CN103124072B - Load characteristic considered power grid dynamic reactive power optimization system and method - Google Patents

Abstract

The invention relates to the field of electrical power system dynamic reactive power control, in particular to a load characteristic considered power grid dynamic reactive power optimization system and method. One port of a load state collector is connected to a load dynamic reactive power regulation controller, collected and processed power grid load characteristics are transmitted to the load dynamic reactive power controller, the load dynamic reactive power controller is connected with a load dynamic reactive power executor, and the load dynamic reactive power executor is used for guiding an electrical power system to operate according to optimizing results of the dynamic reactive power controller. According to the load characteristic considered power grid dynamic reactive power optimization system and method, data required by reactive power optimizing are directly read from an actual power grid, system hardware investments are effectively saved, characteristic variables of factors of load characteristics, load voltage fluctuation and the like are extracted, real-time changing conditions of the power grid are exactly reflected, and the computing complexity is effectively reduced. Powerful scientific theory supports are provided for the field of dynamic reactive power compensation in the future, dynamic reactive power compensation of the power grid is achieved with the minimum reactive power compensation quantity, and thereby enormous economic benefits are achieved.

Description

Consider the electrical network Dynamic reactive power optimization system and method for part throttle characteristics

Art

The present invention relates to field of electrical power system dynamic reactive power control, particularly consider the electrical network Dynamic reactive power optimization system and method for part throttle characteristics.By carrying out analog computation to each section of actual electric network, take into full account the idle characteristic of load in actual electric network, each node voltage in real-time analysis per moment controls situation, adopt the multiple target dynamic reactive power optimization method with inventive concept, realize the optimization to electrical network dynamic passive compensation control strategy, safety, the economy improving power system operation is significant.

Background technology

Reactive power optimization of power system problem is one of important content of Optimization Problems In Power Systems research.Reactive power optimization of power system, namely to ensure premised on power system voltage quality, utilizes reactive power compensation to change the whole network trend, make the meritorious loss of system and reactive power compensation expense minimum.Domestic and international researcher proposes various Reactive Power Optimization Algorithm for Tower, these methods are that Reactive Power Optimazation Problem is regarded as mathematical problem mostly, establish variable, founding mathematical models, belong to static reactive optimization, the dynamic passive compensation optimization method of real system under the system of guarantee Dynamic Voltage Stability condition is not studied.

Summary of the invention

The present invention is directed to the technical problem of above-mentioned existence, provide a kind of electrical network Dynamic reactive power optimization system and method considering part throttle characteristics.Object is from actual electric network, directly to read the data required for idle work optimization, effectively saves system hardware investment, definite reflection electrical network real-time change situation, simplifies the complexity calculated.For electrical network provides dynamic passive compensation more accurately and fast to control.

For achieving the above object, the technical solution adopted for the present invention to solve the technical problems is:

Consider the electrical network Dynamic reactive power optimization system of part throttle characteristics, wherein the hardware real-time control unit of electrical network Dynamic reactive power optimization system comprises: for gathering the load condition collector of network load performance data; The load dynamic reactive conditioning controller that load accurately sorts out completes to part throttle characteristics data analysis; The load dynamic reactive actuator of power system operation is controlled according to the optimized variable of Load Regulation controller output.Wherein, load condition collector Single port is connected to load dynamic reactive conditioning controller, gather and the network load characteristic transmission processed to load dynamic reactive controller; Load dynamic reactive controller is connected with load dynamic reactive actuator, for instructing the operation of electric power system according to the optimum results of dynamic reactive controller;

Software systems comprise actual electric network multiple target dynamic reactive control subsystem, data command transmission control interface, PSASP Load flow calculation data module, Reactive Power Control data interaction module, the analysis module considering electrical network Real-time Load voltage, the increment control algorithm pattern block considering part throttle characteristics, multiple target subregion is idle control strategy module, emergency response policy module; Wherein, PSASP Load flow calculation data module and Reactive Power Control data interaction module are transmitted by interface channel, and all the other intermodules then realize the synchronous interaction of data by shared drive data pool.

Consider the electrical network dynamic reactive power optimization method of part throttle characteristics, comprise following rate-determining steps:

Step 1: read actual electric network variable parameter data in real time from the CC2000 system of dispatching of power netwoks department;

Step 2: carry out Load flow calculation, multilayer output feedback network to electrical network, and adopt rack graph theory according to result of calculation and run hub node method, filters out participation factors is comparatively large, voltage the is lower node voltage weak node as electrical network;

Step 3: the interface channel setting up PSASP transient stability synthesizer (ST) and user interface program (UP);

Step 4: the information of voltage weak spot in transient stability synthesizer (ST) is imported idle control data interactive module;

Step 5: structure incremental type multiple-target subregion dynamic reactive control variables individual variable, initialization population;

Step 6: according to initialized individual variable population with by the Power Flow Information that interface channel is transmitted, calculate all target function values;

Step 7: the target function value calculated is carried out analyses and prediction in consideration load fluctuation incremental modular and system failure fluctuation module, a part is reflected to the load variations situation till the current control moment, calculates for ground floor Reactive power control policy generation module; Another part then reflects the fault disturbance situation of system, calculates for second layer Reactive power control policy generation module; Both are fused in decision variable the most at last, obtain incremental type multiple-target Dynamic reactive power optimization control strategy, feed back in transient stability synthesizer (ST) as final control strategy by interface channel;

Step 8: on electrical network original base, considers the idle work optimization variable that user program (UP) feeds back, and adopts implicit trapezoidal rule iteration and direct Triangle-decomposition algorithm, simultaneous solution transient stability equation;

Step 9: extract reactive load characteristic scale factor, embedded dynamic passive compensation algorithm, calculate the optimum dynamic passive compensation amount under often kind of part throttle characteristics.

