CN103795063A - Circuit overload emergency control system and method based on source load collaborative coefficients - Google Patents

Abstract

The invention discloses a circuit overload emergency control system and method based on source load collaborative coefficients, and belongs to the technical field of electrical power system overload emergency control and load shedding. The system comprises a data collecting module, a source load collaborative coefficient seeking module, a generator tripping load shedding control module, a load power supply restoration module and an overload emergency control module, and the data collecting module, the source load collaborative coefficient seeking module, the generator tripping load shedding control module, the load power supply restoration module and the overload emergency control module are connected in sequence. The method comprises the steps of collecting network structure parameters, voltages of all nodes, power currents of all the nodes, load currents and branch currents, calculating source load branch collaborative coefficients and source load distribution collaborative coefficients, determining a set of control nodes of generator tripping and load shedding, determining the adjustment control quantities of generator tripping and load shedding, selecting generators which do not take part in generator tripping control, determining the adjustment control quantities and load restoration quantities of the generators, and overlaying operation results of the generator tripping load shedding control module and the load power supply restoration module to obtain the final adjustment control quantity. According to the circuit overload emergency control system and method, the safety and the reliability of emergency control are fully guaranteed, and the economical efficiency of control is obviously improved.

Description

Based on circuit overload emergency control system and the method thereof of source lotus coefficient of concordance

Technical field

The invention belongs to power system overload emergency control off-load technical field, relate in particular to a kind of circuit overload emergency control system and method thereof based on source lotus coefficient of concordance.

Background technology

Along with continuous expansion and the structure of electrical network scale are day by day complicated, safe and stable operation and the power supply reliability of system in the accident of the having a power failure on a large scale serious threat being caused by overload.In the time there is overload in circuit; in identification circuit overload and guarantee to protect not malfunction in the situation that; in order to avoid the generation of the accident of having a power failure on a large scale from root; need to select the suitable machine of cutting, cutting load control node and corresponding controlled quentity controlled variable; overload circuit is carried out to emergency control off-load, guarantee system safety stable operation.

At present, be mainly divided into two classes for the common method of emergency control off-load, a class is the emergency control based on sensitivity, and another kind of is the emergency control that based target is optimized.Emergency control based on sensitivity using different generators and load to the sensitivity of overload circuit as the index of its off-load regulating power, and carry out single or equal proportion according to this sensitivity and regulate.This class methods computational process is simple, and decision-making is rapid, but the regulating power of having no idea to make full use of whole system is realized Control of decreasing load on a large scale.The emergency control of based target optimization can take into full account whole operation of power networks situation, take whole grid loss minimum as target, be optimized search, but the target function that quantizes grid loss is described mainly with controlled quentity controlled variable Δ P minimum, has ignored the otherness of each generator node power generation characteristics and load bus loss function.

For above problem, the emergency control that the present invention takes based target to optimize quantizes grid loss from the angle of taking into account economic loss comprehensively, proposes a kind of circuit overload emergency control system and method thereof based on source lotus coefficient of concordance.This invention first upgrades source lotus branch road coefficient of concordance according to system real time operation mode and source lotus is distributed coefficient of concordance.On this basis, determine and cut machine, cutting load control node set according to source lotus branch road coefficient of concordance, take systematic economy loss reduction as target, utilize the optimization of Double fitness value particle cluster algorithm to search control strategy.Meanwhile, be to guarantee power supply reliability, distribute coefficient of concordance not causing new line again under overload condition according to source lotus, selecting a part to have neither part nor lot in the generator increase of cutting machine control exerts oneself, utilize the optimization of Double fitness value particle cluster algorithm to search control strategy, drive part institute cutting load, restore electricity.IEEE10 machine 39 node system simulating, verifyings this strategy can under the prerequisite of system safety stable operation, effectively reduce the load of overload circuit, and there is very high economy guaranteeing.

Summary of the invention

The object of the invention is to, a kind of circuit overload emergency control system and method thereof based on source lotus coefficient of concordance is provided, for realizing the overladen emergency control of circuit on power system.

To achieve these goals, the technical scheme that the present invention proposes is, based on a circuit overload emergency control system for source lotus coefficient of concordance, it is characterized in that described control system comprises that sequentially connected data acquisition module, source lotus coefficient of concordance asked for module, unit shut algorithm control module, load service restoration module and overload emergency control module;

Described data acquisition module is for collection network structural parameters, each node voltage, each node power electric current, each node load electric current and line current;

Described source lotus coefficient of concordance is asked for module and is distributed coefficient of concordance for asking for source lotus branch road coefficient of concordance and source lotus;

Described unit shut algorithm control module is for determining and cut machine and cutting load control node set according to source lotus branch road coefficient of concordance, and definite machine and cutting load adjustment controlled quentity controlled variable of cutting;

Described load service restoration module is for distributing coefficient of concordance to select to have neither part nor lot in the generator of cutting machine control according to source lotus, and definite adjustment controlled quentity controlled variable and load restoration amount that has neither part nor lot in the generator of cutting machine control;

Described overload emergency control module, for the operation result of unit shut algorithm control module and load service restoration module is superposeed, is obtained final adjustment controlled quentity controlled variable.

Based on a circuit overload emergency control method for source lotus coefficient of concordance, it is characterized in that described method comprises:

Step 1: collection network structural parameters, each node voltage, each node power electric current, each node load electric current and branch current;

Step 2: calculate source lotus branch road coefficient of concordance and source lotus and distribute coefficient of concordance;

Step 3: determine and cut machine and cutting load control node set according to source lotus branch road coefficient of concordance, and determine the machine of cutting and cutting load adjustment controlled quentity controlled variable;

Step 4: distribute coefficient of concordance to select to have neither part nor lot in the generator of cutting machine control according to source lotus, and determine the adjustment controlled quentity controlled variable and the load restoration amount that have neither part nor lot in the generator of cutting machine control;

Step 5: the operation result of unit shut algorithm control module and load service restoration module is superposeed, obtain final adjustment controlled quentity controlled variable.

The computational process of described source lotus branch road coefficient of concordance is:

Sub-step A1: adopt formula calculate branch current and node Injection Current coefficient of relationship matrix

Sub-step A2: by branch current and node Injection Current coefficient of relationship matrix

each element is at the d of vectorial plane axle component composition matrix

Described matrix for source lotus branch road coefficient of concordance matrix, the element in this matrix is source lotus branch road coefficient of concordance.

Described source lotus distributes the computational process of coefficient of concordance to be:

Sub-step B1: adopt formula calculating generator node Injection Current and load bus Injection Current relational matrix

Sub-step B2: by generator node Injection Current and load bus Injection Current relational matrix each element is at the d of vectorial plane axle component composition matrix

Described matrix

for source lotus is distributed coefficient of concordance matrix, the element in this matrix is that source lotus is distributed coefficient of concordance.

