔放,思想却很含蓄。不但做到了情景交融,而且做到了情理结合、寓情于景。因为它含蓄,所以更有启发性,更能激发我们的想像,更耐人寻味。过去人们称赞曹操的诗深沉饱满、雄健有力,“如幽燕老将,气韵沉雄”,从这里可以得到印证。全诗的基调为苍凉慷慨的,这也是建安风骨的代表作。 20饮酒(其五) 作者:陶渊明 结庐在人境,而无车马喧。 问君何能尔?心远地自偏。 采菊东篱下,悠然见南山。

山气日夕佳,飞鸟相与还。 此中有真意,欲辨已忘言。 白话译文: 我家建在众人聚居的繁华道,可从没有烦神应酬车马喧闹。 要问我怎能如此之超凡洒脱,心灵避离尘俗自然幽静远邈。 东墙下采撷清菊时心情徜徉,猛然抬头喜见南山胜景绝妙。 暮色中缕缕彩雾萦绕升腾,结队的鸟儿回翔远山的怀抱。 这之中隐含的人生的真理,想要说出却忘记了如何表达。 赏析 本诗是陶渊明组诗《饮酒》二十首中的第五首。诗的意象构成中景与意会,全在一偶然无心上。‘采菊’二句所表达的都是偶然之兴味,东篱有菊,偶然采之;而南山之见,亦是偶尔凑趣;山且无意而见,菊岂有意而采?山中飞鸟,为日夕而归;但其归也,适值吾见南山之时,此亦偶凑之趣也。这其中的“真意”,乃千圣不传之秘,即使道书千卷,佛经万页,也不能道尽其中奥妙,所以只好“欲辨已忘言”不了了之。这种偶然的情趣,偶然无心的情与景会,正是诗人生命自我敞亮之时其空明无碍的本真之境的无意识投射。大隐隐于市,真正宁静的心境,不是自然造就的,而是你自己的心境的外化。 千古名句:“采菊东篱下,悠然见南山”,表达了诗人悠然自得、寄情山水的情怀。 21送杜少府之任蜀州 作者:王勃 城阙辅三秦,风烟望五津。 与君离别意,同是宦游人。 海内存知己,天涯若比邻。 无为在岐路,儿女共沾巾。 译文 古代三秦之地,拱护长安城垣宫阙。 风烟滚滚,望不到蜀州岷江的五津。

OpenLayers 1 OpenLayers简介 OpenLayers是由MetaCarta公司开发的,用于WebGIS客户端的JavaScript包。它实现访问地理空间数据的方法都符合行业标准,比如OpenGIS的WMS和WFS规范,OpenLayers 采用纯面向对象的JavaScript方式开发,同时借用了Prototype框架和Rico库的一些组件。采用OpenLayers作为客户端不存在浏览器依赖性。由于OpenLayers采用JavaScript语言实 现,而应用于Web浏览器中的DOM(文档对 象模型)由JavaScript实现,同时,Web浏览 器(比如IE,FF等)都支持DOM。OpenLayers APIs采用动态类型脚本语言JavaScript编写, 实现了类似与Ajax功能的无刷新更新页面, 能够带给用户丰富的桌面体验(它本身就有一 个Ajax类,用于实现Ajax功能)。 目前,OpenLayers所能够支持的Format有:XML、GML、GeoJSON、GeoRSS、JSON、KML、WFS、WKT(Well-Known Text)。在OPenlayers.Format名称空间下的各个类里,实现了具体读/写这些Format的解析器。OpenLayers所能够利用的地图数据资源“丰富多彩”,在这方面提供给拥护较多的选择,比如WMS、WFS、GoogleMap、KaMap、MSVirtualEarth、WorldWind等等。当然,也可以用简单的图片作为源。 在操作方面,OpenLayers 除了可以在浏览器中帮助开发者实现地图浏览的基本效果,比如放大(Zoom In)、缩小(Zoom Out)、平移(Pan)等常用操作之外,还可以进行选取面、选取线、要素选择、图层叠加等不同的操作,甚至可以对已有的OpenLayers 操作和数据支持类型进行扩充,为其赋予更多的功能。例如,它可以为OpenLayers 添加网络处理服务WPS 的操作接口,从而利用已有的空间分析处理服务来对加载的地理空间数据进行计算。同时,在OpenLayers提供的类库当中,它还使用了类库Prototype.js 和Rico 中的部分组件,为地图浏览操作客户端增加Ajax效果。 2 Openlayers基本使用方法 Openlayers是使用Javascript编写的脚本,与网页设计技术密切相关,因此在使用之前需要掌握一定得相关知识,例如html、css、javascript等。编辑工具推荐使用:EditPlus。 1)下载并拷贝源代码即相关文件 到Openlayers官方网站https://www.doczj.com/doc/ea18026105.html,下载源代码压缩包,解压后可以看到其中的一些目录和文件。需要拷贝的文件和目录有:根目录下的【OpenLayer.js】文件、根目录下的【lib】目录、根目录下的【img】目录、根目录下的【theme】目录。将这4项内容拷贝到你网站的Scripts目录下(当然,这个只是例子,自己的网站程序目录结构自己说了算,只要保证OpenLayers.js,/lib,/img,/theme在同一目录中即可)。

