CN103795063B - Based on circuit overload emergency control system and the method thereof of source lotus coefficient of concordance - Google Patents

Abstract

The invention discloses a kind of circuit overload emergency control system based on source lotus coefficient of concordance in power system overload emergency control off-load technical field and method thereof.System comprises the connected data acquisition module of order, source lotus coefficient of concordance asks for module, unit shut algorithm control module, load service restoration module and overload emergency control module; Method comprises collection network structural parameters, each node voltage, each node power electric current, load current and branch current; Calculating source lotus branch road coefficient of concordance and source lotus distribute coefficient of concordance; Determine machine of cutting and the set of cutting load Controlling vertex, determine machine of cutting and cutting load adjustment controlled quentity controlled variable; Select to have neither part nor lot in the generator cutting machine control, determine its adjustment controlled quentity controlled variable and load restoration amount; By unit shut algorithm control module and the superposition of load service restoration module arithmetic result, obtain and finally adjust controlled quentity controlled variable.The present invention had both fully ensured the safety and reliability of emergency control, significantly improved again the economy of control.<pb pnum="1" />

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, particularly relate to a kind of circuit overload emergency control system based on source lotus coefficient of concordance and method thereof.

Background technology

Along with the continuous expansion of electrical network scale and structure day by day complicated, safe and stable operation and the power supply reliability of system in the large-scale blackout serious threat caused by overload.When there is overload in circuit; in identification circuit overload and when guaranteeing to protect not malfunction; in order to avoid the generation of large-scale blackout from root; need to select suitable machine of cutting, cutting load Controlling vertex and corresponding controlled quentity controlled variable; emergency control off-load is carried out to overload circuit, ensures system safety stable operation.

At present, the common method for emergency control off-load is mainly divided into two classes, and a class is the emergency control based on sensitivity, the another kind of emergency control being based target and optimizing.Based on the emergency control of sensitivity using different generator and load to the index of the sensitivity of overload circuit as 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 having no idea to make full use of whole system realizes Control of decreasing load on a large scale.The emergency control of based target optimization can take into full account whole grid operating conditions, minimum for target with whole grid loss, be optimized search, but the target function quantizing grid loss describes mainly with controlled quentity controlled variable Δ P is minimum, have 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 taking into account economic loss comprehensively, proposes a kind of circuit overload emergency control system based on source lotus coefficient of concordance and method thereof.This invention first upgrades source lotus branch road coefficient of concordance according to system real time operation mode and source lotus distributes coefficient of concordance.On this basis, determine machine of cutting, the set of cutting load Controlling vertex according to source lotus branch road coefficient of concordance, with systematic economy loss reduction for target, utilize the optimization of Double fitness value particle cluster algorithm to search control strategy.Meanwhile, be ensure power supply reliability, distribute coefficient of concordance according to source lotus and do not causing new line again under overload condition, a selection part has neither part nor lot in the generator increase of cutting machine control and exerts oneself, utilize the optimization of Double fitness value particle cluster algorithm to search control strategy, drive part institute cutting load, restore electricity.This strategy of IEEE 10 machine 39 node system simulating, verifying under the prerequisite ensureing system safety stable operation, effectively can reduce the load of overload circuit, and has very high economy.

Summary of the invention

The object of the invention is to, a kind of circuit overload emergency control system based on source lotus coefficient of concordance and method thereof are 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 the connected data acquisition module of order, source lotus coefficient of concordance asks for module, unit shut algorithm control module, load service restoration module and overload emergency control module;

Described data acquisition module is used 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 asks for module for asking for source lotus branch road coefficient of concordance and source lotus distributes coefficient of concordance;

Described unit shut algorithm control module is used for determining machine of cutting and the set of cutting load Controlling vertex according to source lotus branch road coefficient of concordance, and determines machine of cutting and cutting load adjustment controlled quentity controlled variable;

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

Described overload emergency control module is used for the operation result of unit shut algorithm control module and load service restoration module to superpose, and obtains and finally adjusts 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: calculating source lotus branch road coefficient of concordance and source lotus distribute coefficient of concordance;

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

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

Step 5: superposed by the operation result of unit shut algorithm control module and load service restoration module, obtains and finally adjusts 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 axle component composition matrix of vectorial plane

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

The computational process that described source lotus distributes coefficient of concordance is:

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 axle component composition matrix of vectorial plane

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

Described step 3 comprises:

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

At source lotus branch road coefficient of concordance matrix in, selected value is greater than 0 and corresponding node is the element of generator node, is added generator control node set G;

