CN103825306A - Scheduling control method for generator - Google Patents

Abstract

The invention discloses a scheduling control method for a generator. The scheduling control method comprises the steps of determining math description forms of tide and line loss of a power system; constructing an optimal scheduling model in which the minimum line loss is taken as a target and the fairness constraint is considered according to the math description forms; calculating the optimal tide solution of a target function by using a genetic algorithm GA. The aims of economically and fairly distributing generator force and reducing network loss consumption are fulfilled.

Description

Generator dispatch control method

Technical field

The present invention relates to the generator scheduling controlling technical field in electric power system, particularly, relate to a kind of target function based on optimal load flow, loss minimization and the generator dispatch control method of genetic algorithm.

Background technology

Electric power system is bulky complex own not only, and it has extremely strong importance to the national economic development, and therefore, for a long time, safety, high-quality, economical operation are that China's dispatching of power netwoks moves topmost target always.

Power network line losses is that enterprises of managing electric wire netting's spontaneous power plant outlet in delivery of electrical energy and marketing process rises to client and stops produced power consumption and loss.The electric energy loss that power network produces in the time of transmission of electric energy has directly affected service efficiency and the economic benefit of electric energy.So how reasonable arrangement generator output of traffic department, reaches loss minimization, maximization of economic benefit, is the problem that work about electric power person pays close attention to always.

After separating the factory and network, traffic department faces again the fairness problem of scheduling, the hope generator of electricity power enterprise is with the highest load factor operation, but unreasonable due to electrical network, power supply architecture, scheduling institution is difficult to guarantee that every generator is all with the highest efficiency operation, therefore the reasonable problem that arranges generator output plan to become traffic department to need badly solution how just and fairly.

Xinjiang region is as the large-scale Energy Base of NORTHWEST CHINA portion, and the total installation of generating capacity of 2013 reaches 4311.3 ten thousand kilowatts, and wherein 614.6 ten thousand kilowatts of wind-powered electricity generations, account for 14.28% of total installation of generating capacity.Wind energy is as a kind of clean energy resource of pollution-free, renewable, zero cost, has great significance for the consumption that reduces the pollution of the gases such as carbon dioxide, sulfur dioxide to environment and save the fuel such as coal, heavy oil.In order to respond country's 12 development plans, greatly develop regenerative resource, Xinjiang region wind-powered electricity generation construction is further raised speed.But, in Wind Power Generation Industry high speed development, also produced a series of problem.Wind-powered electricity generation construction development has comparatively fast caused the unreasonable of Xinjiang region power supply architecture, thus derived wind-force exert oneself be obstructed, degradation problem under the increase of security of operation risk, peak load regulation network, fm capacity, restricting the ability of Xinjiang region transferring electricity from the west to the east; Meanwhile, a large amount of passing by of wind energy make Xinjiang Power produce a large amount of losses, have affected the economic benefit of power industry.

Therefore, consider that wind-powered electricity generation passes by, and take into account fair and economic generator dispatch control method and have important directive significance for the target of electric power system energy efficient, safe operation, realization economy, justice.

Summary of the invention

The object of the invention is to, for the problems referred to above, propose a kind of generator dispatch control method, to realize economic in the situation that considering that wind energy is passed by, to distribute liberally generator output advantage.

For achieving the above object, the technical solution used in the present invention is:

A kind of generator dispatch control method, comprises the following steps:

Determine the step of the mathematical description form of electric power system tide and line loss;

Set up take loss minimization as target, consider the step of the optimal scheduling model of fairness constraint based on above-mentioned mathematical description form;

And

Utilize Genetic Algorithms to solve the step of the optimal load flow solution of target function.

According to a preferred embodiment of the invention, the mathematical description form of described definite electric power system tide and line loss, for the nodal voltage equation by electric power system and power equation are set up the meritorious tidal current mathematical model of branch road of electric power system, and solve the via net loss that meritorious trend produces.