Step 10: according to cc2000 voltage characteristic analysis result in conjunction with power supply, load bus type (change of Reactive Compensation in Wind Farm type, reactive requirement less type, the rapid change type of reactive requirement ladder, the irregular change of reactive requirement type, the irregular change type of reactive requirement etc. more slowly), comprehensively provide Scheme of Reactive Power Compensation;

Step 11: optimizing process terminates, exports optimum results.

Described structure incremental type multiple-target subregion dynamic reactive control variables individual variable, initialization population, is expressed as follows:

Incremental type multiple-target subregion dynamic reactive control variables is defined as:

$\left\{\begin{array}{c}{P}_{\mathrm{loss}}=\underset{k=1}{\overset{N_B}{\mathrm{\Σ}}}{G}_k(i,j)[U_i^2+U_j^2-2U_i{U}_j\cos ({\mathrm{\θ}}_i-{\mathrm{\θ}}_j)]\\ \mathrm{\ΔU}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{\left[\frac{U_i-U_i^{\mathrm{spec}}}{U_{i\max }-U_{i\min }}\right]}^2\\ M={\mathrm{\λ}}_1\underset{i=1}{\overset{N_D}{\mathrm{\Σ}}}{\left[\frac{U_i-U_{\mathrm{ilim}}}{U_{i\max }-U_{i\min }}\right]}^2+{\mathrm{\λ}}_2\underset{i=1}{\overset{N_g}{\mathrm{\Σ}}}{\left[\frac{Q_i-Q_{\mathrm{ilim}}}{Q_{i\max }-Q_{i\min }}\right]}^2\end{array}\right.---\left(10\right)$

In above formula: U _ilim, Q _ilimbe defined as:

Above-mentioned variable mathematics model explanation is as follows:

P _loss, Δ U, M represent the constrained objective functional value of active power loss, voltage deviation and penalty term, λ respectively ₁for the out-of-limit item penalty factor of node voltage amplitude; λ ₂for generator reactive power is exerted oneself out-of-limit item penalty factor, N _bfor actual electric network set of fingers; G _k(i, j) is for the i-th node on kth branch road in actual electric network is to the conductance of jth node; θ _irepresent the voltage phase angle of the i-th node in real system; θ _jrepresent the voltage phase angle of jth node in real system; for the rated voltage of the i-th node in real system; U _imaxthe voltage representing real system i-th node crosses the border the upper limit; U _iminthe voltage representing real system i-th node crosses the border lower limit; N _dfor the load bus set that voltage in real system crosses the border; N _gfor real system reactive power is exerted oneself the generator node set of crossing the border; Q _irepresent that the reactive power of real system i-th node is exerted oneself; Q _iminrepresent the idle lower limit that crosses the border of exerting oneself of real system i-th node; Q _imaxrepresent the idle upper limit of crossing the border of exerting oneself of real system i-th node.

Described step 5: structure incremental type multiple-target subregion dynamic reactive control variables individual variable, initialization population;

That incremental type multiple-target subregion dynamic reactive control variables is defined as:

$\left\{\begin{array}{c}{P}_{\mathrm{loss}}=\underset{k=1}{\overset{N_B}{\mathrm{\Σ}}}{G}_k(i,j)[U_i^2+U_j^2-2U_i{U}_j\cos ({\mathrm{\θ}}_i-{\mathrm{\θ}}_j)]\\ \mathrm{\ΔU}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{\left[\frac{U_i-U_i^{\mathrm{spec}}}{U_{i\max }-U_{i\min }}\right]}^2\\ M={\mathrm{\λ}}_1\underset{i=1}{\overset{N_D}{\mathrm{\Σ}}}{\left[\frac{U_i-U_{\mathrm{ilim}}}{U_{i\max }-U_{i\min }}\right]}^2+{\mathrm{\λ}}_2\underset{i=1}{\overset{N_g}{\mathrm{\Σ}}}{\left[\frac{Q_i-Q_{\mathrm{ilim}}}{Q_{i\max }-Q_{i\min }}\right]}^2\end{array}\right.---\left(10\right)$

In above formula: U _ilim, Q _ilimbe defined as:

Above-mentioned variable mathematics model explanation is as follows:

P _loss, Δ U, M represent the constrained objective functional value of active power loss, voltage deviation and penalty term, λ respectively ₁for the out-of-limit item penalty factor of node voltage amplitude; λ ₂for generator reactive power is exerted oneself out-of-limit item penalty factor, N _bfor actual electric network set of fingers; G _k(i, j) is for the i-th node on kth branch road in actual electric network is to the conductance of jth node; θ _irepresent the voltage phase angle of the i-th node in real system; θ _jrepresent the voltage phase angle of jth node in real system; for the rated voltage of the i-th node in real system; U _imaxthe voltage representing real system i-th node crosses the border the upper limit; U _iminthe voltage representing real system i-th node crosses the border lower limit; N _dfor the load bus set that voltage in real system crosses the border; N _gfor real system reactive power is exerted oneself the generator node set of crossing the border; Q _irepresent that the reactive power of real system i-th node is exerted oneself; Q _iminrepresent the idle lower limit that crosses the border of exerting oneself of real system i-th node; Q _imaxrepresent the idle upper limit of crossing the border of exerting oneself of real system i-th node.