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

Sub-step C2: minimum for target with economic loss, sets up first object majorized function and determines the first constraints;

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

Described first constraints is:

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

Sub-step C3: solve described first object majorized function, obtain the adjustment controlled quentity controlled variable of each load bus in the adjustment controlled quentity controlled variable of each generator node in generator control node set G and spatial load forecasting node set L, be the machine of cutting and cutting load adjustment 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 chosen in spatial load forecasting 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 ';

Using spatial load forecasting node set L as waiting to turn for load bus set L ';

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

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

Described second constraints is:

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

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

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

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 chart;

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

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

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 system circuit 27 through-put power situation of change curve chart after cutting machine, cutting load control;

Figure 14 is that IEEE10 machine 39 node system cuts machine, cutting load controls rear transient stability check plot;

Figure 15 is that the source lotus of load bus 15,20,26 distributes 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 restoration;

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

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

Embodiment

Below in conjunction with accompanying drawing, preferred embodiment is elaborated.It is emphasized that following explanation is only exemplary, instead of in order to limit the scope of the invention and 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 the connected data acquisition module of order, source lotus coefficient of concordance asks for module, unit shut algorithm control module, load service restoration module and overload emergency control module.

Data acquisition module is used 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 asks for module for asking for source lotus branch road coefficient of concordance and source lotus distributes coefficient of concordance.

Unit shut algorithm control module is used for determining machine of cutting and the set of cutting load Controlling vertex according to source lotus branch road coefficient of concordance, and determines machine of cutting and cutting load adjustment controlled quentity controlled variable.

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

Overload emergency control module is used for the operation result of unit shut algorithm control module and load service restoration module to superpose, and obtains and finally adjusts controlled quentity controlled variable.

The general 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, 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 asks for module.

After the network configuration of system is determined, in each line transmission 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 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, power supply and load that Some Related Algorithms fast searching is large with the overload circuit degree of association can be instructed, 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, system are regarded as a linear network (as shown in Figure 2), then 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 positive direction of direction for electric current phasor of network, therefore generator node Injection Current is just, load bus Injection Current is negative; for node voltage vector; for node admittance matrix, can by branch admittance matrix with network node incidence matrices obtain: easily know branch current phasor again with node voltage phasor there is relation: the pass that can obtain 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 circuitry number, and n is nodes, formula (4) can be turned to:

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

Row k in formula (5) represents the linear relationship between branch road k and each node Injection Current, can be represented by formula (6):

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

For each node, should Kirchhoff's current law (KCL) be met, 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, and have three branch roads to be connected with node 1, the sense of current on circuit as shown in FIG..Then there is following relation in Fig. 3:

$\left\{\begin{array}{c}\frac{{\stackrel{\&CenterDot;}{I}}_{2,B}}{{\stackrel{\&CenterDot;}{I}}_{2,B}+{\stackrel{\&CenterDot;}{I}}_{3,B}}{\stackrel{\&CenterDot;}{I}}_{N1}=\frac{{\stackrel{\&CenterDot;}{I}}_{N1}}{{\stackrel{\&CenterDot;}{I}}_N+{\stackrel{\&CenterDot;}{I}}_{1,B}}{\stackrel{\&CenterDot;}{I}}_{2,B}\\ \frac{{\stackrel{\&CenterDot;}{I}}_{3,B}}{{\stackrel{\&CenterDot;}{I}}_{2,B}+{\stackrel{\&CenterDot;}{I}}_{3,B}}{\stackrel{\&CenterDot;}{I}}_{N1}=\frac{{\stackrel{\&CenterDot;}{I}}_{N1}}{{\stackrel{\&CenterDot;}{I}}_N+{\stackrel{\&CenterDot;}{I}}_{1,B}}{\stackrel{\&CenterDot;}{I}}_{3,B}\end{array}\right.---\left(7\right)$

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

${\stackrel{\&CenterDot;}{I}}_{N1}=\frac{{\stackrel{\&CenterDot;}{I}}_{N1}}{{\stackrel{\&CenterDot;}{I}}_{N1}+{\stackrel{\&CenterDot;}{I}}_{1,B}}({\stackrel{\&CenterDot;}{I}}_{2,B}+{\stackrel{\&CenterDot;}{I}}_{3,B})---\left(8\right)$

Formula (5) is substituted into 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:

${\stackrel{\&CenterDot;}{I}}_{N1}=k\left(\tilde{C}\right({\mathrm{\&lambda;}}_{2i}){\stackrel{\&CenterDot;}{I}}_{2,B}+\tilde{C}({\mathrm{\&lambda;}}_{3i}\left){\stackrel{\&CenterDot;}{I}}_{3,B}\right)---\left(9\right)$

The relation stated by formula (9) 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 the branch current whether consistent with the Injection Current direction of node i (flow to node or flow out node) of circuit j, if consistent, be labeled as 1, all the other are 0; Inverted matrix be similarly a n*b rank matrix, when the branch current of circuit j is contrary with the Injection Current direction of node i, by element N _ijbe labeled as 1, all the other are 0.Formula (10) can be drawn:

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

In formula, " .* " representing matrix in each element and matrix in the corresponding element of each row be multiplied. matrix is a n*1 rank matrix, and wherein element can be tried to achieve by following formula:

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

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 node Injection Current phasor on the right side of formula (9) equation 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 the form represented by formula (1), (2), need the current relationship represented by formula (5), (13) to be converted into active power relation.There is following relation in (d is real axis q is the imaginary axis) known power and electric current in phasor plane:

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

Then branch road injecting power P _bcan be expressed as:

P _B＝U _dI _Bd+U _qI _Bq(15)

(5) are example with the formula, are transformed in phasor plane, known:

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

Formula (16) is substituted in 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 branch road each in actual electric network is much larger than resistance, therefore coefficient matrix with 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 in each line transmission power and system between generator power supply power, load power; be called that source lotus distributes 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, chooses and reduces the generator node that injecting power can reduce overload line power and add in set G, namely choose be greater than the generator node of 0; Obtain spatial load forecasting node set L, choose and reduce the load bus that injecting power can reduce overload line power and add in set L, the node injecting power due to load be opposite direction, so choose be less than the load bus of 0.

Sub-step 102:

Adopt the method for taking into account economic loss to select Controlling vertex with determine that controlled quentity controlled variable compares conventional method will science, more rigorous more.

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)

$C_{RGi}=a_{CRi}{P}_{Gi}^2+b_{CRi}{P}_{Gi}+c_{CRi}---\left(22\right)$

$P_{EGi}=a_{PEi}{P}_{Gi}^2+b_{PEi}{P}_{Gi}+c_{PEi}---\left(23\right)$

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 power generation characteristics of each generator and the loss of outage characteristic of each type load, the present invention is minimum for target with total system economic loss, selects Controlling vertex and the controlled quentity controlled variable determining each Controlling vertex.Total system economic loss is expressed as first object majorized function have:

F＝F _A+F _B-F _C-F _D(24)

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

In formula (24), F is total cost, and unit is unit, and it is made up of four parts: F _awhat represent is the sale of electricity loss that minimizing generator output causes, and is the power variation of each adjustment generator and generating profit (sale of electricity price f _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 save the product of coal-fired total amount after coal price is exerted oneself with adjustment; F _dwhat represent is because each generator reduces saved pollution abatement costs of exerting oneself, and its value is the product of decreasing pollution total emission volumn after pollution control expense exerts oneself with adjustment.

Except consider make target function get minimum except, in circuit overload emergency control policy, also should ensure that system can not lose a series of restrictive conditions such as stable because of taked control.

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

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

Secondly, after taking machine of cutting, cutting load to control, the overload on overload circuit is out-of-limit should be eliminated, and the off-load amount of overload circuit is determined by formula (27):

ΔP _Bi＝(1-α)P _{Bi max}-P _Bi(27)

P in formula _bifor the line transmission power before control, α is the thermally-stabilised nargin of circuit, P _{bi max}for line threshold through-put power.The line power in formula (27) left side is substituted with node injecting power:

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

Meanwhile, after taking emergency control measure, can not there is new overload circuit in system:

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

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

P _{Gi min}≤P _Gi≤P _{Gi max}(30)

V _{Ni min}≤V _Ni≤V _{Ni max}(31)

After taking 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, can build sets up cutting machine, cutting load emergency control model as follows:

min F＝F _A+F _B-F _C-F _D

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

The controlled quentity controlled variable of each Controlling vertex by optimized algorithm according to target function minimum and each equation inequality constraints combine to solve and determine.

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

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

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, be jointly made up of all constraints, its value size reflects 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 ', all load buses controlled by taking cutting load form.Obtain and turn for generator node set G ', the source lotus choosing the middle element of relative convergence L ' distributes coefficient of concordance for positive generator node, do not comprise the generator having taked to cut machine measure.