Described step 3 comprises:

Sub-step C1: obtain generator control node set G and load control node set L;

At source lotus branch road coefficient of concordance matrix

in, selected value be greater than 0 and corresponding node be the element of generator node, added generator control node set G;

At source lotus branch road coefficient of concordance matrix in, selected value is less than 0 and the corresponding node element that is load bus, being added load to control node set L;

Sub-step C2: take economic loss minimum as target, set up first object majorized function and determine the first constraints;

Described first object majorized function is minF=F _a+ F _b-F _c-F _d;

Described the first constraints is:

$s.t.\left\{\begin{array}{c}\underset{i\&Element;G}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Gi}}\right|=\underset{j\&Element;L}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Lj}}\right|\\ {\tilde{C}}_{\mathrm{di}}\mathrm{\&Delta;}{\tilde{P}}_N=(1-a)P_{\mathrm{Bi}\max }-P_{\mathrm{Bi}}\\ {\tilde{P}}_B+{\tilde{C}}_d\mathrm{\&Delta;}{\tilde{P}}_N\&le;(1-a){\tilde{P}}_{B\max }\\ P_{\mathrm{Gi}\min }\&le;P_{\mathrm{Gi}}\&le;P_{\mathrm{Gi}\max }\\ V_{\mathrm{Ni}\min }\&le;V_{\mathrm{Ni}}\&le;V_{\mathrm{Ni}\max }\\ V_c<V_{\mathrm{cr}}\\ {\mathrm{\&delta;}}_{\max }<{\mathrm{\&delta;}}_r\end{array};\right.$

Sub-step C3: solve described first object majorized function, obtain the adjustment controlled quentity controlled variable of each generator node in generator control node set G and load and control the adjustment controlled quentity controlled variable of each load bus in node set L, being the machine of cutting and cutting load and adjusting controlled quentity controlled variable.

Described step 4 comprises:

Sub-step D1: obtain and turn for generator node set G ' and wait to turn for load bus set L ';

The element of choosing in load control node set L distributes coefficient of concordance matrix D % source lotus _dthe value of middle correspondence is positive generator node, is added and turns for generator node set G ';

Load is controlled to node set L as waiting to turn for load bus set L ';

Sub-step D2: the benefit of recovering economy to power is target to the maximum, sets up the second objective optimization function and determines the second constraints;

Described the second objective optimization target function is maxF=F _a+ F _b-F _c-F _d;

Described the second constraints is:

$\left\{\begin{array}{c}\underset{{i\&Element;G}^{\&prime;}}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Pi}}\right|=\underset{{j\&Element;L}^{\&prime;}}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Lj}}\right|\\ \mathrm{\&Delta;}{P}_{\mathrm{Li}}^{\&prime;}\&le;\mathrm{\&Delta;}{P}_{\mathrm{Li}}\\ {\tilde{P}}_B+{\tilde{C}}_d\mathrm{\&Delta;}{\tilde{P}}_N\&le;(1-a){\tilde{P}}_{B\max }\\ P_{\mathrm{Gi}\min }\&le;P_{\mathrm{Gi}}\&le;P_{\mathrm{Gi}\max }\\ V_{\mathrm{Ni}\min }\&le;V_{\mathrm{Ni}}\&le;V_{\mathrm{Ni}\max }\\ V_c<V_{\mathrm{cr}}\\ {\mathrm{\&delta;}}_{\max }<{\mathrm{\&delta;}}_r\end{array};\right.$

Sub-step D3: solve described the second objective optimization function, obtain Δ P _pibe the adjustment controlled quentity controlled variable and the load restoration amount that have neither part nor lot in the generator of cutting machine control.

The present invention evaluates the grid loss of taking emergency control to bring from economic loss angle, in guaranteeing overload circuit off-load, load is carried out to service restoration control, both fully ensure the safety and reliability of emergency control, significantly improved again the economy of controlling.

Accompanying drawing explanation

Fig. 1 is the circuit overload emergency control system structure chart based on source lotus coefficient of concordance;

Fig. 2 is the linear equivalent network figure of node Injection Current;

Fig. 3 be node 1 and connect branch current flow graph;

Fig. 4 is all types of user loss of outage function table;

Fig. 5 is IEEE10 machine 39 node system structure charts;

Fig. 6 is circuit 27 source lotus branch road coefficient of concordance tables;

Fig. 7 is through-put power change curve when overload occurs circuit 27 in IEEE10 machine 39 node systems;

Fig. 8 is system generator rate for incorporation into the power network and meritorious limit value table;

Fig. 9 is system generator coal consumption characterisitic parameter table;

Figure 10 is system generator pollutant emission characterisitic parameter table;

Figure 11 is system loading loss of outage function table;

Figure 12 cuts machine, cutting load control search result table;

Figure 13 is IEEE10 machine 39 node systems circuit 27 through-put power situation of change curve charts after cutting machine, cutting load control;

Figure 14 is that IEEE10 machine 39 node systems are cut transient stability check plot after machine, cutting load control;

Figure 15 is that the source lotus of load bus 15,20,26 is distributed coefficient of concordance table;

Figure 16 is load service restoration search result table;

Figure 17 is transient stability check plot after IEEE10 machine 39 node system load service restorations;

Figure 18 is that the overload emergency control based on source lotus coefficient of concordance is finally adjusted control scale;

Figure 19 is circuit 27 through-put power situation of change curve charts after IEEE10 machine 39 node system load service restorations.

Embodiment

Below in conjunction with accompanying drawing, preferred embodiment is elaborated.Should be emphasized that, following explanation is only exemplary, rather than in order to limit the scope of the invention and to apply.

Embodiment 1

Fig. 1 is the circuit overload emergency control system structure chart based on source lotus coefficient of concordance.As shown in Figure 1, the circuit overload emergency control system based on source lotus coefficient of concordance comprises that sequentially connected data acquisition module, source lotus coefficient of concordance asked for module, unit shut algorithm control module, load service restoration module and overload emergency control module.

Data acquisition module is for collection network structural parameters, each node voltage, each node power electric current, each node load electric current and branch current.

Source lotus coefficient of concordance is asked for module and is distributed coefficient of concordance for asking for source lotus branch road coefficient of concordance and source lotus.

Unit shut algorithm control module is for determining and cut machine and cutting load control node set according to source lotus branch road coefficient of concordance, and definite machine and cutting load adjustment controlled quentity controlled variable of cutting.

Load service restoration module is for distributing coefficient of concordance to select to have neither part nor lot in the generator of cutting machine control according to source lotus, and definite adjustment controlled quentity controlled variable and load restoration amount that has neither part nor lot in the generator of cutting machine control.

Overload emergency control module, for the operation result of unit shut algorithm control module and load service restoration module is superposeed, is obtained final adjustment controlled quentity controlled variable.

The basic principle of the circuit overload emergency control system based on source lotus coefficient of concordance provided by the invention is:

1. data acquisition module.

Data acquisition module is used for gathering native system desired data, comprising: network architecture parameters, each node voltage, each node power electric current, each node load electric current and branch current.

2. source lotus coefficient of concordance is asked for module.

After the network configuration of system is determined, in each circuit through-put power and system, between generator power supply power, load power, there is certain relation; Equally, the supply of each generator power supply power and each load power also exists certain relation.This relation can be represented by formula (1), (2).

${\tilde{P}}_B=\tilde{C}\left(\mathrm{\&lambda;}\right){\tilde{P}}_N---\left(1\right)$

${\tilde{P}}_N\tilde{D}\left(\mathrm{\&lambda;}\right){\tilde{P}}_N---\left(2\right)$

By finding out such relation, can instruct power supply and load that Some Related Algorithms fast searching is large with the overload circuit degree of association, realize effective, rapid, economic emergency control off-load strategy.