According to a preferred embodiment of the invention, the mathematical description form of described definite electric power system tide and line loss is specially:

For the electric power networks of N node, ground is as being not included with reference to node, as network configuration and component parameters known, network equation can be expressed as:

YU＝I

Wherein, Y is N × N rank node admittance matrixs, and U is N × 1 dimension node voltage column vector, and I is N × 1 dimension node Injection Current column vector,

Expand into

$\left[\begin{array}{c}{I}_1\\ I_2\\ I_3\\ ...\\ I_n\end{array}\right]=\left[\begin{array}{ccccc}{Y}_{11}& Y_{12}& Y_{13}& ...& Y_{1n}\\ Y_{21}& Y_{22}& Y_{23}& ...& Y_{2n}\\ Y_{31}& Y_{32}& Y_{33}& ...& Y_{3n}\\ ...& ...& ...& ...& ...\\ Y_{n1}& Y_{n2}& Y_{n3}& ...& Y_{\mathrm{nn}}\end{array}\right]\left[\begin{array}{c}{U}_1\\ U_2\\ U_3\\ ...\\ U_n\end{array}\right]$

In electric power system calculation, given operation variable is node injecting power, rather than node Injection Current, and above formula is rewritten as,

$\mathrm{YU}={\left[\frac{S}{U}\right]}^{*}$

Wherein, the injection complex power that S is node,

for the conjugation of S;

Above formula launches, obtains power equation to be,

${\stackrel{\·}{U}}_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{\stackrel{*}{Y}}_{\mathrm{ij}}{\stackrel{*}{U}}_j=P_i+j{Q}_i$

By node voltage polar coordinate representation, even ${\stackrel{\·}{U}}_i=U_i{e}^{{\mathrm{j\δ}}_i}=U_i(\cos {\mathrm{\δ}}_i+j\sin {\mathrm{\δ}}_i),$ Draw,

$U_i{e}^{{\mathrm{j\δ}}_i}\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}(G_{\mathrm{ij}}-j{B}_{\mathrm{ij}})U_j{e}^{-j{\mathrm{\δ}}_j}=P_i+j{Q}_i$

By real part and imaginary part apportion, obtain,

$U_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{U}_j(G_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}}+B_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}})=P_i$

$U_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{U}_j(G_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}}-B_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}})=Q_i$

P in formula _iand Q _ifor the power of load decision,

The meritorious through-put power of branch road can be expressed as:

$P_{\mathrm{ij}}=U_i^2{G}_{\mathrm{ij}}-U_i{U}_j(G_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}}+B_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}})$

$P_{\mathrm{ji}}=U_j^2{G}_{\mathrm{ij}}-U_i{U}_j(G_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ji}}+B_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ji}})$

Wherein, G _ij+ jB _ijfor branch road admittance.Therefore, the active loss of branch road ij is expressed as:

$P_{L-\mathrm{ij}}=P_{\mathrm{ij}}+P_{\mathrm{ji}}=(U_i^2+U_j^2)G_{\mathrm{ij}}-2U_i{U}_j{G}_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}}$

Due to δ _ijconventionally very little, thereby,

$\cos {\mathrm{\δ}}_{\mathrm{ij}}=1-\frac{{{\mathrm{\δ}}_{\mathrm{ij}}}^2}{2}$

Draw,

P _L-ij＝(U _i-U _j) ²G _ij+(δ _i-δ _j) ²U _iU _jG _ij，

Because voltage magnitude is insensitive to the meritorious variation of injecting of node, can think that it is invariable.Therefore, grid loss changing unit is only relevant to the meritorious injection of node, is expressed as:

$P_{\mathrm{L\δ}}=\underset{\mathrm{ij}}{\mathrm{\Σ}}{({\mathrm{\δ}}_i-{\mathrm{\δ}}_j)}^2{U}_i{U}_j{G}_{\mathrm{ij}},$

Be expressed as with matrix form:

P _Lδ＝δ ^TG ^*δ

Wherein, δ is the column vector of node voltage phase angle, G ^*computing formula be

$\left\{\begin{array}{c}{G^{*}}_{\mathrm{ij}}=-U_i{U}_j{G}_{\mathrm{ij}}\\ {G^{*}}_{\mathrm{ii}}=-\underset{j\≠i}{\overset{N}{\underset{j=1}{\mathrm{\Σ}}}}{G^{*}}_{\mathrm{ij}}\end{array}\right..$

According to a preferred embodiment of the invention, described take loss minimization as target, consider specifically to comprise the optimal scheduling model of fairness constraint:

Set up target function with loss minimization, add the equality constraint of power flow equation; Add the inequality constraints of fairness condition; Consider meritorious exert oneself restriction and set end voltage restriction.