Sub-step 102: under the control measure of cutting machine, cutting load, the out-of-limit problem of circuit overload is resolved, but causes the loss of a large amount of load.In order to ensure the reliability of power supply, after cutting machine, cutting load control, a part of load needing to excise of band can be turned, the loss amount of minimizing load by increasing the non-generator output cutting machine control.

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 the maximization of economic benefit making to restore electricity.So its target function is the same with the target function form of cutting machine, cutting load controls, but pursuit is that target function gets maximum.In addition formula (27) etc. constraints also inapplicable here, with the addition of the inequality constraints condition of a load restoration upper limit, the cutting load amount before the load namely recovered is not more than:

ΔP′ _Li≤ΔP _Li(36)

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

max F＝F _A+F _B-F _C-F _D

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

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

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

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

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, be jointly made up of all constraints, its value size reflects 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 to carry out off-load to the out-of-limit circuit of overload as early as possible, ensure system safety stable operation, this part is basis and the core of emergency control policy; And load service restoration mainly considers the power supply reliability ensureing power supply user, reduce the economic loss having a power failure and bring, this part is supplementing of emergency control policy and extends as far as possible.In addition, system requires also different to this two-part time scale, and for cutting machine, cutting load control, in order to ensure the stable operation of system, need to realize Control of decreasing load as early as possible, time scale is just shorter; And for load service restoration, should consider that after the stable operation of guarantee system safety recovering load powers again, its time scale is loosely many compared with the former, therefore carries out after the former.

Using after the operation result of two parts superposes as final control strategy, namely finally adjust 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: calculating source lotus branch road coefficient of concordance and source lotus 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 axle component composition matrix of vectorial plane matrix for source lotus branch road coefficient of concordance matrix, the element in this matrix is source lotus branch road coefficient of concordance.

The computational process that source lotus distributes 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 node Injection Current oppositely mark matrix.

Sub-step B2: by generator node Injection Current and load bus Injection Current relational matrix each element is at the d axle component composition matrix of vectorial plane matrix for source lotus distributes coefficient of concordance matrix, the element in this matrix is that source lotus distributes coefficient of concordance.

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

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

At source lotus branch road coefficient of concordance matrix in, selected value is greater than 0 and corresponding node is the element of generator node, is added generator control node set G.

At source lotus branch road coefficient of concordance matrix in, selected value is less than 0 and corresponding node is the element of load bus, by its spatial load forecasting node set L.

Sub-step C2: minimum for target with economic loss, sets up first object majorized function and determines the first constraints.

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

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

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

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

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

The element chosen in spatial load forecasting 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 '.

Using spatial load forecasting node set L as waiting to turn for load bus set L '.

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

Second objective optimization target function is max F=F _a+ F _b-F _c-F _d.

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

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

Step 5: superposed by the operation result of unit shut algorithm control module and load service restoration module, obtains and finally adjusts controlled quentity controlled variable.

Embodiment 2

Shown in Fig. 5 is IEEE 10 machine 39 node diagram, 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 transmitted before fault passes through power flow transfer, cause circuit 27 and overload occurs, and line power surmounts through-put power stability limit, now, need by taking machine of cutting, cutting load to control and the measure of load service restoration reaches the target of overload circuit off-load, and make the economic loss that caused by emergency control policy off-load minimum.

After circuit 29 is cut, network topology structure changes, and first needs to revise former incidence matrices and branch admittance matrix namely matrix is found and matrix element corresponding to middle circuit 29 is deleted.According to system source lotus branch road coefficient of concordance after formula (4), the excision of (10) computational scheme coefficient of concordance is distributed 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 when 0.25s, is excised after 50ms by this power line main protection, and now due to power flow transfer, overload (P appears in another basic routing line 27 of same transmission cross-section _b27=209.97MW) and surmounted the transmission power limit (P of this circuit _b27max=200MW).The change of circuit 27 through-put power as shown in Figure 7.

Need 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 time to the loss of outage function of each load bus.The generator node participating in controlling should choose the source lotus branch road coefficient of concordance of circuit 27 in Fig. 6 be greater than the node of 0, namely reduce to exert oneself and can reduce the load of circuit.By finding, choosing generator node 35,36 is Controlling vertex, composition set G.For choosing of the load bus participating in controlling, select equally according to the source lotus branch road coefficient of concordance of circuit 27, the injecting power due to load bus is in the other direction, so should choose be less than the node of 0.By finding, choosing load bus 3,4,7,8,12,15,16,18,20,21,24,25,26,27,28,29 is Controlling vertex, composition set L.