Described extraction reactive load characteristic scale factor, is embedded dynamic passive compensation algorithm, is calculated the optimum dynamic passive compensation controlled quentity controlled variable under often kind of part throttle characteristics; Be expressed as follows:

According to the real-time dynamic passive compensation amount of electrical network that user program (UP) feeds back, adopt Prony algorithm matching load voltage cycle of oscillation, extract reactive load characteristic scale factor, embedded dynamic passive compensation algorithm, provided the optimum dynamic passive compensation control strategy under often kind of part throttle characteristics;

Step 9.1:SVC application is analyzed;

An application of SVC is power distribution network, for meeting power load to fast-changing reactive power demand.Large and the occasion of frequent variations of those reactive requirement, sometimes along with the generation of harmonic current, require SVC quick adjustment export idle while, possess harmonic current filtering or inhibitory action.As arc furnace, the various milling train of smelting industry, the mine hoist of mining industry, the large-scale gate elevator at harbour, the traction change etc. of electric railway all needs to install SVC for improving power supply network quality, improves the quality of products; The Another Application field of SVC is power transmission network, for regulating network system impedance, improves the stability of system cloud gray model;

Step 9.2:SVG application is analyzed;

From achievement in research both domestic and external and application experience, SVG, as the dynamic reactive compensation device of a kind of advanced person, is applied to the effect that power transmission network can play following several respects:

(1) when system jam, dynamically provide voltage support, guarantee the stability of busbar voltage, improve electric power system transient stability level, reduce low pressure release load quantity, and prevent because transient voltage collapses the pernicious power outage of large area caused;

(2) dynamically maintain transmission line terminal voltage, improve transmission line stable state transmission power limit (the idle output of every kvar about can improve the transient stability limit value of 0.5 ~ 0.7kW), improve alternating current-direct current remote conveying power;

(3) suppress system overvoltage, improve system voltage stabilizes;

(4) damping power oscillation of power system;

In addition, the SVG being applied to the lower distribution network load side of electric pressure (is commonly referred to Distribution SVG, be called for short DSVG) can realize suppressing voltage flicker, compensate load unbalanced, improve power factor, improve the functions such as the quality of power supply, in industry acquisition extensive uses such as metallurgy, electric iron;

Step 9.3:SVC application is analyzed.

Described step 1: read actual electric network variable parameter data in real time from the CC2000 system of dispatching of power netwoks department; Comprise the following steps:

Step 1.1: what the variable parameter data of described actual electric network comprised electricity grid network framework, branch parameters information, each node generator and load meritoriously exerts oneself, the position of transformer voltage ratio, generator terminal voltage, reactive-load compensation equipment and capacity and control variables used, state variable constraints;

Step 1.2: in the actual motion of electrical network, the characteristic of conventional load, power supply and grid structure describes the operational mode of electrical network;

Specifically be expressed as follows:

1. the power system operating mode described by part throttle characteristics comprises: peak load, waist lotus, Gu He;

2. the power system operating mode described by power supply characteristic comprises: a. water power: dry season, wet season; B. thermoelectricity: heating period, non-heating period; C. wind-powered electricity generation: wind-powered electricity generation is sent out greatly, little of wind-powered electricity generation;

3. comprise by the power system operating mode of grid structure characteristic description: normal operating mode, fault and maintenance mode;

The operational mode of described electrical network is: (1) peak load, dry season, heating period, little of wind-powered electricity generation; (2) peak load, wet season, non-heating period, wind-powered electricity generation are sent out greatly; (3) waist lotus, dry season, heating period, little of wind-powered electricity generation.

Described rack Graph Analysis is for being interpreted as: comprehensive analyze real system network architecture, assert that the node that single-ended power node and system wiring are less than 2 is line voltage weak node; Described operation hub node is interpreted as: in artificial identification real system, the 220kV node of all 500kV nodes and electrical network end is for running hub node, and is manually determined as electric network reactive compensation both candidate nodes.

The invention has the beneficial effects as follows:

The present invention is based on the multiple target Dynamic reactive power optimization system and method for actual electric network, along with improving constantly of automaticity in actual electric network, Dynamic reactive power optimization controls the concern being more and more subject to people.The present invention is by setting up the interface channel between PSASP transient stability program (ST) and user program (UP), the data required for transient stability analysis are read in real time from actual electric network, rack graph theory is adopted to filter out line voltage weak node with operation hub node method innovatively, and extract the characteristic variable of the factor such as network failure and load fluctuation, eventually through being programmed in UP program, this weak node is comprehensively solved, the dynamic passive compensation amount that the system that provides needs in real time.On this basis, build part throttle characteristics module and actual electric network load voltage analysis module respectively, the different reactive requirement characteristic of simulation actual electric network and real-time voltage situation, the final Reactive Power Control strategy generating optimization, to reach real-time, accurately carry out the object of reactive power compensation, for electrical power system dynamic reactive power optimizes the theory analysis foundation that field provides science, the transient stability analysis set up and the interface channel of user program and consider the multilayer output feedback network method of user program feedback variable, for electrical network is more accurate, dynamic passive compensation opens inventive concept efficiently.In electrical network actual motion, set up target function and boundary condition to the economy of electrical network, stable operation, by solving optimum dynamic passive compensation amount, formation control scheme carries out the control of electrical network dynamic passive compensation, effectively achieves electrical network economy, rationally runs.