According to a preferred embodiment of the invention, the optimal load flow model take loss minimization as target be power flow equation as:

minP _Lδ＝min(δ ^TG ^*δ)。

According to a preferred embodiment of the invention, the equality constraint of described power flow equation comprises, active balance constraint and reactive balance constraint; Described active balance retrains for each node, has

$P_{\mathrm{Gi}}-P_{\mathrm{Li}}-U_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{U}_j(G_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}}+B_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}})=0$

Wherein, P _gifor the active power of the actual output of generator; P _lifor the active power of load actual consumption;

For whole system, have

$\underset{i=1}{\overset{i=n}{\mathrm{\Σ}}}{P}_{\mathrm{Gi}}-\underset{i=1}{\overset{i=n}{\mathrm{\Σ}}}{P}_{\mathrm{Li}}-\mathrm{\Δ}{P}_{\mathrm{\Σ}}=0$

Wherein, Δ P _Σfor total active loss of network;

Described reactive balance constraint: have for each node

$Q_{\mathrm{Gi}}-Q_{\mathrm{Li}}+\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{Q}_{\mathrm{ci}}-U_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{U}_j(G_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}}-B_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}})=0$

Wherein, Q _gifor the reactive power of the actual output of generator; Q _lifor the reactive power of load actual consumption; Q _cifor the reactive power of compensation equipment supply;

For whole system, have

$\underset{i=1}{\overset{i=n}{\mathrm{\Σ}}}{Q}_{\mathrm{GCi}}-\underset{i=1}{\overset{i=n}{\mathrm{\Σ}}}{Q}_{\mathrm{Li}}-\mathrm{\Δ}{Q}_{\mathrm{\Σ}}=0$

Wherein, the reactive power Q of power supply supply _gCformed the reactive power Q of i.e. generator supply by two parts _greactive power Q with compensation equipment supply _c; Δ Q _Σfor total reactive loss of network.

According to a preferred embodiment of the invention, the inequality constraints of described fairness condition comprises generated power units limits, fairness Index Constraints and generator voltage constraint,

Described generated power units limits is:

P _Fimin≤P _Fi≤P _Fimax

P _fifor controlled generating set is exerted oneself, P _wifor uncontrollable generator output;

Described fairness Index Constraints: establish α _ibe the poor of the load factor of i platform unit and total system Rate of average load, in keeping system, all adjustable units actual exerted oneself and maintains an identical value left and right with the ratio of installed capacity,

α _i=λ _i-λ，-0.05≤α _i≤0.05。

Described generator voltage constraint:

U _imin≤U _i≤U _imax。

Technical scheme of the present invention has following beneficial effect:

Technical scheme of the present invention, carries out scheduling controlling based on optimal load flow to generator, improves economy, the fairness of management and running department power system dispatching, is considering the effective system losses that reduce under the prerequisite that wind energy is passed by.Reach economical, distribute generator output and reduce the object that network loss consumes liberally.

Below by drawings and Examples, technical scheme of the present invention is described in further detail.

Accompanying drawing explanation

Fig. 1 is the generator dispatch control method flow chart described in the embodiment of the present invention.

Embodiment

Below in conjunction with accompanying drawing, the preferred embodiments of the present invention are described, should be appreciated that preferred embodiment described herein, only for description and interpretation the present invention, is not intended to limit the present invention.

As shown in Figure 1, a kind of generator dispatch control method, the generator dispatch control method of the target function based on optimal load flow, loss minimization and genetic algorithm comprises the following steps:

Determine the step of the mathematical description form of electric power system tide and line loss;

Set up take loss minimization as target, consider the step of the optimal scheduling model of fairness constraint based on above-mentioned mathematical description form;

And

Utilize Genetic Algorithms to solve the step of the optimal load flow solution of target function.

Wherein, determine the mathematical description form of electric power system tide and line loss, for the nodal voltage equation by electric power system and power equation are set up the meritorious tidal current mathematical model of branch road of electric power system, and solve the via net loss that meritorious trend produces.

The mathematical description form of determining electric power system tide and line loss is specially:

For the electric power networks of N node, ground is as being not included with reference to node, as network configuration and component parameters known, network equation can be expressed as:

YU＝I

Wherein, Y is N × N rank node admittance matrixs, and U is N × 1 dimension node voltage column vector, and I is N × 1 dimension node Injection Current column vector,

Expand into

$\left[\begin{array}{c}{I}_1\\ I_2\\ I_3\\ ...\\ I_n\end{array}\right]=\left[\begin{array}{ccccc}{Y}_{11}& Y_{12}& Y_{13}& ...& Y_{1n}\\ Y_{21}& Y_{22}& Y_{23}& ...& Y_{2n}\\ Y_{31}& Y_{32}& Y_{33}& ...& Y_{3n}\\ ...& ...& ...& ...& ...\\ Y_{n1}& Y_{n2}& Y_{n3}& ...& Y_{\mathrm{nn}}\end{array}\right]\left[\begin{array}{c}{U}_1\\ U_2\\ U_3\\ ...\\ U_n\end{array}\right]$