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

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 is formed restrained boundary fitness function v (x according to formula (38) ₁, x ₂..., x _n), and searched for by Double fitness value particle swarm optimization algorithm.Each Controlling vertex controlled quentity controlled variable result after search as shown in figure 12, is designated as Δ P _n1.

From formula (18), the off-load amount of circuit 27 for taking machine of cutting, cutting load to control off-load when 20.24MW, 0.5s, after off-load, the through-put power of circuit 27 is 189.73MW (as shown in figure 13), is less than P _b27max, and meet the requirement of whole equation and inequality constraints condition.Cut machine, minimum total system economic loss that cutting load controls to cause is F ₁=193060.7 yuan/hour.The power system transient stability after emergency control is taked to verify situation 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 Figure 12, owing to taking the machine of cutting, cutting load measure, cause having the load of 3 nodes (15,20,26) to receive loss, in order to improve the reliability of customer power supply, save the economic loss having 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 Δ P _n1in the excision value of each load bus.

Equally first, choose Controlling vertex, for control overhead node, namely need 3 nodes restored electricity, they form load bus set L; For control generator node, non-other generator nodes cutting machine Controlling vertex should be chosen, and source lotus distribution coefficient of concordance should be chosen be greater than the generator node (there is relation of the supply) of zero.The source lotus of load bus 15,20,26 distributes coefficient of concordance as shown in figure 15, by finding (search result of three nodes gets union), choosing generator node 30,31,32,33,34,37,38,39 is Controlling vertex, composition set G.

After Controlling vertex is selected, determine target function f (x according to formula (25), (37) ₁, x ₂..., x _n), parameter with cut machine, cutting load controls consistent, is distinguished as the maximum instead of minimum value of 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 searched for by Double fitness value particle swarm optimization algorithm.Each Controlling vertex controlled quentity controlled variable result after search as shown in figure 16, is designated as Δ P _n2.

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

The power system transient stability after emergency control is taked to verify situation as shown in figure 17, system stability.Overall overload emergency control policy 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), the off-load amount of circuit 27 after 0.7s takes load restoration to control for 21.45MW, after off-load, the through-put power of circuit 27 is 188.52MW (as shown in figure 19), is less than P _b27max, and meet the requirement of whole equation 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; be only the present invention's preferably embodiment, but protection scope of the present invention is not limited thereto, is anyly familiar with those skilled in the art in the technical scope that the present invention discloses; the change that can expect easily or replacement, all should be encompassed within 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., based on a circuit overload emergency control system for source lotus coefficient of concordance, it is characterized in that described control system comprises the connected data acquisition module of order, source lotus coefficient of concordance asks for module, unit shut algorithm control module, load service restoration module and overload emergency control module;

Described data acquisition module is used 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 asks for module for asking for source lotus branch road coefficient of concordance and source lotus distributes coefficient of concordance;

Described unit shut algorithm control module is used for determining machine of cutting and the set of cutting load Controlling vertex according to source lotus branch road coefficient of concordance, and determines machine of cutting and cutting load adjustment controlled quentity controlled variable;

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

Described overload emergency control module is used for the operating structure of unit shut algorithm control module and load service restoration module to superpose, and obtains and finally adjusts controlled quentity controlled variable.

2., 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: calculating source lotus branch road coefficient of concordance and source lotus distribute coefficient of concordance;

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

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

Step 5: superposed by the operating structure of unit shut algorithm control module and load service restoration module, obtains and finally adjusts 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 axle component composition matrix of vectorial plane

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, $\tilde{K}=1./(1+\tilde{P}\tilde{C}(\mathrm{\&lambda;}));$

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

for branch current and node Injection Current oppositely mark matrix;

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

Described matrix for source lotus distributes coefficient of concordance matrix, the element in this matrix is that source lotus distributes 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 spatial load forecasting node set L;

At source lotus branch road coefficient of concordance matrix in, selected value is greater than 0 and corresponding node is the element of generator node, is added generator control node set G;

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

Sub-step C2: minimum for target with economic loss, sets up first object majorized function and determines 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 spatial load forecasting node set L;

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

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

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

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 first constraints is:

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

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

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 node i place generator maximum injection power;

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 load bus in the adjustment controlled quentity controlled variable of each generator node in generator control node set G and spatial load forecasting node set L, be the machine of cutting and cutting load adjustment 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 chosen in spatial load forecasting 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 ';

Using spatial load forecasting node set L as waiting to turn for load bus set L ';

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

Described 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

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

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

Described second constraints is:

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

Δ P ' _lifor System recover load value;

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