The present invention, owing to directly can read the data required for idle work optimization from actual electric network, saves system hardware investment effectively; Be extracted the characteristic variable of the factor such as part throttle characteristics and load voltage fluctuation, the more definite electrical network real-time change situation that reflects; Multiple target wattles power economic equivalent control strategy generation module, simplifies the complexity of calculating effectively.Provide strong scientific theory to the dynamic passive compensation field in future to support, with minimum reactive power compensation amount, realize the dynamic passive compensation of electrical network, thus create huge economic benefit.

Below in conjunction with the drawings and specific embodiments, the present invention is further detailed explanation.

Accompanying drawing explanation

Fig. 1 is target grid Substation Bus Arrangement figure in prior art;

Fig. 2 is actual electric network multiple target Dynamic reactive power optimization system flow chart in the present invention;

Fig. 3 is busbar voltage when not putting into operation SVG in the present invention;

Fig. 4 is busbar voltage when putting into operation SVG in the present invention;

Fig. 5 is the catenation principle of ST and UP in the present invention;

Fig. 6 is structural representation of the present invention.

Embodiment

Embodiment 1:

The present invention is a kind of electrical network Dynamic reactive power optimization system and method considering part throttle characteristics, and wherein the hardware real-time control unit of electrical network Dynamic reactive power optimization system comprises: for gathering the load condition collector of network load performance data; The load dynamic reactive conditioning controller that load accurately sorts out completes to part throttle characteristics data analysis; The load dynamic reactive actuator of power system operation is controlled according to the optimized variable of Load Regulation controller output.Wherein, load condition collector Single port is connected to load dynamic reactive conditioning controller, gather and the network load characteristic transmission processed to load dynamic reactive controller; Load dynamic reactive controller is connected with load dynamic reactive actuator, for instructing the operation of electric power system according to the optimum results of dynamic reactive controller, as shown in Figure 6.

Total system software section of the present invention comprises actual electric network multiple target dynamic reactive control subsystem, data command transmission control interface, PSASP Load flow calculation data module, Reactive Power Control data interaction module, the analysis module considering electrical network Real-time Load voltage, the increment control algorithm pattern block considering part throttle characteristics, multiple target subregion is idle control strategy module, emergency response policy module.Wherein, PSASP Load flow calculation data module and Reactive Power Control data interaction module are transmitted by interface channel, and all the other intermodules then realize the synchronous interaction of data by shared drive data pool.

Consider the electrical network dynamic reactive power optimization method of part throttle characteristics, comprise the steps:

Step 1: read actual electric network variable parameter data in real time from the CC2000 system of dispatching of power netwoks department;

Step 1.1: what the variable parameter data of described actual electric network comprised electricity grid network framework, branch parameters information, each node generator and load meritoriously exerts oneself, the position of transformer voltage ratio, generator terminal voltage, reactive-load compensation equipment and capacity and control variables used, state variable constraints.

Step 1.2: in the actual motion of electrical network, the characteristic of conventional load, power supply and grid structure describes the operational mode of electrical network.Specifically be expressed as follows:

1. the power system operating mode described by part throttle characteristics comprises: peak load, waist lotus, Gu He;

2. the power system operating mode described by power supply characteristic comprises: a. water power: dry season, wet season

B. thermoelectricity: heating period, non-heating period

C. wind-powered electricity generation: wind-powered electricity generation is sent out greatly, little of wind-powered electricity generation

3. comprise by the power system operating mode of grid structure characteristic description: normal operating mode, fault and maintenance mode.

Three kinds of typical operation modes of electrical network are chosen in the present invention:

1. peak load, dry season, heating period, little of wind-powered electricity generation

2. peak load, wet season, non-heating period, wind-powered electricity generation are sent out greatly

3. waist lotus, dry season, heating period, little of wind-powered electricity generation

Step 2: carry out Load flow calculation, multilayer output feedback network to electrical network, and adopt rack graph theory according to result of calculation and run hub node method, filters out participation factors is comparatively large, voltage the is lower node voltage weak node as electrical network;

The specific explanations of this step is as follows:

Rack Graph Analysis is for being interpreted as: comprehensive analyze real system network architecture, assert that the node that single-ended power node and system wiring are less than 2 is line voltage weak node;

Operation hub node is interpreted as: in artificial identification real system, the 220kV node of all 500kV nodes and electrical network end is for running hub node, and is manually determined as electric network reactive compensation both candidate nodes.

Step 3: the interface channel setting up PSASP transient stability synthesizer (ST) and user interface program (UP);

The interface principle of transient stability program (ST) and user interface program (UP) passage is:

When not setting up transient stability program (ST) and user program (UP) passage, the number sequence model of PSASP multilayer output feedback network (ST) can be summarized as following three parts.

1. the Mathematical Modeling of electrical network, i.e. network equation:

X=F(X，Y) (1)

Wherein,

F=(f ₁，f ₂，...，f _n) ^T(2)

X=(x ₁, x ₂..., x _n) ^tfor the variable that network equation solves.