金蝶供应链初始化流程介绍-非常贴近财务人员

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第一部分 金蝶供应链初始化流程介绍 教学目的:通过学习掌握供应链与其他系统的联系 教学要求:了解各模块间的联系 教学重点、难点:供应链与其他系统的联系 教学内容:整体操作流程 整体操作流程 采购(进销售 (出收货通知单 发货通 知(出销售发票 工 资管理系 统 应付帐款系 统 仓存管理系 统 应收帐款系 统固定资产系 统 存货核算系 统 商机(服 务)系统

凭总帐

建立分支机建立门配置传 与其他模块进 存货核算

第二部分供应链系统初始化处理 教学目的:通过学习掌握如何建立一个新帐套并对其进行初始化设置 教学要求:①掌握供应链系统初始化流程及操作 ②了解系统参数的设置 ③熟悉各基础资料的设置 ④初始数据录入 教学重点、难点:①初始化操作流程 ②了解核算参数设置的含义 ③基础资料的设置 教学内容:初始化准备工作、初始化的操作流程 序言 1、什么是初始化?(提问:请尝试以自己的语言解释什么是初始化?) ◎名词解释:初始化就是完成手工与电脑系统的工作交接、数据交接、管理交接 2、初始化的重要作用和影响。(教材中说明) 一、初始化准备工作 1、新建帐套 2、在总帐系统进行引入会计科目工作 二、初始化流程 注意:供应链系统,只要在其中任意一个系统进行初始化,其他系统也会同时完成) 1、“工具”→“系统初始化”→“核算参数设置”(细讲各参数的设置对后日的影响) ◆核算方式

1 流水灯流程框图: N Y 流水灯程序: /*********************************************************** 描述 : LED 流水灯的控制; 8个LED 会进行流水灯的演示; ***********************************************************/ #include #define uchar unsigned char temp 值赋给P1口延时 Temp 值左移一位 i=i+1 i=0 temp=oxfe 开始 i<8

#define uint unsigned int sbit PP=P3^6 ; /*********************************************************** * 名称 : Delay() * 功能 : 延时,延时时间为 10ms * del * 输入 : del * 输出 : 无 ***********************************************************/ void Delay(uint del) { uint i,j; for(i=0; i