In electric power system calculation, given operation variable is node injecting power, rather than node Injection Current, and above formula is rewritten as,

$\mathrm{YU}={\left[\frac{S}{U}\right]}^{*}$

Wherein, the injection complex power that S is node,

for the conjugation of S;

Above formula launches, obtains power equation to be,

${\stackrel{\·}{U}}_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{\stackrel{*}{Y}}_{\mathrm{ij}}{\stackrel{*}{U}}_j=P_i+j{Q}_i$

By node voltage polar coordinate representation, even ${\stackrel{\·}{U}}_i=U_i{e}^{{\mathrm{j\δ}}_i}=U_i(\cos {\mathrm{\δ}}_i+j\sin {\mathrm{\δ}}_i),$ Draw,

$U_i{e}^{{\mathrm{j\δ}}_i}\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}(G_{\mathrm{ij}}-j{B}_{\mathrm{ij}})U_j{e}^{-j{\mathrm{\δ}}_j}=P_i+j{Q}_i$

By real part and imaginary part apportion, obtain,

$U_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{U}_j(G_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}}+B_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}})=P_i$

$U_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{U}_j(G_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}}-B_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}})=Q_i$

P in formula _iand Q _ifor the power of load decision,

The meritorious through-put power of branch road can be expressed as:

$P_{\mathrm{ij}}=U_i^2{G}_{\mathrm{ij}}-U_i{U}_j(G_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}}+B_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}})$

$P_{\mathrm{ji}}=U_j^2{G}_{\mathrm{ij}}-U_i{U}_j(G_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ji}}+B_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ji}})$

Wherein, G _ij+ jB _ijfor branch road admittance.Therefore, the active loss of branch road ij is expressed as:

$P_{L-\mathrm{ij}}=P_{\mathrm{ij}}+P_{\mathrm{ji}}=(U_i^2+U_j^2)G_{\mathrm{ij}}-2U_i{U}_j{G}_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}}$

Due to δ _ijconventionally very little, thereby,

$\cos {\mathrm{\δ}}_{\mathrm{ij}}=1-\frac{{{\mathrm{\δ}}_{\mathrm{ij}}}^2}{2}$

Draw,

P _L-ij＝(U _i-U _j) ²G _ij+(δ _i-δ _j) ²U _iU _jG _ij，

Because voltage magnitude is insensitive to the meritorious variation of injecting of node, can think that it is invariable.Therefore, grid loss changing unit is only relevant to the meritorious injection of node, is expressed as:

$P_{\mathrm{L\δ}}=\underset{\mathrm{ij}}{\mathrm{\Σ}}{({\mathrm{\δ}}_i-{\mathrm{\δ}}_j)}^2{U}_i{U}_j{G}_{\mathrm{ij}},$

Be expressed as with matrix form:

P _Lδ＝δ ^TG ^*δ

Wherein, δ is the column vector of node voltage phase angle, G ^*computing formula be

$\left\{\begin{array}{c}{G^{*}}_{\mathrm{ij}}=-U_i{U}_j{G}_{\mathrm{ij}}\\ {G^{*}}_{\mathrm{ii}}=-\underset{j\≠i}{\overset{N}{\underset{j=1}{\mathrm{\Σ}}}}{G^{*}}_{\mathrm{ij}}\end{array}\right..$

Take loss minimization as target, consider specifically to comprise the optimal scheduling model of fairness constraint:

Set up target function with loss minimization, add the equality constraint of power flow equation; Add the inequality constraints of fairness condition; Consider meritorious exert oneself restriction and set end voltage restriction.

Optimal load flow model take loss minimization as target be power flow equation as:

minP _Lδ＝min(δ ^TG ^*δ)。

In meritorious exert oneself restriction and set end voltage restriction, generated power units limits is:

P _Fimin≤P _Fi≤P _Fimax

P _fifor controlled generating set is exerted oneself, P _wifor uncontrollable generator output.

The inequality constraints of fairness condition: establish α _ibe the poor of the load factor of i platform unit and total system Rate of average load, in keeping system, all adjustable units actual exerted oneself and maintains an identical value left and right with the ratio of installed capacity,

α _i=λ _i-λ，-0.05≤α _i≤0.05。

Meritorious generator voltage constraint of exerting oneself in restriction and set end voltage restriction:

U _imin≤U _i≤U _imax。

The further detailed step of mathematical description form of determining electric power system tide and line loss is as follows:

For the electric power networks of N node (as being not included with reference to node), if network configuration and component parameters are known, network equation can be expressed as

YU＝I

Wherein, Y is N × N rank node admittance matrixs; U is N × 1 dimension node voltage column vector; I is N × 1 dimension node Injection Current column vector.If disregard the non-linear of network element, do not consider phase shifting transformer yet, Y is symmetrical matrix.