2. the Mathematical Modeling of the primary equipment such as generator, load secondary automatics, i.e. the differential equation:

Y=G(X，Y) (3)

Wherein,

F=(f ₁，f ₂，...，f _n) ^T(4)

X=(x ₁, x ₂.., x _n) ^tfor the variable that network equation solves.

G=(g ₁，g ₂，...，g _n) (5)

Y=(y ₁, y ₂..., y _n) ^tfor the variable of differential equation

3. the simulation of perturbation scheme and stabilizing measures, as electrical network simple fault or complex fault and impact load, quick closing valve valve, cut machine, cutting load, tangent line road etc.The effect of these factors changes X, Y.

After setting up transient stability program (ST) and user program (UP) passage, above-mentioned transient stability Mathematical Modeling should consider variable parameter U in user program, then the Mathematical Modeling of formula (1), formula (2) and user program is as follows:

X=F(X，Y,U) (6)

Y=G(X，Y,U) (7)

U=H(X，Y,U) (8)

Wherein:

H=(h ₁，h ₂，...，h _n) ^T(9)

U=(u ₁, u ₂..., u _l) be the variable of user's equation solution.

In multilayer output feedback network, the solution procedure of its differential equation is step integration, and namely t will obtain X each period _t, Y _t, its integration step is Δ t.Therefore, between ST and UP, each period alternately performs once, and be illustrated in fig. 5 shown below, Fig. 5 is the catenation principle of ST and UP.UP in Fig. 5 can be multiple, and now their implementation is for walking, and after namely all UP are complete, then returns ST.

Step 4: the information of voltage weak spot in transient stability synthesizer (ST) is imported idle work optimization data interaction module;

Step 5: structure incremental type multiple-target subregion dynamic reactive control variables individual variable, initialization population;

Incremental type multiple-target subregion dynamic reactive control variables is defined as:

$\left\{\begin{array}{c}{P}_{\mathrm{loss}}=\underset{k=1}{\overset{N_B}{\mathrm{\Σ}}}{G}_k(i,j)[U_i^2+U_j^2-2U_i{U}_j\cos ({\mathrm{\θ}}_i-{\mathrm{\θ}}_j)]\\ \mathrm{\ΔU}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{\left[\frac{U_i-U_i^{\mathrm{spec}}}{U_{i\max }-U_{i\min }}\right]}^2\\ M={\mathrm{\λ}}_1\underset{i=1}{\overset{N_D}{\mathrm{\Σ}}}{\left[\frac{U_i-U_{\mathrm{ilim}}}{U_{i\max }-U_{i\min }}\right]}^2+{\mathrm{\λ}}_2\underset{i=1}{\overset{N_g}{\mathrm{\Σ}}}{\left[\frac{Q_i-Q_{\mathrm{ilim}}}{Q_{i\max }-Q_{i\min }}\right]}^2\end{array}\right.---\left(10\right)$

In above formula: U _ilim, Q _ilimbe defined as:

Above-mentioned variable mathematics model explanation is as follows:

P _loss, Δ U, M represent the constrained objective functional value of active power loss, voltage deviation and penalty term, λ respectively ₁for the out-of-limit item penalty factor of node voltage amplitude; λ ₂for generator reactive power is exerted oneself out-of-limit item penalty factor, N _bfor actual electric network set of fingers; G _k(i, j) is for the i-th node on kth branch road in actual electric network is to the conductance of jth node; θ _irepresent the voltage phase angle of the i-th node in real system; θ _jrepresent the voltage phase angle of jth node in real system; for the rated voltage of the i-th node in real system; U _imaxthe voltage representing real system i-th node crosses the border the upper limit; U _iminthe voltage representing real system i-th node crosses the border lower limit; N _dfor the load bus set that voltage in real system crosses the border; N _gfor real system reactive power is exerted oneself the generator node set of crossing the border; Q _irepresent that the reactive power of real system i-th node is exerted oneself; Q _iminrepresent the idle lower limit that crosses the border of exerting oneself of real system i-th node; Q _imaxrepresent the idle upper limit of crossing the border of exerting oneself of real system i-th node.

Step 6: according to initialized individual variable population with by the Power Flow Information that interface channel is transmitted, calculate all target function values;

Step 7: the target function value calculated is carried out analyses and prediction in consideration load fluctuation incremental modular and system failure fluctuation module, a part is reflected to the load variations situation till the current control moment, calculates for ground floor Reactive power control policy generation module; Another part then reflects the fault disturbance situation of system, calculates for second layer Reactive power control policy generation module.Both are fused in decision variable the most at last, obtain incremental type multiple-target Dynamic reactive power optimization control strategy, feed back in transient stability synthesizer (ST) as final control strategy by interface channel;

Step 8: on electrical network original base, considers the idle work optimization variable that user program (UP) feeds back, and adopts implicit trapezoidal rule iteration and direct Triangle-decomposition algorithm, simultaneous solution transient stability equation;

Step 9: extract reactive load characteristic scale factor, embedded dynamic passive compensation algorithm, calculate the optimum dynamic passive compensation amount under often kind of part throttle characteristics.

According to the real-time dynamic passive compensation amount of electrical network that user program (UP) feeds back, adopt Prony algorithm matching load voltage cycle of oscillation, extract reactive load characteristic scale factor, embedded dynamic passive compensation algorithm, provided the optimum dynamic passive compensation control strategy under often kind of part throttle characteristics.

Step 9.1:SVC application is analyzed.