NASA World Wind开源项目配置详解 NASA World Wind是C#开发的个人电脑上的开源的3D图形虚拟地球系统。它结合了美国国家航空航天局(NASA)从卫星拍摄的图像,这些图像应用于Blue Marble,Landsat7,SRTM, MODIS以及其它更多的地方。 用户可以到这里下载.net源码https://www.doczj.com/doc/ea18026105.html,/ 下载后,打开解决方案,使用的是.net2.0,一共有16个项目组成。 编译整个项目,发现缺少几个程序集的引用。 PluginSDK项目需三个引用: Microsoft.DirectX,Microsoft.DirectX.Direct3D,Microsoft.DirectX.Direct3D X; WorldWind项目需四个引用: Microsoft.DirectX,Microsoft.DirectX.Direct3D,Microsoft.DirectX.Direct3D X,Microsoft.DirectX.DirectInput。 首先了解一下DirectX: 微软的DirectX上一系列技术的集成,用来提供Windows平台多媒体运行的 API,支持应用程序、多媒体软件和3D游戏极其声效。 我下载的是DirectX9.0c简体中文版,下载地址是:https://www.doczj.com/doc/ea18026105.html,/system/patch/download_17624.html 解压后,运行程序DXSETUP.exe。

完成后,打开目录C:\WINDOWS\https://www.doczj.com/doc/ea18026105.html,\DirectX for Managed Code 发现会有十个文件 将1.0.2902.0目录的四个dll文件copy到其他的目录中,引用到项目中,发现还是编译不通过,于是我将1.0.2911.0目录的Microsoft.DirectX.Direct3DX.dll进 行替换,编译成功! 设置WorldWind为启动项目,Ctrl+F5,启动后出现一个图片的界面,过了半分钟的样子,出现一个directX版本的错误,哦,这个还是有办法的,呵呵。运行命令"dxdiag",点击“display”,将所有的设置为"Enabled".

数据初始化全流程 完成税控服务器上架后,需要对系统必要的数据进行初始化,具体流程如下 系统中操作流程如下: 一、添加服务器列表即添加核心板。具体流程如下: (1) 使用admin 登录税控服务器管理系统,点击左边菜单树中的“税控服务器管 理”-“税控服务器管理”,点击“添加服务器”标签,如下图所示: 注意: 服务器名称:服务器的名称 服务器型号:TCG-01S 税控服务器IP 地址:税控服务器的实际IP 地址 税控服务器端口号:12366 统一受理IP 地址:税局发票上传IP 地址 统一受理端口号:税局发票上传端口号 启用标志:主核心板的状态为“启用”,备用核心板状态为“停用”。 (2) 所有信息填写完毕后,点击上图中的”添加服务器信息“即可。 (3) 点击“服务器列表”标签,在操作栏,点击“ ”修改按钮,可将“服务器名 称”按照对应税号修改为纳税人名称,修改完毕后,点击“ ”进行保存即

可,截图如下: 二、在税号下创建分公司管理员。具体流程如下: (1)使用admin登录税控服务器管理系统,点击左边菜单树中的“税控服务器管理”-“税控服务器管理”,点击“服务器列表”标签,如下图所示: (2)点击上图中的“”管理按钮,进入到税控服务器管理界面,点击“系统管理”-“操作员管理”,进入到操作员管理界面,截图如下:

注意: 用户类型:选择管理员。 操作员代码:登录系统的用户帐号。 操作员名称:登录系统的用户人员名称。 启用标志:启用 (3)所有信息维护完毕后,点击“保存”即可。 三、使用分公司管理员创建开票终端。具体流程如下: (1)使用分公司管理员登录税控服务器管理系统,点击左边菜单树中的“开票终端管理”-“开票终端管理”,点击“添加开票终端”,如下图所示:

系统总体业务流程图 图 1-1: 系统初始化流程说明 1-1: 目标进行系统初始化,使系统进入可处理正常业务状态。 业务背景系统安装后,系统的参数、基础资料等都没有,系统还不能处理具体的业务。用户必须根据实际的业务管理需要,设置系统控制参数、科目、核算项目等后,才能处理正常业务。 适用 范 围 在系统启用之前,适用所有的行业。 序号责任部门责任人1 启用账套——启用账套,设置账套期间财务/IT部系统管理 员 2 系统参数设置——设置系统参数财务/IT部系统管理 员 3 用户设置——将系统用户和每个用户的权限在系统中 设定 财务部主管会计 4 币别设置——在系统中设置币别财务部总账会计 5 核算项目、科目设置——在系统中设置科目和核算项 目 财务部主管会计 6 期初数据录入——将期初余额录入系统财务部主管会计 7 数据检查——系统检查期初余额是否平衡,数据是否 正确还需人工做进一步的检查。 财务部主管会计