Generator power supply in system and load can represent by the form of node Injection Current, regard system as a linear network (as shown in Figure 2), for this linear network, can list network node voltage equation:

${\tilde{I}}_N={\tilde{Y}}_N{\tilde{V}}_N---\left(3\right)$

In formula (3)

for node Injection Current phasor, to flow to the direction of network as the positive direction of electric current phasor, therefore generator node Injection Current for just, load bus Injection Current is for negative;

for node voltage vector;

for node admittance matrix, can be by branch admittance matrix

with network node incidence matrices

obtain: easily know again branch current phasor

with node voltage phasor

there is relation:

can obtain the pass of branch current and node Injection Current in network is:

${\tilde{I}}_B=\tilde{Y}{\tilde{A}}^T{\tilde{Y}}_N^{-1}{\tilde{I}}_N---\left(4\right)$

Will

front coefficient matrix

be designated as

be the matrix on b*n rank, b is a way, and n is nodes, formula (4) can be turned to:

${\tilde{I}}_B=\tilde{C}\left(\mathrm{\&lambda;}\right){\tilde{I}}_N---\left(5\right)$

Linear relationship between k line display branch road k and each node Injection Current in formula (5), can be represented by formula (6):

${\stackrel{\&CenterDot;}{I}}_{k,B}={\mathrm{\&lambda;}}_{k1}{\stackrel{\&CenterDot;}{I}}_{1,N}+{\mathrm{\&lambda;}}_{k2}{\stackrel{\&CenterDot;}{I}}_{2,N}+...+{\mathrm{\&lambda;}}_{\mathrm{kn}}{\stackrel{\&CenterDot;}{I}}_{n,N}---\left(6\right)$

For each node, should meet Kirchhoff's current law (KCL), Figure 3 shows that the current direction situation of node 1 and institute's connection branch road thereof.As shown in Figure 3, node 1 is load bus, and its node Injection Current is negative direction, has three branch roads to be connected with node 1, and the sense of current on circuit as shown in FIG..In Fig. 3, there is following relation:

$\left\{\begin{array}{c}\frac{{\stackrel{\&CenterDot;}{I}}_{2,B}}{{\stackrel{\&CenterDot;}{I}}_{2,B}+{\stackrel{\&CenterDot;}{I}}_{3,B}}{\stackrel{\&CenterDot;}{I}}_{\mathrm{<figure-callout\; id="1"\; label="N"\; filenames="HDA0000471688930000031.png,HDA0000471688930000052.png"\; state="\{\{state\}\}">N</figure-callout>}1}=\frac{{\stackrel{\&CenterDot;}{I}}_{N1}}{{\stackrel{\&CenterDot;}{I}}_N+{\stackrel{\&CenterDot;}{I}}_{1,B}}{\stackrel{\&CenterDot;}{I}}_{2,B}\\ \frac{{\stackrel{\&CenterDot;}{I}}_{3,B}}{{\stackrel{\&CenterDot;}{I}}_{2,B}+{\stackrel{\&CenterDot;}{I}}_{3,B}}{\stackrel{\&CenterDot;}{I}}_{\mathrm{<figure-callout\; id="1"\; label="N"\; filenames="HDA0000471688930000031.png,HDA0000471688930000052.png"\; state="\{\{state\}\}">N</figure-callout>}1}=\frac{{\stackrel{\&CenterDot;}{I}}_{N1}}{{\stackrel{\&CenterDot;}{I}}_N+{\stackrel{\&CenterDot;}{I}}_{1,B}}{\stackrel{\&CenterDot;}{I}}_{3,B}\end{array}---\left(7\right)\right.$

Two formulas in formula (7) are added, have:

${\stackrel{\&CenterDot;}{I}}_{\mathrm{<figure-callout\; id="1"\; label="N"\; filenames="HDA0000471688930000031.png,HDA0000471688930000052.png"\; state="\{\{state\}\}">N</figure-callout>}1}=\frac{{\stackrel{\&CenterDot;}{I}}_{N1}}{{\stackrel{\&CenterDot;}{I}}_{\mathrm{<figure-callout\; id="1"\; label="N"\; filenames="HDA0000471688930000031.png,HDA0000471688930000052.png"\; state="\{\{state\}\}">N</figure-callout>}1}+{\stackrel{\&CenterDot;}{I}}_{1\mathrm{nB}}}({\stackrel{\&CenterDot;}{I}}_{2,B}+{\stackrel{\&CenterDot;}{I}}_{3,B})---\left(8\right)$

By formula (5) substitution formula (8), order

by load bus Injection Current with connection branch road the transformation of branch current be the relation of load bus and each node Injection Current:

${\stackrel{\&CenterDot;}{I}}_{\mathrm{<figure-callout\; id="1"\; label="N"\; filenames="HDA0000471688930000031.png,HDA0000471688930000052.png"\; state="\{\{state\}\}">N</figure-callout>}1}=k(\tilde{C}\left({\mathrm{\&lambda;}}_{2i}\right){\stackrel{\&CenterDot;}{I}}_{2,B}+\tilde{C}\left({\mathrm{\&lambda;}}_{3i}\right){\stackrel{\&CenterDot;}{I}}_{3,B})---\left(9\right)$

The relation that formula (9) is explained uses the mode of matrix to represent, first defines two line direction correlation matrixes.Forward matrix be a n*b rank matrix, element P _ijrepresent circuit _jbranch current whether consistent with the Injection Current direction of node i (flow to node or flow out node), if be unanimously labeled as 1, all the other are 0; Inverted matrix be similarly a n*b rank matrix, in the time of the branch current of circuit j and the Injection Current opposite direction of node i, by element Ni _jbe labeled as 1, all the other are 0.Can draw formula (10):

${\stackrel{\&CenterDot;}{I}}_N=\tilde{K}.*\tilde{N}\tilde{C}\left(\mathrm{\&lambda;}\right){\stackrel{\&CenterDot;}{I}}_N---\left(10\right)$

In formula, " .* " representing matrix

in each element and matrix

in the corresponding element of each row multiply each other.

matrix is a n*1 rank matrix, and wherein element can be tried to achieve by following formula:

$k_i=\frac{{\stackrel{\&CenterDot;}{I}}_{\mathrm{Ni}}}{{\stackrel{\&CenterDot;}{I}}_{\mathrm{Ni}}+P_i*{\stackrel{\&CenterDot;}{I}}_B}=\frac{{\stackrel{\&CenterDot;}{I}}_{\mathrm{Ni}}}{{\stackrel{\&CenterDot;}{I}}_{\mathrm{Ni}}+P_i*{\stackrel{\&CenterDot;}{\mathrm{CI}}}_N}---\left(11\right)$

And then try to achieve

the computing formula of matrix is:

$\tilde{K}={\stackrel{\&CenterDot;}{I}}_{N.}/({\stackrel{\&CenterDot;}{I}}_N+\tilde{P}*\tilde{C}{\stackrel{\&CenterDot;}{I}}_N)=1./(1+\tilde{P}\tilde{C})---\left(12\right)$

By formula (9) equation right side node Injection Current phasor

front coefficient matrix

be designated as

be the matrix on n*n rank, formula (10) can be turned to:

${\tilde{I}}_N=\tilde{D}\left(\mathrm{\&lambda;}\right){\tilde{I}}_N---\left(13\right)$

In order to obtain formula (1), (2) represented form, formula (5), (13) represented current relationship need to be converted into active power relation.There is following relation in (d is that real axis q is the imaginary axis) known power and electric current in phasor plane:

$\left\{\begin{array}{c}P=U_d{I}_d+U_q{I}_q\\ Q=U_q{I}_d-U_d{I}_q\end{array}\right.---\left(14\right)$