Expanded into

$\left[\begin{array}{c}{I}_1\\ I_2\\ I_3\\ ...\\ I_n\end{array}\right]=\left[\begin{array}{ccccc}{Y}_{11}& Y_{12}& Y_{13}& ...& Y_{1n}\\ Y_{21}& Y_{22}& Y_{23}& ...& Y_{2n}\\ Y_{31}& Y_{32}& Y_{33}& ...& Y_{3n}\\ ...& ...& ...& ...& ...\\ Y_{n1}& Y_{n2}& Y_{n3}& ...& Y_{\mathrm{nn}}\end{array}\right]\left[\begin{array}{c}{U}_1\\ U_2\\ U_3\\ ...\\ U_n\end{array}\right]$

During electric power system is calculated, given operation variable is node injecting power, rather than node Injection Current, and above formula can be rewritten as

$\mathrm{YU}={\left[\frac{S}{U}\right]}^{*}$

Wherein, the injection complex power that S is node;

for the conjugation of S.

Above formula is launched, and available power equation is

${\stackrel{\·}{U}}_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{\stackrel{*}{Y}}_{\mathrm{ij}}{\stackrel{*}{U}}_j=P_i+j{Q}_i$

If node voltage polar coordinate representation, even

${\stackrel{\·}{U}}_i=U_i{e}^{{\mathrm{j\δ}}_i}=U_i(\cos {\mathrm{\δ}}_i+j\sin {\mathrm{\δ}}_i),$ Substitution obtains

$U_i{e}^{{\mathrm{j\δ}}_i}\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}(G_{\mathrm{ij}}-j{B}_{\mathrm{ij}})U_j{e}^{-j{\mathrm{\δ}}_j}=P_i+j{Q}_i$

By real part and imaginary part apportion, can obtain

$U_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{U}_j(G_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}}+B_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}})=P_i$

$U_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{U}_j(G_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}}-B_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}})=Q_i$

For load bus, the P of this node, Q is determined by workload demand, is generally uncontrollable.The feature of this category node is P, and Q is given, the V of this node, and θ waits to ask.This category node is called PQ node.Also can regard P as without the contact node injecting, the given node of Q, its P, Q value is all zero.

For generator node, because making the voltage magnitude of this point, generator excitation regulating action remains unchanged, and active power determines by output of a generator, so the P of this node, V is given, Q, θ waits to ask.This category node is called PV node.

The meritorious through-put power of branch road can be expressed as:

$P_{\mathrm{ij}}=U_i^2{G}_{\mathrm{ij}}-U_i{U}_j(G_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}}+B_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}})$

$P_{\mathrm{ji}}=U_j^2{G}_{\mathrm{ij}}-U_i{U}_j(G_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ji}}+B_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ji}})$

Wherein, G _ij+ jB _ijfor branch road admittance.Therefore, the active loss of branch road ij can be expressed as:

$P_{L-\mathrm{ij}}=P_{\mathrm{ij}}+P_{\mathrm{ji}}=(U_i^2+U_j^2)G_{\mathrm{ij}}-2U_i{U}_j{G}_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}}$

Due to δ _ijconventionally very little, thereby,

$\cos {\mathrm{\δ}}_{\mathrm{ij}}=1-\frac{{{\mathrm{\δ}}_{\mathrm{ij}}}^2}{2}$

Above formula substitution can be obtained

P _L-ij＝(U _i-U _j) ²G _ij+(δ _i-δ _j) ²U _iU _jG _ij

Because voltage magnitude is insensitive to the meritorious variation of injecting of node, can think that it is invariable.Therefore, grid loss changing unit is only relevant to the meritorious injection of node, can be expressed as:

$P_{\mathrm{L\δ}}=\underset{\mathrm{ij}}{\mathrm{\Σ}}{({\mathrm{\δ}}_i-{\mathrm{\δ}}_j)}^2{U}_i{U}_j{G}_{\mathrm{ij}}$

Be expressed as with matrix form:

P _Lδ＝δ ^TG ^*δ

Wherein, δ is the column vector of node voltage phase angle, G ^*computing formula be

$\left\{\begin{array}{c}{G^{*}}_{\mathrm{ij}}=-U_i{U}_j{G}_{\mathrm{ij}}\\ {G^{*}}_{\mathrm{ii}}=-\underset{j\≠i}{\overset{N}{\underset{j=1}{\mathrm{\Σ}}}}{G^{*}}_{\mathrm{ij}}\end{array}\right.$

Described take loss minimization as target, consider the optimal scheduling model of fairness constraint:

Target function: the optimal load flow model take loss minimization as target

minP _Lδ＝min(δ ^TG ^*δ)

Meritorious the exerting oneself that in model, adjustable control variables is fired power generating unit, nonadjustable control variables is that the meritorious of wind-powered electricity generation unit exerted oneself, state variable is that generator reactive is exerted oneself and load bus voltage.