凭证处理业务流程说明相关内容见表2-2: 目标实现凭证的生成、审核、过账和修改所有的操作 业务背景用户在实现初始化之后,系统已成功启用。财务人员需要以凭证的方式记录公司发生的实际经济业务。同时,按照实际的工作要求,对凭证进行审核、过账,发现错误进行修改。 适用范围1.1、各种方式产生的凭证,包括手工凭证、系统生成凭证、模式凭证、自动转 账凭证、外部引入凭证、凭证冲销等6种方式产生的凭证。 2.2、凭证的所有处理业务,凭证的生成、审核、过账、修改和删除。 序号责任部门责任人 1 新增凭证——手工录入、引入或者系统产生的凭证。财务部会计 2 凭证查询——查询符合条件的凭证财务部财务人员 3 凭证审核——会计主管审核系统内的凭证财务部总账会计 4 凭证反审核——发现已审核的凭证错误,将其反审核, 进入可修改状态 财务部主管会计 5 凭证过账——将符合条件的凭证登记到账薄财务部主管会计 6 凭证反过账——发现已过账的凭证错误,将其反过账, 进入可修改状态 财务部主管会计 凭证录入与审核 业务流程图

2014年高考诗歌阅读真题与赏析资料汇编 一、(新课标卷Ⅰ)阅读下面这首宋词,完成8~9题。 阮郎归无名氏① 春风吹雨绕残枝,落花无可飞。小池寒渌欲生漪,雨晴还日西。 帘半卷,燕双归。讳愁无奈眉②。翻身整顿着残棋,沉吟应劫迟③。 [注]①作者一作秦观。②讳愁:隐瞒内心的痛苦。③劫:围棋术语。 8.词上半阕的景物描写对全词的感情抒发起了什么作用?请结合内容分析。(5分) 【试题答案】奠定了词的情感基调。春风吹雨,残红满地,词一开始就给人以掩抑低回之感; 接下来写风雨虽停,红日却已西沉,凄凉的氛围非但没有解除,反而又被抹上了一层暗淡的暮色。 【试题考点】鉴赏诗歌的表达技巧——结构作用 【试题解析】词的上阕主要在写景,描写的是凄凉的景象场面:丝丝细雨被和暖的春风吹送着, 飘洒在繁花落尽的树枝上。满地落花被雨水浇湿,再也飞舞不起来了。池塘里碧绿的水面上随风荡 起微微的波纹。雨晴了,一轮斜阳依旧出现在西方的天空上。在“哀”的暮春景色中,抒发的是一 种“哀”情,奠定了全词的感情基调。 9.末尾两句表现了词中人物什么样的情绪?是如何表现的?请简要阐述。(6分) 【试题答案】末尾两句表现了词中人物思绪纷乱、无法排遣的愁情。是通过人物自身的动作来 表现的。回身整理残棋并想续下,借以转移愁情,可又因心事重重,以致犹豫不决,落子迟缓。 【试题考点】分析评价诗歌的思想内容 【试题解析】下阕写当主人公在百无聊赖中卷起珠帘,恰恰看到燕子成双成对地飞来飞去。这更加勾起了女主人公的一怀愁绪。这种愁绪实在难以排遣,满心想加以掩饰,无奈却在紧蹙的双眉 中显露出来。于是只好强打精神,翻身起来,继续下那盘没有下完的棋。岂料应劫之际,她竟然举 棋不定,沉吟半晌,难以落子。最后两句借续下残棋的动作来表达自己难以排遣的愁情。 【《阮郎归》诗歌赏析】“春风”二句起调低沉,一开始就给人以掩抑低回之感。春风吹雨已 自凄凉,而花枝已凋残矣,风雨仍依旧吹打不舍,景象更为惨淡。“落花无可飞”,写残红满地, 沾泥不起,比雨绕残枝,又进一层,表面上写景,实际上渗透着悲伤情绪。两句为全篇奠定了哀婉 的基调。 三、四句写雨霁天晴,按理色调应该转为明朗,情绪应该转为欢快。可是不然,词的感情旋律 仍旧脱离不了低调。盖风雨虽停,而红日却已西沉。因此凄凉的氛围非但没有解除,反而又被抹上 了一层暮色。 词的下阕,由写景转入抒情,仍从景物引起。“帘半卷,燕双归”,开帘待燕,亦闺中常事, 而引起下句如许之愁,无他,“双燕”的“双”字作怪耳。其中燕归又与前面的花落相互映衬。花 落已引起红颜易老的悲哀;燕归来,则又勾起不见所欢的惆怅。燕双人独。怎能不令人触景生愁, 于是迸出“讳愁无奈眉”。 一个警句。所谓“讳愁”,并不是说明她想控制自己的感情,掩抑内心的愁绪,而是言“愁” 的一种巧妙的写法。“讳愁无奈眉”,就是对双眉奈何不得,双眉紧锁,竟也不能自主地露出愁容,语似无理,却比直接说“愁上眉尖”艺术性高多了。 结尾二句,紧承“讳愁”句来。因为愁词无法排遣,所以她转过身来,整顿局上残棋,又从而 着之,借以移情,可是着棋以后,又因心事重重,落子迟缓,难以应敌。这个结尾通过词中人物自 身的动作,生动而又准确地反映了纷乱的愁绪。 二、(新课标卷II)古代诗歌阅读(11分) 阅读下面两首诗,完成8-9题。 含山店梦觉作 [唐]韦庄 曾为流离惯别家,等闲挥袂客天涯。灯前一觉江南梦,惆怅起来山月斜。 1