Branch road injecting power P _bcan be expressed as:

P _B=U _dI _Bd+U _qIB _q(15)

Take formula (5) as example, be transformed in phasor plane, known:

$\left\{\begin{array}{c}{I}_{\mathrm{Bd}}=C_d{I}_{\mathrm{Nd}}-C_q{I}_{\mathrm{Nq}}\\ I_{\mathrm{Bq}}=C_q{I}_{\mathrm{Nd}}+C_d{I}_{\mathrm{Nq}}\end{array}---\left(16\right)\right.$

By in formula (16) substitution formula (15), can obtain:

P _B=C _d(U _dI _Nd+U _qI _Nq)+C _q(U _qI _Nd-U _dI _Nq)=C _dP _N+C _qQ _N(17)

Because the reactance of each branch road in actual electric network is much larger than resistance, therefore coefficient matrix

in the real part of each element

all much larger than imaginary part

therefore formula (17) can be further converted to:

${\tilde{P}}_B={\tilde{C}}_d{\tilde{P}}_N---\left(18\right)$

In like manner, formula (13) also can be converted into power form:

${\tilde{P}}_N={\tilde{D}}_d{\tilde{P}}_N---\left(19\right)$

be called source lotus branch road coefficient of concordance, represent contacting between generator power supply power, load power in each circuit through-put power and system;

be called source lotus and distribute coefficient of concordance, represent the relation of the supply of each generator power supply power and each load power.

3. unit shut algorithm control module.

Sub-step 101: obtain generator control node set G, choose reduce injecting power can reduce overload line power generator node add set G in, choose

be greater than 0 generator node; Obtaining load and controlling node set L, choosing and reduce the load bus that injecting power can reduce overload line power and add in set L, because the node injecting power of load be opposite direction, so choose

be less than 0 load bus.

Sub-step 102:

The method that economic loss is taken into account in employing is selected to control node and is compared conventional method science, more rigorous more with definite controlled quentity controlled variable.

For the load of different user types, its loss of outage function is also different, the loss of outage function statistical form of Tu4Shi China medium-sized city actual count.

For different fossil-fired units, the expenses of surfing Internet in its unit interval, coal consumption amount, pollutant emission flow function can be expressed as:

F _PGi=f _PGiP _Gi(21)

$C_{\mathrm{RGi}}=a_{\mathrm{<figure-callout\; id="2"\; label="CRi\; P\; Gi"\; filenames="HDA0000471688930000031.png,HDA0000471688930000043.png"\; state="\{\{state\}\}">CRi</figure-callout>}}{P}_{\mathrm{Gi}}^{}{}_2^{}+b_{\mathrm{CRi}}{P}_{\mathrm{Gi}}+c_{\mathrm{CRi}}---\left(22\right)$

$P_{\mathrm{EGi}}=a_{\mathrm{<figure-callout\; id="2"\; label="PEi\; P\; Gi"\; filenames="HDA0000471688930000031.png,HDA0000471688930000043.png"\; state="\{\{state\}\}">PEi</figure-callout>}}{P}_{\mathrm{Gi}}^{}{}_2^{}+b_{\mathrm{PEi}}{P}_{\mathrm{Gi}}+c_{\mathrm{PEi}}---\left(23\right)$

In formula: f _pGifor the rate for incorporation into the power network coefficient of generating set, unit is unit/MW.h; a _cRi, b _cRi, c _cRifor the coefficient of coal consumption characteristic quadratic function, unit is t/MW ²h, t/MWh, t/h; a _pEi, b _pEi, c _pEifor the coefficient of pollutant emission characteristic quadratic function, unit is t/MW ²h, t/MWh, t/h; P _gifor generating set active power output valve, unit is MW.

Consider the loss of outage characteristic of power generation characteristics and each type load of each generator, the present invention, take total system economic loss minimum as target, selects to control the controlled quentity controlled variable of node and definite each control node.Total system economic loss is expressed as to first object majorized function to be had:

F=F _A+F _B-F _C-F _D(24)

$\left\{\begin{array}{c}{F}_A=\underset{i\&Element;G}{\mathrm{\&Sigma;}}\mathrm{\&Delta;}{P}_{\mathrm{Gi}}*(f_{\mathrm{AP}}-f_{\mathrm{Pi}})\\ F_B=\underset{i\&Element;L}{\mathrm{\&Sigma;}}\mathrm{\&Delta;}{P}_{\mathrm{Li}}*f_{\mathrm{Li}}\\ F_C=k_C*\underset{i\&Element;G}{\mathrm{\&Sigma;}}\left(a_{\mathrm{CRi}}{(P_{\mathrm{Gi}}^2-(P_{\mathrm{Gi}}-\mathrm{\&Delta;}{P}_{\mathrm{Gi}})}^2\right)\\ +b_{\mathrm{CRi}}(P_{\mathrm{Gi}}-(P_{\mathrm{Gi}}-\mathrm{\&Delta;}{P}_{\mathrm{Gi}})))\\ F_D=k_D*\underset{i\&Element;G}{\mathrm{\&Sigma;}}\left(a_{\mathrm{PEi}}{(P_{\mathrm{Gi}}-\mathrm{\&Delta;}{P}_{\mathrm{Gi}})}^2\right)\\ +b_{\mathrm{PEi}}(P_{\mathrm{Gi}}-(P_{\mathrm{Gi}}-\mathrm{\&Delta;}{P}_{\mathrm{Gi}})))\end{array}---\left(25\right)\right.$

In formula (24), F is total cost, and unit is unit, and it is made up of four parts: F _awhat represent is to reduce the sale of electricity loss that generator output causes, and is power variation and generating profit (the sale of electricity price f of each adjustment generator _aPdeduct online price f _pi) the sum of products; F _bwhat represent is total loss of outage of each load; F _cwhat represent is because each generator reduces the coal consumption expense of exerting oneself saved, and its value is exerted oneself and saved the product of coal-fired total amount afterwards for coal price and adjustment; F _dwhat represent is because each generator reduces the saved pollution abatement costs of exerting oneself, and its value is after pollution control expense exerts oneself with adjustment, to reduce the product of disposal of pollutants total amount.

Except considering that target function is got minimum, the system that also should guarantee in circuit overload emergency control policy can not lose because of taked control a series of restrictive conditions such as stable.

First according to network power balance principle, should take the control program of equivalent unit shut algorithm, exist:

$\underset{i\&Element;G}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Pi}}\right|=\underset{j\&Element;L}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Lj}}\right|---\left(26\right)$

Secondly, taking after the machine of cutting, cutting load control, out-of-limit should the elimination of overload on overload circuit,

The off-load amount of overload circuit is determined by formula (27):

ΔP _Bi=(1-α)P _Bimax-P _Bi(27)

P in formula _bifor the circuit through-put power before controlling, α is the thermally-stabilised nargin of circuit, P _bimaxfor line threshold through-put power.The line power in formula (27) left side is substituted with node injecting power:

${\tilde{C}}_{\mathrm{di}}\mathrm{\&Delta;}{\tilde{P}}_N=(1-a)P_{\mathrm{Bi}\max }-P_{\mathrm{Bi}}---\left(28\right)$

, take after emergency control measure, can not there is new overload circuit in system meanwhile:

${\tilde{P}}_B+{\tilde{C}}_d\mathrm{\&Delta;}{\tilde{P}}_N\&le;(1-a){\tilde{P}}_{B\max ---\left(29\right)}$

In addition, also should consider generator power inequality constraints, node voltage inequality constraints:

P _Gimin≤P _Gi≤P _Gimax(30)

V _Nimin≤V _Ni≤V _Nimax(31)

Take after emergency control policy, system should meet transient stability, i.e. not out-of-limit, the angle stability of energy function:

V _c<V _cr(32)

δ _max<δ _r(33)

V in formula _crfor transient energy function stability limit, δ _maxfor system maximum work angular difference, δ _rfor the angle stability limit.