An application of SVC is power distribution network, for meeting power load to fast-changing reactive power demand.Large and the occasion of frequent variations of those reactive requirement, sometimes along with the generation of harmonic current, require SVC quick adjustment export idle while, possess harmonic current filtering or inhibitory action.As arc furnace, the various milling train of smelting industry, the mine hoist of mining industry, the large-scale gate elevator at harbour, the traction change etc. of electric railway all needs to install SVC for improving power supply network quality, improves the quality of products; The Another Application field of SVC is power transmission network, for regulating network system impedance, improves the stability of system cloud gray model.

Step 9.2:SVG application is analyzed.

From achievement in research both domestic and external and application experience, SVG, as the dynamic reactive compensation device of a kind of advanced person, is applied to the effect that power transmission network can play following several respects:

(1) when system jam, dynamically provide voltage support, guarantee the stability of busbar voltage, improve electric power system transient stability level, reduce low pressure release load quantity, and prevent because transient voltage collapses the pernicious power outage of large area caused.

(2) dynamically maintain transmission line terminal voltage, improve transmission line stable state transmission power limit (the idle output of every kVar about can improve the transient stability limit value of 0.5 ~ 0.7kW), improve alternating current-direct current remote conveying power.

(3) suppress system overvoltage, improve system voltage stabilizes.

(4) damping power oscillation of power system.

In addition, the SVG being applied to the lower distribution network load side of electric pressure (is commonly referred to Distribution SVG, be called for short DSVG) can realize suppressing voltage flicker, compensate load unbalanced, improve power factor, improve the functions such as the quality of power supply, in industry acquisition extensive uses such as metallurgy, electric iron;

Step 9.3:SVC application is analyzed, and refers to table 1.

Step 10: according to cc2000 voltage characteristic analysis result in conjunction with power supply, load bus type (change of Reactive Compensation in Wind Farm type, reactive requirement less type, the rapid change type of reactive requirement ladder, the irregular change of reactive requirement type, the irregular change type of reactive requirement etc. more slowly), comprehensively provide Scheme of Reactive Power Compensation, wherein reactive-load compensation equipment is chosen by following principle:

1) select good economy performance, operating experience maturation for the load that idle change demand is less, static compensation characteristic divides into groups fixed capacitor compensation preferably;

2) for the SVC of the stepped vertiginous load of reactive requirement, the irregular change of the reactive requirement load point that load, response time requirement are not high more slowly selection better economy;

3) higher for the irregular vertiginous power load of reactive requirement, response time requirement or need to improve transmission line stable state transmission power limit, suppress system overvoltage, improve system voltage stabilizes, the website of damping power oscillation of power system selects the good SVG of transient characterisitics.

The specific explanations of this step is: the real-time dynamic passive compensation amount of electrical network fed back according to user program (UP), adopt Prony algorithm matching load voltage cycle of oscillation, extract reactive load characteristic scale factor, embedded dynamic passive compensation algorithm, provided the optimum dynamic passive compensation control strategy under often kind of part throttle characteristics.Refer to table 2.

Step 11: optimizing process terminates, exports optimum results.

Embodiment 2:

Below in conjunction with Fig. 1-Fig. 4, specific embodiment of the invention is described further.It is emphasized that following explanation is only exemplary, instead of in order to limit the scope of the invention and apply.

In present embodiment, with Anshan electrical network for goal in research electrical network.Anshan electrical network main conditions are: Xiuyan Pian Ling 66kV electric substation of Anshan power supply administration provides 2 66kV inlet wires by higher level, two sections of 10kV buses are reduced to through two main transformers (1# main transformer capacity is 16MVA, 2# main transformer capacity is 20MVA), 10kV bus mother connects closed operation, for subordinate load is powered.

To the optimization method of the multiobject dynamic reactive control strategy of above-mentioned consideration, comprise the steps:

Step 1: read actual electric network variable parameter data in real time from the CC2000 system of dispatching of power netwoks department;

Step 2: carry out Load flow calculation, multilayer output feedback network to Anshan electrical network, and adopt rack graph theory according to result of calculation and run hub node method, filters out participation factors is comparatively large, voltage the is lower node voltage weak node as electrical network;

Step 3: the interface channel setting up PSASP transient stability synthesizer (ST) and user interface program (UP);

Step 4: the Power Flow Information of voltage weak spot in transient stability synthesizer (ST) is imported idle control data interactive module;

Step 5: structure incremental type multiple-target subregion Dynamic reactive power optimization controls individual variable, sets up multiple target Dynamic reactive power optimization model.Machine-processed according to the Refresh Data of Operation system setting by the master control entrance of this control system, judge whether system carries out data interaction with idle control data interactive module.

Step 6: by idle control module, utilizes data-interface to gather desired data, and calculates all target function values;

Step 7: the target function value calculated is carried out analyses and prediction in consideration load fluctuation incremental modular and system failure fluctuation module, a part is reflected to the load variations situation till the current control moment, calculates for ground floor Reactive power control policy generation module; Another part then reflects the fault disturbance situation of system, calculates for second layer Reactive power control policy generation module.Both are fused in decision variable the most at last, obtain incremental type multiple-target Dynamic reactive power optimization control strategy, feed back in transient stability synthesizer (ST) as final control strategy by interface channel;

Actual load changes comparatively violent within 5 periods of 9:00-14:00, and therefore in this period, the operating frequency of control appliance is higher.Adopt within this period and there is better dynamic response characteristic, the SVG of faster response time, and each period carries out dynamic passive compensation amount to adopt INTEGRAL THEOREM OF MEAN to determine.