基于World Wind的二次开发概要设计说明书 [V1.0版本] 二零一一年十月

修订历史记录 日期版本作者审核人审核时间备注2011年10月22日V1.0版本刘美琳 石少华 赵昱昀

目录1.引言.... 1.1 编写目的... 1.2 背景... 1.3 定义... 1.4 参考资料... 2.总体设计.... 2.1 需求规定... 2.1.1系统功能... 2.1.2系统性能... 2.1.3输入输出要求... 2.1.4数据管理能力要求... 2.1.5故障处理要求... 2.1.6其他专门要求... 2.2 运行环境... 2.2.1设备... 2.2.2支持软件... 2.2.3接口... 2.2.4控制... 2.3 基本设计概念和处理流程... 2.4 结构... 2.5 功能需求与系统模块的关系... 2.6 人工处理过程... 2.7 尚未解决的问题... 3.接口设计.... 3.1用户接口... 3.2外部接口... 3.3内部接口... 4.运行设计.... 4.1运行模块组合... 4.2运行控制... 4.3运行时间... 5.系统数据结构设计.... 5.1逻辑结构设计要点... 5.2物理结构设计要点... 5.3数据结构与程序的关系... 6.系统出错处理设计... 6.1出错信息... 6.2补救措施... 6.3系统维护设计... 1引言

1.1编写目的 [说明编写这份概要设计说明书的目的,指出预期的读者。] 1.2背景 A.[待开发软件系统的名称;] B. [列出本项目的任务提出者、开发者、用户。] 1.3定义 [列出本文件中用到的专门术语的定义和外文首字母组词的原词组。] 1.4参考资料 [列出有关的参考资料。] 2总体设计 2.1需求规定 [说明对本系统的主要的输入输出项目、处理的功能性能要求。包括] 2.1.1 系统功能 2.1.2 系统性能 2.1.2.1精度 2.1.2.2时间特性要求 2.1.2.4可靠性 2.1.2.5灵活性 2.1.3 输入输出要求 2.1.4 数据管理能力要求