Equality constraint-power flow equation

(1) active balance constraint: for each node, have

$P_{\mathrm{Gi}}-P_{\mathrm{Li}}-U_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{U}_j(G_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}}+B_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}})=0$

Wherein, P _gifor the active power of the actual output of generator; P _lifor the active power of load actual consumption.

For whole system, have

$\underset{i=1}{\overset{i=n}{\mathrm{\Σ}}}{P}_{\mathrm{Gi}}-\underset{i=1}{\overset{i=n}{\mathrm{\Σ}}}{P}_{\mathrm{Li}}-\mathrm{\Δ}{P}_{\mathrm{\Σ}}=0$

Wherein, Δ P _Σfor total active loss of network.

(2) reactive balance constraint: have for each node

$Q_{\mathrm{Gi}}-Q_{\mathrm{Li}}+\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{Q}_{\mathrm{ci}}-U_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{U}_j(G_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}}-B_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}})=0$

Wherein, Q _gifor the reactive power of the actual output of generator; Q _lifor the reactive power of load actual consumption; Q _cifor the reactive power of compensation equipment supply.

For whole system, have

$\underset{i=1}{\overset{i=n}{\mathrm{\Σ}}}{Q}_{\mathrm{GCi}}-\underset{i=1}{\overset{i=n}{\mathrm{\Σ}}}{Q}_{\mathrm{Li}}-\mathrm{\Δ}{Q}_{\mathrm{\Σ}}=0$

Wherein, the reactive power Q of power supply supply _gCformed the reactive power Q of i.e. generator supply by two parts _greactive power Q with compensation equipment supply _c; Δ Q _Σfor total reactive loss of network.

Inequality constraints

(1) generated power units limits: establish blower fan and all access electrical network, and with nonadjustable generated output operation, therefore P _wifor uncontrollable generator output; Fired power generating unit is exerted oneself as regulated variable, therefore P _fiexert oneself for controlled generating set, need meet its meritorious constraint.

P _Fimin≤P _Fi≤P _Fimax

(2) fairness Index Constraints: definition α _ibe the poor of the load factor of i platform unit and total system Rate of average load, in keeping system, all adjustable units actual exerted oneself and maintains an identical value left and right with the ratio of installed capacity.

α _i=λ _i-λ，-0.05≤α _i≤0.05。

(3) generator voltage constraint:

U _imin≤U _i≤U _imax

Using loss minimization as target, solve target function and use GA genetic algorithm, concrete steps are as follows:

1) coding adopts and has easily convergence under large aberration rate, processes comparatively effectively real coding of function optimization problem.

2) initialization population: adopt Small section method, first the span of each parameter to be optimized is divided into the total several minizones of colony, in each minizone, generate randomly respectively a more initial individuality, this has guaranteed the range that initial population distributes at Feasible Solution Region to a certain extent, and amount of calculation is also little simultaneously.

3) choosing of target function: the target function using exponential type target function as parameter identification.

4) selection strategy: adopt random system of selection uniformly.

5) crossover and mutation: cross method is selected Heuristic, variation method is selected Adaptive feasible.

In conjunction with IEEE14 node system, further embodiment is

Generator in IEEE14 system 1 is made as to balance node, and generator 2, generator 3, generator 4 be as the adjustable generator of firepower, and generator 5 is made as the exert oneself wind-driven generator of operation with 100MW.

The foundation of tide model can be understood as according to nodal voltage equation and power equation and solves power flow equation.