Comprehensive above-mentioned consideration, the model that can build sets up cutting machine, cutting load emergency control is as follows:

minF=F _A+F _B-F _C-F _D

$s.t.\left\{\begin{array}{c}\underset{i\&Element;G}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Pi}}\right|=\underset{j\&Element;L}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Lj}}\right|\\ {\tilde{C}}_{\mathrm{di}}\mathrm{\&Delta;}{\tilde{P}}_N=(1-a)P_{\mathrm{Bi}\max }-P_{\mathrm{Bi}}\\ {\tilde{P}}_B+{\tilde{C}}_d\mathrm{\&Delta;}{\tilde{P}}_N\&le;(1-a){\tilde{P}}_{B\max }\\ P_{\mathrm{Gi}\min }\&le;P_{\mathrm{Gi}}\&le;P_{\mathrm{Gi}\max }\\ V_{\mathrm{Ni}\min }\&le;V_{\mathrm{Ni}}\&le;V_{\mathrm{Ni}\max }\\ V_c<V_{\mathrm{cr}}\\ {\mathrm{\&delta;}}_{\max }<{\mathrm{\&delta;}}_r\end{array}---\left(34\right)\right.$

Each controlled quentity controlled variable of controlling node by optimized algorithm according to target function minimum and each equation inequality constraints combine solve definite.

Sub-step 103: consider separation comparative approach to be incorporated in PSO algorithm, separate targets function and constraints are two fitness indexs, thereby optimization problem is converted into:

$\left\{\begin{array}{c}\min f(x_1,x_2,...,x_n)\\ v(x_1,x_2,...x_n)=\underset{j=1}{\overset{q}{\mathrm{\&Sigma;}}}\max (0,g_j(x_1,x_2,...,x_n))\\ +\underset{p=1}{\overset{m}{\mathrm{\&Sigma;}}}\left|h_P(x_1,x_2,...,x_n)\right|\end{array}---\left(35\right)\right.$

F(x ₁, x ₂..., x _n) corresponding to the target function value of required extreme-value problem; V(x ₁, x ₂..., x _n) corresponding to required extreme-value problem constraints, jointly formed by all constraints, its value size has reflected the degree of closeness of each particle and restrained boundary.Using these two functions, together as the fitness function of particle, the quality of each particle is determined by certain comparison rule jointly by these two functional values.

4. load service restoration module.

Sub-step 101: obtain and wait to turn for load bus set L ', formed by all load buses of taking cutting load control.Obtain and turn for generator node set G ', choose the source lotus of the middle element of relative convergence L ' and distribute coefficient of concordance for positive generator node, do not comprise the generator of having taked to cut machine measure.

Sub-step 102: cutting under the control measure of machine, cutting load, the out-of-limit problem of circuit overload is resolved, has still caused the loss of a large amount of loads.In order to ensure the reliability of power supply, after cutting machine, cutting load control, can turn the load that a band part needs excision by increasing the non-generator output of cutting machine control, reduce the loss amount of load.

Cut the control thinking of machine, cutting load according to a upper trifle, from the angle of economic loss, the object of load service restoration is to make the maximization of economic benefit that restores electricity.So its target function is the same with the target function form of cutting machine, cutting load control, but pursuit is that target function is got maximum.In addition formula (27) etc. constraints also inapplicable here, added the inequality constraints condition of a load restoration upper limit, the cutting load amount before the load recovering is not more than:

$\mathrm{\&Delta;}{P}_{\mathrm{Li}}^{\&prime;}\&le;\mathrm{\&Delta;}{P}_{\mathrm{Li}}---\left(36\right)$

Therefore the Mathematical Modeling of load service restoration is as follows:

maxF=F _A+F _B-F _C-F _D

$\left\{\begin{array}{c}\underset{{i\&Element;G}^{\&prime;}}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Pi}}\right|=\underset{{j\&Element;L}^{\&prime;}}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Lj}}\right|\\ \mathrm{\&Delta;}{P}_{\mathrm{Li}}^{\&prime;}\&le;\mathrm{\&Delta;}{P}_{\mathrm{Li}}\\ {\tilde{P}}_B+{\tilde{C}}_d\mathrm{\&Delta;}{\tilde{P}}_N\&le;(1-a){\tilde{P}}_{B\max }\\ P_{\mathrm{Gi}\min }\&le;P_{\mathrm{Gi}}\&le;P_{\mathrm{Gi}\max }\\ V_{\mathrm{Ni}\min }\&le;V_{\mathrm{Ni}}\&le;V_{\mathrm{Ni}\max }\\ V_c<V_{\mathrm{cr}}\\ {\mathrm{\&delta;}}_{\max }<{\mathrm{\&delta;}}_r\end{array}---\left(37\right)\right.$

Equally, respectively turn for generator node choose with each node turn for controlled quentity controlled variable by optimized algorithm according to target function maximum and each equation inequality constraints combine solve definite.

Sub-step 103: consider separation comparative approach to be incorporated in PSO algorithm, separate targets function and constraints are two fitness indexs, thereby optimization problem is converted into:

$\left\{\begin{array}{c}\min f(x_1,x_2,...,x_n)\\ v(x_1,x_2,...x_n)=\underset{j=1}{\overset{q}{\mathrm{\&Sigma;}}}\max (0,g_j(x_1,x_2,...,x_n))\\ +\underset{p=1}{\overset{m}{\mathrm{\&Sigma;}}}\left|h_P(x_1,x_2,...,x_n)\right|\end{array}---\left(38\right)\right.$

F(x ₁, x ₂..., x _n) corresponding to the target function value of required extreme-value problem; V(x ₁, x ₂..., x _n) corresponding to required extreme-value problem constraints, jointly formed by all constraints, its value size has reflected the degree of closeness of each particle and restrained boundary.Using these two functions, together as the fitness function of particle, the quality of each particle is determined by certain comparison rule jointly by these two functional values.

5. overload emergency control overall evaluation module.

Overload emergency control policy forms by cutting machine, cutting load control and load service restoration two parts, this two-part starting point and emphasis are had nothing in common with each other, cut machine, cutting load control is in order as early as possible the out-of-limit circuit of overload to be carried out to off-load, guarantee system safety stable operation, this part is basis and the core of emergency control policy; And load service restoration is mainly the power supply reliability of considering to guarantee power supply user, reduce the economic loss that has a power failure and bring as far as possible, this part is supplementing of emergency control policy and extends.In addition, system requires also different to this two-part time scale, for cutting machine, cutting load control, in order to guarantee the stable operation of system, need to realize as early as possible Control of decreasing load, and time scale is just shorter; And for load service restoration, should after guaranteeing system safety stable operation, consider again to recover load power supply, its time scale is loosely many compared with the former, therefore carry out after the former.

After superposeing, the operation result of two parts as final control strategy, finally adjusts controlled quentity controlled variable Δ P _nf=Δ P _n1+ Δ P _n2.