K3账套新建流程 K3中间层帐套管理一、新建帐套 --帐套管理—新建按钮(白纸按钮)中间层开始操作流程:服务器电脑----程序--K3帐套号、帐套名不能重复但可修改,但帐套类型选择标准供应链解决方案不注意点: 10分钟的时间。—可更改,建账大约需要5

二、设置参数和启用帐套帐套管理—设置按钮中间层开始操作流程:服务器电脑----程序--K3--公司名称可改,其他参数在帐套启用后即不可更改(包括总账启用期间)注意点:数据库尚未完成建账初始化,系统不易引发的错误:如果帐套未启用就使用,系统会报错。能使用 三、用户管理:新建用户、功能授权. 操作流程:K3主控台—进入相应帐套—系统设置—用户管理 1、用户组:注意系统管理员组与一般用户组的区别 2、新建用户 操作流程: K3主控台—进入相应帐套—系统设置—用户管理—用户按钮—用户菜单—新建用户

、注意系统管理员的新增(即用户、只能是系统管理员才可以增加人名b 注意点:a 组的选择)、用户授权 3主控台—进入相应帐套—系统设置—用户管理—用户管理—用户管理,选K3 操作流程:中用户,单击用户管理菜单—功能权限按钮

、只能是系统管理员才可以给一般用户进行授权,报表的授权应在报表系统工具a注意点:—〉报表权限控制里给与授权。; b、系统管理员身份的人不需要进行授权; c、具体权限的划分—“高级”中处理 4、查看软件版本及版本号主界面,“帮助”菜单下的“关于” K3. 5、查看系统使用状况启动中间层—〉系统—〉系统使用状况,查看加密狗信息;网络控制工具 6、 而这会未能释放此网络任务,如果一任务启动时间很长,那极有可能是发生意外事件,功能来所以需要手动清除该任务。可使用[清除当前任务]限制其它用户使用相关互斥任务,执行清除网络任务。金蝶软件提供了网络控制功能,为保证网络环境中多用户并发操作时财务数据的安全性,

流程图 本标准等同采用国际标准ISO 5807—1985《信息处理一数据流程图、程序流程图、系统流程图程序网络图、系统资源图的文件编制符号及约定》。 l 引言 图可广泛用于描绘各种类型的信息处理问题及其解决方法。图的使用并不局限于本标准中所给的 示例 在应用中,所确定的内部规则必须满足实际的处理或数据规格说明。本标准中给出一些指导性原 则,遵循这些原则可以增强图的可读性,有利于图与正文的交叉引用。 图中包含具有确定含义的符号、简单的说u性文字和各种连线。本标准不涉及说明性文字的内容, 但每个符号有一个无歧义。有意义的名称,它在整个文件编制中都是一致的。 图可以分为洋细程度不同的层次,层次的数目取决于信息处理问题的规模和复杂性。这些详细程 度不同的层次应用使得不同部分及各部分间相互关系可作为一个整体来理解。 正常情况下,要有一个表明整个系统主要组成部分的图,该图作为层次图形的顶层图。每一较低 层都对上一层的一个或几个部分进行详细的描述。 2 范围和应用领域 本标准规定在信息处理文件编制中使用的各种符号,并给出在下列图中使用这些符号的约定: a.数据流程图; b.程序流程图; c.系统流程图; d.程序网络图; e.系统资源图。 3 引用标准 GB 5271.1—85数据处理词汇 01部分基本术语 4 术语 GB 5271.1中的术语以及下述术语适用于本标准。 4.1 基本符号 当处理或数据媒体的精确性质或形式未知时,或者当不需要描述实际的媒体时所使用的符号。 4.2 特定符号 当处理或数据媒体的精确性质或形式已经知道时,或者当需要描述实际的媒体时所使用的符号。 4.3 流程图 对某一个问题的定义、分析或解法的图形表示,图中用各种符号来表示操作、数据、流向以及装 置等。 5 数据流程图 数据流程图表示求解某一问题的数据通路。同时规定了处理的主要阶段和所用的各种数据媒体。 数据流程图包括: a.指明数据存在的数据符号,这些数据符号也可指明该数据所使用的媒体; b.指明对数据执行的处理的处理符号,这些符号也可指明该处理所用到的机器功能; c.指明几个处理和(或)数据媒体之间的数据流的流线符号;