Nodal voltage equation is:

$\left[\begin{array}{c}{I}_1\\ I_2\\ I_3\\ ...\\ I_n\end{array}\right]=\left[\begin{array}{ccccc}{Y}_{11}& Y_{12}& Y_{13}& ...& Y_{1n}\\ Y_{21}& Y_{22}& Y_{23}& ...& Y_{2n}\\ Y_{31}& Y_{32}& Y_{33}& ...& Y_{3n}\\ ...& ...& ...& ...& ...\\ Y_{n1}& Y_{n2}& Y_{n3}& ...& Y_{\mathrm{nn}}\end{array}\right]\left[\begin{array}{c}{U}_1\\ U_2\\ U_3\\ ...\\ U_n\end{array}\right]$

Power equation is:

${\stackrel{\·}{U}}_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{\stackrel{*}{Y}}_{\mathrm{ij}}{\stackrel{*}{U}}_j=P_i+j{Q}_i$

And then can obtain active power equation and reactive power equation:

$U_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{U}_j(G_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}}+B_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}})=P_i$

$U_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{U}_j(G_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}}-B_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}})=Q_i$

Solve line loss model according to the tide model of setting up, the active power loss equation that can obtain branch road ij in conjunction with meritorious power equation is

$P_{L-\mathrm{ij}}=P_{\mathrm{ij}}+P_{\mathrm{ji}}=(U_i^2+U_j^2)G_{\mathrm{ij}}-2U_i{U}_j{G}_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}}$

Node is injected to meritorious caused via net loss to be expressed as by the form of matrix:

P _Lδ＝δ ^TG ^*δ

G ^*computing formula be

$\left\{\begin{array}{c}{G^{*}}_{\mathrm{ij}}=-U_i{U}_j{G}_{\mathrm{ij}}\\ {G^{*}}_{\mathrm{ii}}=-\underset{j\≠i}{\overset{N}{\underset{j=1}{\mathrm{\Σ}}}}{G^{*}}_{\mathrm{ij}}\end{array}\right.$

Set up the optimal load flow model take loss minimum as target according to via net loss model:

minP _Lδ＝min(δ ^TG ^*δ)

Obtain i.e. meritorious power flow equation and the reactive power flow equation of equality constraint of target function according to tide model:

Active balance constraint: for each node, have

$P_{\mathrm{Gi}}-P_{\mathrm{Li}}-U_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{U}_j(G_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}}+B_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}})=0$

Reactive balance constraint: for each node, have

$Q_{\mathrm{Gi}}-Q_{\mathrm{Li}}+\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{Q}_{\mathrm{ci}}-U_i\underset{j=1}{\overset{j=n}{\mathrm{\Σ}}}{U}_j(G_{\mathrm{ij}}\sin {\mathrm{\δ}}_{\mathrm{ij}}-B_{\mathrm{ij}}\cos {\mathrm{\δ}}_{\mathrm{ij}})=0$

Consideration based on to fairness and generated power Power generation limits and the restriction of generating terminal voltage, adds inequality constraints simultaneously.Generated power units limits, the unit that can regulate is thermal power generation unit, considers the meritorious bound restriction of exerting oneself of fired power generating unit:

P _Fimin≤P _Fi≤P _Fimax

According to the fairness index α proposing _iset up fairness constraint, setting deviation is ± 0.05, and fairness constraint inequality is:

|α _i|≤0.05

Generator voltage is constrained to:

U _imin≤U _i≤U _imax

Can set up optimal load flow model according to target function and constraints, Genetic Algorithms can solve nonlinear optimal problem, and therefore, the present invention adopts Genetic Algorithms to solve optimal load flow, and according to the result of trying to achieve, generator output is adjusted, concrete steps are as follows:

1) coding adopts and has easily convergence under large aberration rate, processes comparatively effectively real coding of function optimization problem.

2) initialization population: adopt Small section method, first the span of each parameter to be optimized is divided into the total several minizones of colony, in each minizone, generate randomly respectively a more initial individuality, this has guaranteed the range that initial population distributes at Feasible Solution Region to a certain extent, and amount of calculation is also little simultaneously.

3) choosing of target function: using the optimal load flow model of loss minimization as target function.

4) selection strategy: adopt random system of selection uniformly.

5) crossover and mutation: cross method is selected Heuristic, variation method is selected Adaptive feasible.

The optimized individual number of GA is set to 120, and genetic algebra is set to 25.

Generator parameter before adjusting and fairness index are contrasted with the result that solves optimal load flow gained, and concrete condition is in table 1.

Table 1, generator parameter contrast table:

Can find out the generator output allocative decision by solving optimal load flow gained according to the result of upper table, every generator loading rate and system Rate of average load are more approaching, fairness index significantly reduces, the load factor that shows each generating set all maintains near average, has improved the fairness of dispatching of power netwoks.

Meanwhile, the grid loss before contrast is adjusted and after adjusting, details are in table 2.

Table 2, network loss situation contrast table:

?	Before adjustment (MW)	After adjusting (MW)
			Via net loss	10.997	9.145

The dispatching method that visible the present invention proposes, in guaranteeing fairness, has also significantly reduced the loss in network, has improved the economy of power system operation.To sum up, it is effective that the present invention proposes generator dispatch control method, has potential engineering using value.