Based on above-mentioned principle, a kind of circuit overload emergency control method based on source lotus coefficient of concordance provided by the invention comprises:

Step 1: collection network structural parameters, each node voltage, each node power electric current, each node load electric current and branch current.

Step 2: calculate source lotus branch road coefficient of concordance and source lotus and distribute coefficient of concordance.

Wherein, the computational process of source lotus branch road coefficient of concordance is:

Sub-step A1: adopt formula

calculate branch current and node Injection Current coefficient of relationship matrix

Sub-step A2: by branch current and node Injection Current coefficient of relationship matrix

each element is at the d of vectorial plane axle component composition matrix matrix for source lotus branch road coefficient of concordance matrix, the element in this matrix is source lotus branch road coefficient of concordance.

Source lotus distributes the computational process of coefficient of concordance to be:

Sub-step B1: adopt formula

calculating generator node Injection Current and load bus Injection Current relational matrix

wherein,

for branch current and node Injection Current mark matrix in the same way,

for branch current and the reverse mark matrix of node Injection Current.

Sub-step B2: by generator node Injection Current and load bus Injection Current relational matrix

each element is at the d of vectorial plane axle component composition matrix

matrix for source lotus is distributed coefficient of concordance matrix, the element in this matrix is that source lotus is distributed coefficient of concordance.

Step 3: determine and cut machine and cutting load control node set according to source lotus branch road coefficient of concordance, and determine the machine of cutting and cutting load adjustment controlled quentity controlled variable.Comprise:

Sub-step C1: obtain generator control node set G and load control node set L.

At source lotus branch road coefficient of concordance matrix

in, selected value be greater than 0 and corresponding node be the element of generator node, added generator control node set G.

At source lotus branch road coefficient of concordance matrix

in, selected value is less than 0 and the corresponding node element that is load bus, is loaded and controls node set L.

Sub-step C2: take economic loss minimum as target, set up first object majorized function and determine the first constraints.

Wherein, first object majorized function is minF=F _a+ F _b-F _c-F _d.

The first constraints is: $s.t.\left\{\begin{array}{c}\underset{i\&Element;G}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Gi}}\right|=\underset{j\&Element;L}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Lj}}\right|\\ {\tilde{C}}_{\mathrm{di}}\mathrm{\&Delta;}{\tilde{P}}_N=(1-a)P_{\mathrm{Bi}\max }-P_{\mathrm{Bi}}\\ {\tilde{P}}_B+{\tilde{C}}_d\mathrm{\&Delta;}{\tilde{P}}_N\&le;(1-a){\tilde{P}}_{B\max }\\ P_{\mathrm{Gi}\min }\&le;P_{\mathrm{Gi}}\&le;P_{\mathrm{Gi}\max }\\ V_{\mathrm{Ni}\min }\&le;V_{\mathrm{Ni}}\&le;V_{\mathrm{Ni}\max }\\ V_c<V_{\mathrm{cr}}\\ {\mathrm{\&delta;}}_{\max }<{\mathrm{\&delta;}}_r\end{array}.\right.$

Sub-step C3: solve described first object majorized function, obtain the adjustment controlled quentity controlled variable of each generator node in generator control node set G and load and control the adjustment controlled quentity controlled variable of each load bus in node set L, being the machine of cutting and cutting load and adjusting controlled quentity controlled variable.

Step 4: distribute coefficient of concordance to select to have neither part nor lot in the generator of cutting machine control according to source lotus, and determine the adjustment controlled quentity controlled variable and the load restoration amount that have neither part nor lot in the generator of cutting machine control.

Sub-step D1: obtain and turn for generator node set G ' and wait to turn for load bus set L '.

The element of choosing in load control node set L distributes coefficient of concordance matrix source lotus

the value of middle correspondence is positive generator node, is added and turns for generator node set G '.

Load is controlled to node set L as waiting to turn confession load bus set L '.

Sub-step D2: the benefit of recovering economy to power is target to the maximum, sets up the second objective optimization function and determines the second constraints.

The second objective optimization target function is maxF=F _a+ F _b-F _c-F _d.

Described the second constraints is: $\left\{\begin{array}{c}\underset{{i\&Element;G}^{\&prime;}}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Pi}}\right|=\underset{{j\&Element;L}^{\&prime;}}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Lj}}\right|\\ \mathrm{\&Delta;}{P}_{\mathrm{Li}}^{\&prime;}\&le;\mathrm{\&Delta;}{P}_{\mathrm{Li}}\\ {\tilde{P}}_B+{\tilde{C}}_d\mathrm{\&Delta;}{\tilde{P}}_N\&le;(1-a){\tilde{P}}_{B\max }\\ P_{\mathrm{Gi}\min }\&le;P_{\mathrm{Gi}}\&le;P_{\mathrm{Gi}\max }\\ V_{\mathrm{Ni}\min }\&le;V_{\mathrm{Ni}}\&le;V_{\mathrm{Ni}\max }\\ V_c<V_{\mathrm{cr}}\\ {\mathrm{\&delta;}}_{\max }<{\mathrm{\&delta;}}_r\end{array}.\right.$

Sub-step D3: solve described the second objective optimization function, obtain Δ P _pibe the adjustment controlled quentity controlled variable and the load restoration amount that have neither part nor lot in the generator of cutting machine control.

Step 5: the operation result of unit shut algorithm control module and load service restoration module is superposeed, obtain final adjustment controlled quentity controlled variable.

Embodiment 2

Shown in Fig. 5 is IEEE10 machine 39 node diagrams, and circuit 29 and circuit 27 are generator 35 and generator 36 basic routing lines to other node power outputs.When circuit 29 break down cut after, its line power transmitting before fault shifts by trend, cause circuit 27 that overload occurs, and line power surmounts through-put power stability limit, now, need to reach the target of overload circuit off-load by the measure of taking the machine of cutting, cutting load control and load service restoration, and make the economic loss minimum causing by emergency control policy off-load.

After circuit 29 is cut, network topology structure changes, and first needs to revise former incidence matrices

and branch admittance matrix

find matrix and matrix

the corresponding element of middle circuit 29 is deleted.According to system source lotus branch road coefficient of concordance after formula (4), the excision of (10) computational scheme

distribute coefficient of concordance with source lotus the source lotus branch road coefficient of concordance of circuit 27

as shown in Figure 6.

There is three-phase shortcircuit in known system circuit 29 in the time of 0.25s, after 50ms, is excised by this power line main protection, and now, because trend shifts, overload (P appears in another of same transmission cross-section basic routing line 27 _b27=209.97MW) and surmounted the transmission power limit (P of this circuit _b27max=200MW).The variation of circuit 27 through-put powers as shown in Figure 7.

Need to be by cutting machine, off-load is carried out in cutting load control.In system, the relevant parameter of the expenses of surfing Internet of generator, coal consumption amount, pollutant emission flow function is as shown in Fig. 8, Fig. 9, Figure 10.

As shown in figure 11, choose 1h is the unit interval to the loss of outage function of each load bus.The generator node that participates in controlling should be chosen the source lotus branch road coefficient of concordance of circuit 27 in Fig. 6

be greater than 0 node, reduce to exert oneself and can reduce the load of circuit.By finding, choose generator node 35,36 for controlling node, composition set G.For choosing of the load bus that participates in controlling, select according to the source lotus branch road coefficient of concordance of circuit 27 equally, because the injecting power of load bus is in the other direction, so should choose

be less than 0 node.By finding, choose load bus 3,4,7,8,12,15,16,18,20,21,24,25,26,27,28,29 for controlling node, composition set L.