代赠 唐代:李商隐 楼上黄昏欲望休,玉梯横绝月中钩。 芭蕉不展丁香结,同向春风各自愁。 作品赏析 这是一首描写女子思念情人的诗作,诗中的女子,深居高楼,黄昏时分,她因百般无聊赖而思念起情人来了。对其思念越浓,就越渴望和他相见,恨不得他立刻出现在楼前,她按耐不住自己焦急的心情,走到楼头前,想去眺望远处,看看他来了没有。可是又蓦然想到他必定来不了,他怎么知道自己在思念他呢?就算知道又如何能这么快就来到跟前呢?她只得止步,折回楼内,欲望还休,欲见而无法相见,这种复杂的心情折磨得她坐立难安,满楼徘徊。此句把女子复杂矛盾的心理和孤寂无聊的失望情态完全表现出来了。 楼上黄昏欲望休,玉梯横绝月如钩 “楼上黄昏”,点明时间是薄暮时分,地点是在高楼之上。在中国古代诗词作品里,这样的环境有很强的暗示性,往往用来点染离愁与相思。如李白的“瞑色入高楼,有人楼上愁”,就是在这样一种意境中展开。主人公在黄昏时分登上高楼,想凭栏远眺,最终却凄然作罢。“欲望休”一本作“望欲休”。“休”,即停止、罢休之意。为什么欲望还休呢?答案隐藏在下一句里。 “玉梯”,楼梯、阶梯的美称。“横绝”,即横度。南朝诗人江淹《倡妇自悲赋》写汉宫佳人失宠独居,有“青苔积兮银阁涩,网罗生兮玉梯虚”之句。“玉梯虚”是说玉梯虚设,无人来登。此诗的“玉梯横绝”,是说玉梯横断,无由得上,喻指情人被阻,不能来此相会。原来,主人公渴望见到心上人,情不自禁地要上楼眺望;突然想到他不能前来,于是停下了脚步。唉,不望也罢,免得再添一段新愁。就在这迟疑进退间,天上一弯新月洒下淡淡的清辉,将她的无限思念与失望投射在孤寂的身影中。“月如钩”,一作“月中钩”,不仅烘托了环境的寂寞与凄清,还有象征意义:月儿的缺而不圆,就像是一对情人的不得会合。 芭蕉不展丁香结,同向春风各自愁 "春风"反衬了"愁"。愁人眼里无春色,抬头望月,新月如钩。低头近观,只见芭蕉树的蕉心还未舒展,丁香树上尽是缄结不开的花蕾;它们共同对着黄昏时清冷的春风,各自含愁不解。这既是主人公眼前实景的描绘,同时又是借物写人,以芭蕉喻情人,以丁香喻女子自己,隐喻二人异地同心,都在为不得与对方相会而愁苦。 芭蕉未展、丁香未开本是客观的自然景物,无所谓愁,但在主人公眼里却是满目哀愁。这是因为心中有愁,所以蕉叶难以舒展;满腹是恨,故而花瓣怨结难开。人之愁极,故而触目伤情,而触目之悲更添离人之恨。这两句诗移情入景,借景写情,设喻精巧,融比兴象征为一体。 诗人用不展的芭蕉和固结的丁香来比喻愁绪,不仅使得抽象的情感变得可见可感、具体形象,更使得这种比况具有某种象征的意味。不展的芭蕉与固结的丁香,不仅是主人公愁绪的触发物;作为诗歌的意象,又成为其愁思的载体和象征。 这两句意境优美,音情摇曳,把“一种相思,两处闲愁”的两地徘徊表现得兴味悠长,多少情思尽在其中。清人陆鸣皋说:“妙在‘同’,又妙在‘各自’,他人累言不能尽者,此以一语蔽之。”赞叹的就是这两句诗的含韵不尽。

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