Finally it should be noted that: the foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, although the present invention is had been described in detail with reference to previous embodiment, for a person skilled in the art, its technical scheme that still can record aforementioned each embodiment is modified, or part technical characterictic is wherein equal to replacement.Within the spirit and principles in the present invention all, any modification of doing, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.

Claims (7)

1. a generator dispatch control method, is characterized in that, comprises the following steps:

Determine the step of the mathematical description form of electric power system tide and line loss;

Set up take loss minimization as target, consider the step of the optimal scheduling model of fairness constraint based on above-mentioned mathematical description form;

And

Utilize Genetic Algorithms to solve the step of the optimal load flow solution of target function.

2. generator dispatch control method according to claim 1, it is characterized in that, the mathematical description form of described definite electric power system tide and line loss, for the nodal voltage equation by electric power system and power equation are set up the meritorious tidal current mathematical model of branch road of electric power system, and solve the via net loss that meritorious trend produces.

3. generator dispatch control method according to claim 2, is characterized in that, the mathematical description form of described definite electric power system tide and line loss is specially:

For the electric power networks of N node, ground is as being not included with reference to node, as network configuration and component parameters known, network equation can be expressed as:

YU＝I

Wherein, Y is N × N rank node admittance matrixs, and U is N × 1 dimension node voltage column vector, and I is N × 1 dimension node Injection Current column vector,

Expand into

In electric power system calculation, given operation variable is node injecting power, rather than node Injection Current, and above formula is rewritten as,

Wherein, the injection complex power that S is node,

for the conjugation of S;

Above formula launches, obtains power equation to be,

By node voltage polar coordinate representation, even

draw,

By real part and imaginary part apportion, obtain,

P in formula _iand Q _ifor the power of load decision,

The meritorious through-put power of branch road can be expressed as:

Wherein, G _ij+ jB _ijfor branch road admittance, therefore, the active loss of branch road ij is expressed as:

Due to δ _ijconventionally very little, thereby,

Draw,

P _L-ij＝(U _i-U _j) ²G _ij+(δ _i-δ _j) ²U _iU _jG _ij，

Because voltage magnitude is insensitive to the meritorious variation of injecting of node, can think that it is invariable, therefore, grid loss changing unit is only relevant to the meritorious injection of node, is expressed as:

Be expressed as with matrix form:

P _Lδ＝δ ^TG ^*δ

Wherein, δ is the column vector of node voltage phase angle, G ^*computing formula be

4. according to the generator dispatch control method described in claim 2 or 3, it is characterized in that, described take loss minimization as target, consider specifically to comprise the optimal scheduling model of fairness constraint:

Set up target function with loss minimization, add the equality constraint of power flow equation; Add the inequality constraints of fairness condition; Consider meritorious exert oneself restriction and set end voltage restriction.

5. generator dispatch control method according to claim 4, is characterized in that, the optimal load flow model take loss minimization as target be power flow equation as:

minP _Lδ＝min(δ ^TG ^*δ)。

6. generator dispatch control method according to claim 4, is characterized in that, the equality constraint of described power flow equation comprises, active balance constraint and reactive balance constraint; Described active balance retrains for each node, has

Wherein, P _gifor the active power of the actual output of generator; P _lifor the active power of load actual consumption;

For whole system, have

Wherein, Δ P _Σfor total active loss of network;

Described reactive balance constraint: have for each node

Wherein, Q _gifor the reactive power of the actual output of generator; Q _lifor the reactive power of load actual consumption; Q _cifor the reactive power of compensation equipment supply;

For whole system, have

Wherein, the reactive power Q of power supply supply _gCformed the reactive power Q of i.e. generator supply by two parts _greactive power Q with compensation equipment supply _c; Δ Q _Σfor total reactive loss of network.

7. generator dispatch control method according to claim 4, is characterized in that, the inequality constraints of described fairness condition comprises generated power units limits, fairness Index Constraints and generator voltage constraint,

Described generated power units limits is:

P _Fimin≤P _Fi≤P _Fimax

P _fifor controlled generating set is exerted oneself, P _wifor uncontrollable generator output;

Described fairness Index Constraints: establish α _ibe the poor of the load factor of i platform unit and total system Rate of average load, in keeping system, all adjustable units actual exerted oneself and maintains an identical value left and right with the ratio of installed capacity,

α _i=λ _i-λ，-0.05≤α _i≤0.05，

Described generator voltage constraint:

U _imin≤U _i≤U _imax。

Images