After control node is selected, determine target function f (x according to formula (24), (25) ₁, x ₂..., x _n), the coefficient correlation that generator control node set G and load are controlled node set L is provided by the table in Fig. 6, Fig. 8, Fig. 9, Figure 10 and Figure 11, brings formula into and calculates.

For related constraint condition, determine by formula (34), wherein the thermally-stabilised nargin α of circuit is 5%, line threshold through-put power P _b27maxfor 200MW, required off-load amount is P _b27-(1-α) P _b27maxequal 19.97MW.The institute Prescribed Properties relevant to node injecting power formed to restrained boundary fitness function v(x according to formula (38) ₁, x ₂..., x _n), and search for by Double fitness value particle swarm optimization algorithm.Each control node control amount result after search as shown in figure 12, is designated as P _n1.

From formula (18), the off-load amount of circuit 27 for 20.24MW, when 0.5s, take the machine of cutting, cutting load control off-load, after off-load the through-put power of circuit 27 be 189.73MW(as shown in figure 13), be less than P _b27max, and meet the requirement of whole equatioies and inequality constraints condition.Cutting the minimum total system economic loss that machine, cutting load control cause is F ₁=193060.7 yuan/hour.Take power system transient stability verification situation after emergency control as shown in figure 14, maximum generation machine merit angular difference (node 34 and node 39) is 38.0683 degree, minimum busbar voltage (node 31) is 0.98pu, minimum bus frequency (node 36) is 59.98Hz, system stability.

As shown in Table 7, owing to having taked the machine of cutting, cutting load measure, cause having the load (15,20,26) of 3 nodes to be subject to loss, in order to improve the reliability of customer power supply, save the economic loss that has a power failure and cause as far as possible, can suitably increase exerting oneself of other generators, turn band part excision load, the power supply of recovered part excision load.The upper limit that each load bus recovers load is P _n1in the excision value of each load bus.

Equally first, choose control node, for control overhead node, need 3 nodes restoring electricity, they form load bus set L; For controlling generator node, should choose non-other generator nodes of cutting machine control node, and should choose source lotus and distribute coefficient of concordance

be greater than zero generator node (having relation of the supply).The source lotus of load bus 15,20,26 is distributed coefficient of concordance

as shown in figure 15, by finding (search result of three nodes is got union), choose generator node 30,31,32,33,34,37,38,39 for controlling node, composition set G.

After control node is selected, determine target function f (x according to formula (25), (37) ₁, x ₂..., x _n), parameter with cut machine, cutting load control is consistent, distinguishes maximum rather than minimum value for getting target function.For related constraint condition, determine by formula (36), form restrained boundary fitness function v(x ₁, x ₂..., x _n), and again search for by Double fitness value particle swarm optimization algorithm.Each control node control amount result after search as shown in figure 16, is designated as P _n2.

This result meets whole equatioies and inequality constraints, and F retrieves economic losses ₂=160489.5 yuan/hour.

Take power system transient stability verification situation after emergency control as shown in figure 17, system stability.The overload emergency control policy of entirety is Δ P to the controlled quentity controlled variable of each node _nf=Δ P _n1+ Δ P _n2, result as shown in figure 18.

From formula (18), 0.7s takes the off-load amount of circuit 27 after load restoration control

for 21.45MW, after off-load the through-put power of circuit 27 be 188.52MW(as shown in figure 19), be less than P _b27max, and meet the requirement of whole equatioies and inequality constraints condition.The minimum total system economic loss that whole emergency control causes is F ₁-F ₂=32571.2 yuan/hour.

The above; only for preferably embodiment of the present invention, but protection scope of the present invention is not limited to this, is anyly familiar with in technical scope that those skilled in the art disclose in the present invention; the variation that can expect easily or replacement, within all should being encompassed in protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range of claim.

Claims (6)

1. the circuit overload emergency control system based on source lotus coefficient of concordance, is characterized in that described control system comprises that sequentially connected data acquisition module, source lotus coefficient of concordance asked for module, unit shut algorithm control module, load service restoration module and overload emergency control module;

Described data acquisition module is for collection network structural parameters, each node voltage, each node power electric current, each node load electric current and line current;

Described source lotus coefficient of concordance is asked for module and is distributed coefficient of concordance for asking for source lotus branch road coefficient of concordance and source lotus;

Described unit shut algorithm control module is for determining and cut machine and cutting load control node set according to source lotus branch road coefficient of concordance, and definite machine and cutting load adjustment controlled quentity controlled variable of cutting;

Described load service restoration module is for distributing coefficient of concordance to select to have neither part nor lot in the generator of cutting machine control according to source lotus, and definite adjustment controlled quentity controlled variable and load restoration amount that has neither part nor lot in the generator of cutting machine control;

Described overload emergency control module, for the operating structure of unit shut algorithm control module and load service restoration module is superposeed, is obtained final adjustment controlled quentity controlled variable.

2. the circuit overload emergency control method based on source lotus coefficient of concordance, is characterized in that described method comprises:

Step 1: collection network structural parameters, each node voltage, each node power electric current, each node load electric current and branch current;

Step 2: calculate source lotus branch road coefficient of concordance and source lotus and distribute coefficient of concordance;

Step 3: determine and cut machine and cutting load control node set according to source lotus branch road coefficient of concordance, and determine the machine of cutting and cutting load adjustment controlled quentity controlled variable;

Step 4: distribute coefficient of concordance to select to have neither part nor lot in the generator of cutting machine control according to source lotus, and determine the adjustment controlled quentity controlled variable and the load restoration amount that have neither part nor lot in the generator of cutting machine control;

Step 5: the operating structure of unit shut algorithm control module and load service restoration module is superposeed, obtain final adjustment controlled quentity controlled variable.

3. method according to claim 2, is characterized in that the computational process of described source lotus branch road coefficient of concordance is:

Sub-step A1: adopt formula

calculate branch current and node Injection Current coefficient of relationship matrix

Sub-step A2: by branch current and node Injection Current coefficient of relationship matrix

each element is at the d of vectorial plane axle component composition matrix

Described matrix

for source lotus branch road coefficient of concordance matrix, the element in this matrix is source lotus branch road coefficient of concordance.

4. method according to claim 3, is characterized in that the computational process of described source lotus distribution coefficient of concordance is:

Sub-step B1: adopt formula

calculating generator node Injection Current and load bus Injection Current relational matrix

Wherein,

for branch current and node Injection Current mark matrix in the same way;

for branch current and the reverse mark matrix of node Injection Current;

Sub-step B2: by generator node Injection Current and load bus Injection Current relational matrix

each element is at the d of vectorial plane axle component composition matrix

Described matrix

for source lotus is distributed coefficient of concordance matrix, the element in this matrix is that source lotus is distributed coefficient of concordance.