Step 8: on electrical network original base, considers the idle work optimization variable that user program (UP) feeds back, by solving the Optimal Control Strategy of the dynamic reactive drawing this target grid.In systems in practice, have employed the Dynamic reactive power optimization control strategy that the present invention proposes, its actual test result is:

(1) 66kV busbar voltage test result

Busbar voltage resultant distortion rate

Before SVC puts into operation:

66kV busbar voltage AB phase voltage resultant distortion rate maximum is the large value of 0.85%, 95% probability is 0.75%; CB phase voltage resultant distortion rate maximum is the large value of 0.86%, 95% probability is 0.75%;

After SVC puts into operation:

66kV busbar voltage AB phase voltage resultant distortion rate maximum is the large value of 0.85%, 95% probability is 0.76%; CB phase voltage resultant distortion rate maximum is the large value of 0.90%, 95% probability is 0.79%;

Before SVC puts into operation (AB phase voltage):

2 subharmonic voltage containing ratios are 0.02%, 3 subharmonic voltage containing ratios be 0.26%, 5 subharmonic voltage containing ratios be 0.38%, 7 subharmonic voltage containing ratios be 0.47%, 11 subharmonic voltage containing ratios is 0.38%;

After SVC puts into operation (AB phase voltage):

2 subharmonic voltage containing ratios are 0.08%, 3 subharmonic voltage containing ratios be 0.51%, 5 subharmonic voltage containing ratios be 0.77%, 7 subharmonic voltage containing ratios be 0.49%, 11 subharmonic voltage containing ratios is 0.33%;

(2) 1# main transformer secondary side harmonic current test result

Before SVC puts into operation

A phase current: fundamental current value 1320.22A, 2 subharmonic currents are 0.6A, 3 subharmonic currents are 4.2A, 5 subharmonic currents are 8.5A, 7 subharmonic currents are 6.3A, 11 subharmonic currents are 2.2A;

C phase current: fundamental current value 1299.3A, 2 subharmonic currents are 0.5A, 3 subharmonic currents are 9.8A, 5 subharmonic currents are 9.0A, 7 subharmonic currents are 5.3A, 11 subharmonic currents are 2.3A;

After SVC puts into operation

A phase current: fundamental current value 1258.5A, 2 subharmonic currents are 4.8A (even existing), 3 subharmonic currents are 12.7A, 5 subharmonic currents are 9.8A, 7 subharmonic currents are 5.2A, 11 subharmonic currents are 2.1A.

C phase current: fundamental current value 1243.82 subharmonic current is 6.8A, 3 subharmonic currents are 14.0A, and 5 subharmonic currents are 9.5A, and 7 subharmonic currents are 5.1A, and 11 subharmonic currents are 2.2A.

(3) SVC branch road harmonic current test result

A phase current: fundamental current value 173.9A, 2 subharmonic currents are 7.0A (mainly appearing at the moment that MCR drops into and exits), 3 subharmonic currents are 10.1A, 5 subharmonic currents are 6.5A, 7 subharmonic currents are 3.3A, 11 subharmonic currents are 1.3A;

C phase current: fundamental current value 183.2A, 2 subharmonic currents are 7.6A (mainly appearing at the moment that MCR drops into and exits), and 3 subharmonic currents are 4.3A, and 5 subharmonic currents are 6.7A, and 7 subharmonic currents are 3.3A, and 11 subharmonic currents are 1.3A.

Test result: the resultant distortion rate of 66kV busbar voltage increases to some extent after SVC puts into operation viewed from test result, voltage resultant distortion is far below 3% limits value of national regulations.What in harmonic voltage, 3,5 subharmonic voltages increased is comparatively obvious, and each odd harmonic before and after SVC puts into operation and the content of even-order harmonic also meet the requirements prescribed; From the test result of 1# Circuit Fault on Secondary Transformer load current, the ratio of 1# main transformer secondary side harmonic current before SVC puts into operation shared by 3,5,7 subharmonic current content is bigger, after SVC puts into operation, 2,3,5 subharmonic current content increase to some extent, and wherein 2 subharmonic currents mainly appear at the moment that SVC drops into and exits; Individual harmonic current value be all less than by minimum capacity of short circuit be 1168.2MVA conversion after national standard limit value.In sum, the dynamic reactive control strategy drawn by the present invention is far superior to control strategy in the past, achieves huge economic benefit.Table 1,50 ~+150Mvar mix SVG and SVC and compare

Table 2:50 ~+150Mvar mixes SVG and SVC and compares

Claims (6)

1. consider the electrical network dynamic reactive power optimization method of part throttle characteristics, it is characterized in that: comprise following rate-determining steps:

Step 1: read actual electric network variable parameter data in real time from the CC2000 system of dispatching of power netwoks department;

Step 2: carry out Load flow calculation, multilayer output feedback network to electrical network, and adopt rack graph theory according to result of calculation and run hub node method, filters out participation factors is comparatively large, voltage the is lower node voltage weak node as electrical network;

Step 3: the interface channel setting up PSASP transient stability synthesizer (ST) and user interface program (UP);

Step 4: the information of voltage weak spot in transient stability synthesizer (ST) is imported idle control data interactive module;

Step 5: structure incremental type multiple-target subregion dynamic reactive control variables individual variable, initialization population;