5. method according to claim 4, is characterized in that described step 3 comprises:

Sub-step C1: obtain generator control node set G and load control node set L;

At source lotus branch road coefficient of concordance matrix

in, selected value be greater than 0 and corresponding node be the element of generator node, added generator control node set G;

At source lotus branch road coefficient of concordance matrix

in, selected value be less than 0 and corresponding node be the element that meets node, loaded and controlled node set L;

Sub-step C2: take economic loss minimum as target, set up first object majorized function and determine the first constraints;

Described first object majorized function is minF=F _a+ F _b-F _c-F _d;

Wherein, F is economic loss;

F _afor each generator reduces the sale of electricity loss of exerting oneself caused, and

Δ P _gifor the adjustment controlled quentity controlled variable of the generator node i in generator control node set G;

F _aPfor sale of electricity price;

F _pifor the electric energy online price of the generator node i in generator control node set G;

F _bfor total loss of outage of load bus, and

Δ P _lifor the adjustment controlled quentity controlled variable of load bus i in load control node set L;

F _lifor the energy value of load bus i in load control node set L;

F _cfor each generator reduces the coal consumption expense of exerting oneself saved, and $F_C=k_C*\underset{i\&Element;G}{\mathrm{\&Sigma;}}\left(a_{\mathrm{CRi}}(P_{\mathrm{Gi}}^2-{(P_{\mathrm{Gi}}-\mathrm{\&Delta;}{P}_{\mathrm{Gi}})}^2\right)+b_{\mathrm{Gi}}-(P_{\mathrm{Gi}}-\mathrm{\&Delta;}{P}_{\mathrm{Gi}});$

K _cfor coal price;

A _cRifor the coal consumption characterisitic function quadratic term coefficient of the generator node i in generator control node set G;

B _cRifor the coal consumption characterisitic function Monomial coefficient of the generator node i in generator control node set G;

P _gifor the active power output valve of the generator node i in generator control node set G;

F _dfor each generator reduces the saved pollution abatement costs of exerting oneself, and $F_D=k_D*\underset{{i\&Element;G}^{\&prime;}}{\mathrm{\&Sigma;}}\left(a_{\mathrm{PEi}}(P_{\mathrm{Gi}}^2-{(P_{\mathrm{Gi}}-\mathrm{\&Delta;}{P}_{\mathrm{Gi}})}^2+b_{\mathrm{PEi}}(P_{\mathrm{Gi}}-(P_{\mathrm{Gi}}-\mathrm{\&Delta;}{P}_{\mathrm{Gi}}))\right);$

K _dfor pollution control expense;

A _pEifor the pollutant emission characterisitic function quadratic term coefficient of the generator node i in generator control node set G;

B _pEifor the pollutant emission characterisitic function Monomial coefficient of the generator node i in generator control node set G;

Described the first constraints is:

$s.t.\left\{\begin{array}{c}\underset{i\&Element;G}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Gi}}\right|=\underset{j\&Element;L}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Lj}}\right|\\ {\tilde{C}}_{\mathrm{di}}\mathrm{\&Delta;}{\tilde{P}}_N=(1-a)P_{\mathrm{Bi}\max }-P_{\mathrm{Bi}}\\ {\tilde{P}}_B+{\tilde{C}}_d\mathrm{\&Delta;}{\tilde{P}}_N\&le;(1-a){\tilde{P}}_{B\max }\\ P_{\mathrm{Gi}\min }\&le;P_{\mathrm{Gi}}\&le;P_{\mathrm{Gi}\max }\\ V_{\mathrm{Ni}\min }\&le;V_{\mathrm{Ni}}\&le;V_{\mathrm{Ni}\max }\\ V_c<V_{\mathrm{cr}}\\ {\mathrm{\&delta;}}_{\max }<{\mathrm{\&delta;}}_r\end{array};\right.$

Wherein, C _difor source lotus branch road coefficient of concordance matrix in, value be greater than 0 and corresponding node be the matrix of the element composition of generator node;

α is the thermally-stabilised nargin of circuit;

for node injecting power variable quantity matrix;

for branch road injecting power matrix;

for branch road injecting power maximum matrix;

P _bimaxfor the through-put power upper limit of branch road i;

P _bifor the actual transmission power of branch road i;

P _gimaxfor the maximum injecting power of node i place generator;

P _giminfor the minimum injecting power of node i place generator;

V _nimaxfor node i place upper voltage limit;

V _niminfor node i place lower voltage limit;

V _nifor node i place magnitude of voltage;

V _cfor transient state energy value;

V _crfor transient energy function stability limit;

δ _maxfor system maximum work angular difference;

δ _rfor the system angle stability limit;

Sub-step C3: solve described first object majorized function, obtain the adjustment controlled quentity controlled variable of each generator node in generator control node set G and load and control the adjustment controlled quentity controlled variable of each load bus in node set L, being the machine of cutting and cutting load and adjusting controlled quentity controlled variable.

6. method according to claim 5, is characterized in that described step 4 comprises:

Sub-step D1: obtain and turn for generator node set G ' and wait to turn for load bus set L ';

The element of choosing in load control node set L distributes coefficient of concordance matrix source lotus the value of middle correspondence is positive generator node, is added and turns for generator node set G ';

Load is controlled to node set L as waiting to turn for load bus set L ';

Sub-step D2: the benefit of recovering economy to power is target to the maximum, sets up the second objective optimization function and determines the second constraints;

Described the second objective optimization target function is maxF=F _a+ F _b-F _c-F _d;

Wherein, F is economic loss;

F _afor each generator reduces the sale of electricity loss of exerting oneself caused, and

F _bfor total loss of outage of load bus, and

$F_C=k_C*\underset{{i\&Element;G}^{\&prime;}}{\mathrm{\&Sigma;}}\left(a_{\mathrm{CRi}}{(P_{\mathrm{Gi}}^2-\left(P_{\mathrm{Gi}}\mathrm{\&Delta;}{P}_{\mathrm{Gi}}\right)}^2\right)+b_{\mathrm{CRi}}(P_{\mathrm{Gi}}-(P_{\mathrm{Gi}}-\mathrm{\&Delta;}{P}_{\mathrm{Gi}}));$

$F_D=k_D*\underset{{i\&Element;G}^{\&prime;}}{\mathrm{\&Sigma;}}\left(a_{\mathrm{PEi}}(P_{\mathrm{Gi}}^2-{(P_{\mathrm{Gi}}-\mathrm{\&Delta;}{P}_{\mathrm{Gi}})}^2+b_{\mathrm{PEi}}(P_{\mathrm{Gi}}-(P_{\mathrm{Gi}}-\mathrm{\&Delta;}{P}_{\mathrm{Gi}}))\right);$

Described the second constraints is:

$\left\{\begin{array}{c}\underset{{i\&Element;G}^{\&prime;}}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Pi}}\right|=\underset{{j\&Element;L}^{\&prime;}}{\mathrm{\&Sigma;}}\left|\mathrm{\&Delta;}{P}_{\mathrm{Lj}}\right|\\ \mathrm{\&Delta;}{P}_{\mathrm{Li}}^{\&prime;}\&le;\mathrm{\&Delta;}{P}_{\mathrm{Li}}\\ {\tilde{P}}_B+{\tilde{C}}_d\mathrm{\&Delta;}{\tilde{P}}_N\&le;(1-a){\tilde{P}}_{B\max }\\ P_{\mathrm{Gi}\min }\&le;P_{\mathrm{Gi}}\&le;P_{\mathrm{Gi}\max }\\ V_{\mathrm{Ni}\min }\&le;V_{\mathrm{Ni}}\&le;V_{\mathrm{Ni}\max }\\ V_c<V_{\mathrm{cr}}\\ {\mathrm{\&delta;}}_{\max }<{\mathrm{\&delta;}}_r\end{array};\right.$

for system is recovered load value;

Sub-step D3: solve described the second objective optimization function, obtain Δ P _pibe the adjustment controlled quentity controlled variable and the load restoration amount that have neither part nor lot in the generator of cutting machine control.

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