Step 6: according to initialized individual variable population with by the Power Flow Information that interface channel is transmitted, calculate all target function values;

Step 7: the target function value calculated is carried out analyses and prediction in consideration load fluctuation incremental modular and system failure fluctuation module, a part is reflected to the load variations situation till the current control moment, calculates for ground floor Reactive power control policy generation module; Another part then reflects the fault disturbance situation of system, calculates for second layer Reactive power control policy generation module; Both are fused in decision variable the most at last, obtain incremental type multiple-target Dynamic reactive power optimization control strategy, feed back in transient stability synthesizer (ST) as final control strategy by interface channel;

Step 8: on electrical network original base, considers the idle work optimization variable that user program (UP) feeds back, and adopts implicit trapezoidal rule iteration and direct Triangle-decomposition algorithm, simultaneous solution transient stability equation;

Step 9: extract reactive load characteristic scale factor, embedded dynamic passive compensation algorithm, calculate the optimum dynamic passive compensation amount under often kind of part throttle characteristics;

Step 10: according to cc2000 voltage characteristic analysis result in conjunction with power supply, load bus type, load bus type comprises Reactive Compensation in Wind Farm type, reactive requirement change less type, the rapid change type of reactive requirement ladder, the irregular change of reactive requirement type, the irregular change type of reactive requirement more slowly, comprehensively provides Scheme of Reactive Power Compensation;

Step 11: optimizing process terminates, exports optimum results.

2. the electrical network dynamic reactive power optimization method of consideration part throttle characteristics according to claim 1, is characterized in that: described structure incremental type multiple-target subregion dynamic reactive control variables individual variable, and initialization population, is expressed as follows:

Incremental type multiple-target subregion dynamic reactive control variables is defined as:

（10）

In above formula: , be defined as:

（11）

（12）

Above-mentioned variable mathematics model explanation is as follows:

, , represent the constrained objective functional value of active power loss, voltage deviation and penalty term respectively, for the out-of-limit item penalty factor of node voltage amplitude; for generator reactive power is exerted oneself out-of-limit item penalty factor, for actual electric network set of fingers; for the i-th node on kth branch road in actual electric network is to the conductance of jth node; represent the voltage phase angle of the i-th node in real system; represent the voltage phase angle of jth node in real system; for the rated voltage of the i-th node in real system; the voltage representing real system i-th node crosses the border the upper limit; the voltage representing real system i-th node crosses the border lower limit; for the load bus set that voltage in real system crosses the border; for real system reactive power is exerted oneself the generator node set of crossing the border; represent that the reactive power of real system i-th node is exerted oneself; represent the idle lower limit that crosses the border of exerting oneself of real system i-th node; represent the idle upper limit of crossing the border of exerting oneself of real system i-th node.

3. the electrical network dynamic reactive power optimization method of consideration part throttle characteristics according to claim 1, it is characterized in that: described extraction reactive load characteristic scale factor, embedded dynamic passive compensation algorithm, calculated the optimum dynamic passive compensation controlled quentity controlled variable under often kind of part throttle characteristics; Be expressed as follows:

According to the real-time dynamic passive compensation amount of electrical network that user program (UP) feeds back, adopt Prony algorithm matching load voltage cycle of oscillation, extract reactive load characteristic scale factor, embedded dynamic passive compensation algorithm, provide the optimum dynamic passive compensation control strategy under often kind of part throttle characteristics.

4. the electrical network dynamic reactive power optimization method of consideration part throttle characteristics according to claim 1, is characterized in that: described step 1: from the CC2000 system of dispatching of power netwoks department, read actual electric network variable parameter data in real time; Comprise the following steps:

Step 1.1: what the variable parameter data of described actual electric network comprised electricity grid network framework, branch parameters information, each node generator and load meritoriously exerts oneself, the position of transformer voltage ratio, generator terminal voltage, reactive-load compensation equipment and capacity and control variables used, state variable constraints;

Step 1.2: in the actual motion of electrical network, describes the operational mode of electrical network by the characteristic of load, power supply and grid structure;

Specifically be expressed as follows:

the power system operating mode described by part throttle characteristics comprises: peak load, waist lotus, Gu He;

the power system operating mode described by power supply characteristic comprises: a. water power: dry season, wet season; B. thermoelectricity: heating period, non-heating period; C. wind-powered electricity generation: wind-powered electricity generation is sent out greatly, little of wind-powered electricity generation;

comprise by the power system operating mode of grid structure characteristic description: normal operating mode, fault and maintenance mode.

5. the electrical network dynamic reactive power optimization method of consideration part throttle characteristics according to claim 4, is characterized in that: the operational mode of described electrical network is: (1) peak load, dry season, heating period, little of wind-powered electricity generation; (2) peak load, wet season, non-heating period, wind-powered electricity generation are sent out greatly; (3) waist lotus, dry season, heating period, little of wind-powered electricity generation.

6. the electrical network dynamic reactive power optimization method of consideration part throttle characteristics according to claim 1, is characterized in that: described

Rack Graph Analysis is for being interpreted as: comprehensive analyze real system network architecture, assert that the node that single-ended power node and system wiring are less than 2 is line voltage weak node;

Described operation hub node is interpreted as: in artificial identification real system, the 220kV node of all 500kV nodes and electrical network end is for running hub node, and is manually determined as electric network reactive compensation both candidate nodes.