CN105006843A - Multi-time-scale flexible load scheduling method for handling wind power uncertainties - Google Patents

Abstract

The invention relates to a multi-time-scale flexible load scheduling method for handling wind power uncertainties. The method comprises the following steps: a scheduling center predicting a power system load and wind power generation on different time scales; the scheduling center establishing a wind power predication uncertainty model, making a thermal power/hydropower set scheduling plan and releasing power system operation information and flexible load scheduling need information; load agents, according to response characteristics of different types of flexible controllable loads, and based on a multi-agent technology, marking quotation models facilitating their own benefits for reporting to the scheduling center; the scheduling center, according to schedulable capabilities and quotation information reported by the load agents, carrying out optimization scheduling on schedulable load resources of the multiple load agents, and sending load adjusting instructions and final compensation prices to the load agents; and the load agents adjusting the electricity power of managed loads through an electricity price mechanism or a stimulation mechanism. According to the invention, the method enriches the scheduling modes for the wind power uncertainties and enhances the adjusting capability of a power network.

Description

A kind of reply wind-powered electricity generation probabilistic Multiple Time Scales flexible load dispatching method

Technical field

The present invention relates to a kind of intelligent grid power system dispatching and run control technology, be specifically related to a kind of reply wind-powered electricity generation probabilistic Multiple Time Scales flexible load dispatching method.

Background technology

Because the regenerative resources such as wind-powered electricity generation self have the feature of " unfriendly " such as fluctuation, intermittence, anti-peak regulation, low schedulabilities, challenge is proposed to the dispatching of power netwoks mode of traditional " generating follow load ".Power supply, between electrical network and load three, coordination and interaction should be carried out, not only be conducive to the energy and the power dynamic equilibrium ability that improve electric power system, also being conducive to the lifting realizing bulk power grid most optimum distribution of resources and comprehensive utilization rate of energy source, is the important development direction of intelligent grid.

Electrical network gathers and there is sub-load, its power consumption can in designation area in " stretching " or shift between Different periods, flexible load had both comprised the traditional load such as air-conditioning, refrigerator in industrial load, Commercial Load and the resident living load in power consumer, also comprised the two-way controllable burden such as energy storage, electric automobile.Utilize power flexible load to balance the fluctuation of batch (-type) regenerative resource, existing certain research and Preliminary Practice at present, but also need the problem of solution two aspects, one is time dimension, different time dimension predicated error is adapted to, regulate the difference of scope of resource and cost thereof.Two is Object Dimension, adapt to the otherness of load when participating in dispatching of power netwoks and running of demand response project of different nature and different qualities.

Summary of the invention

For the deficiencies in the prior art, the object of this invention is to provide a kind of reply wind-powered electricity generation probabilistic Multiple Time Scales flexible load dispatching method, on the one hand directly act on behalf of flexible controllable burden in compass of competency to multiple load carries out the joint optimal operation of Multiple Time Scales coordination, to improve the receiving ability of wind-powered electricity generation to the method taking into account on wind-powered electricity generation predicated error basis; On the other hand, based on multi-agent technology, carry out cooperation control by the dissimilar flexible load of load agency to wide area distribution.

The object of the invention is to adopt following technical proposals to realize:

The invention provides a kind of reply wind-powered electricity generation probabilistic Multiple Time Scales flexible load dispatching method, its improvements are, described method adopts Multiple Time Scales to coordinate, and described method comprises the steps:

1) control centre predicts power system load and wind power generation on Different time scales;

2) on Different time scales, control centre sets up wind power prediction uncertainty models, formulates conventional fire/Hydropower Unit operation plan, announces power system operation information and flexible load dispatching requirement information;

3) load agency is according to the response characteristic of dissimilar flexible controllable burden, analyze and coordinate to arrange 24 hours a few days ago, the controlled variable of flexible load in compass of competency in a few days 1 hour, in a few days 15 minutes and real-time time yardstick, flexible load dispatching requirement information, power system operation information and historical transactional information are learnt, the Offer Model being conducive to self benefits is formulated based on multi-agent technology, and reporting scheduling center;

4) the schedulable ability and quotation information that report are acted on behalf of by control centre according to load, minimum for target with control centre's scheduling cost, scheduling is optimized to the schedulable burdened resource that multiple load is acted on behalf of, and load adjustment instruction and final making up price are sent to load agency;

5), after load agency obtains final dispatch command, minimum for target with load scheduling agent cost, by Price Mechanisms or incentive mechanism, the electric power to institute's administrative loads adjusts.

Further, in described step 1), the Different time scales of flexible load scheduling comprises 24 hours a few days ago, compass of competency in a few days 1 hour, in a few days 15min and real-time time yardstick;

A, a few days ago 24 hour load scheduling, within every 24 hours, perform once, be divided into the power adjustment of 96 periods to following one day load agency to make plan, its control object is the flexible load that response speed is slow, advance notification times is long, comprises the industrial load of iron and steel and non-ferrous metals processing;

B, in a few days 1 hour load scheduling, within every 1 hour, perform once, on the basis taking into account Load Regulation amount a few days ago, plan is made to the power adjustment of following 1 hour load agency, scheduler object is the load of short, the fast response time of regulating cycle in load agency, comprises the illumination in business and communal facility and air conditioner load;

C, in a few days 15 minute load scheduling, performs once for every 15 minutes, take into account 24 hours a few days ago and in a few days 1 hour load scheduling effect basis on, the electric power of the load-responsive in acting on behalf of load adjusts, and comprises ice conserve cold and electric automobile;

Compass of competency on D, real-time time yardstick, control object is the inner load participating in real-time response of load agency, comprises the load that energy storage and ice conserve cold have energy storage characteristic, controls to match with automatic generation AGC.

Further, described step 2) in, in each time scale, control centre takes into account wind-powered electricity generation predicated error, unbalanced power amount caused by the uncertainty of wind power is in confidence level in a certain scope as constraints condition of opportunity, and the relaxation factor of design opportunities constraints, its computing formula is:

r＝1-(σ/2D _wN)h （1）；

Wherein, σ is wind-powered electricity generation predicted power mean square deviation, D _wNfor the rated power of system wind-powered electricity generation, coefficient h regulates according to dispatching requirement at different levels;

The uncertainty of wind power is represented the distributed model adopting normal distribution as wind power prediction error by the error of wind power prediction; Suppose predicated error Normal Distribution N (0, σ ²), wherein σ ²depend on predicted time yardstick, setting wind energy turbine set active power of output analogue value D _wt () is approximate obeys N (D _wf(t), σ ²), average D _wft () is active power of wind power field predicted value, variances sigma ²value is carried out, accurately to reflect this power prediction error level according to different predicted time yardsticks; Wind field output of gaining merit is expressed as follows:

$D_w\left(t\right)=\frac{1}{\sqrt{2\mathrm{\π}}\mathrm{\σ}}\exp (-\frac{{(x-D_{\mathrm{Wf}}\left(t\right))}^2}{{2\mathrm{\σ}}^2})---\left(2\right).$

Further, in described step 3), in each time scale, carry out flexible load interaction scheduling based on multi-agent technology between load agency and control centre, load agency is target to the maximum with self benefits, and set up its Offer Model, expression formula is as follows:

max{Esy}＝max{|ΔD _ik|L _iAk-|ΔD _iEX|cost _iEX-|ΔD _iP|cost _iP} （3）；

In formula, i represents the period; Δ D _ikfor load acts on behalf of k power adjustment total amount; L _iAkfor load acts on behalf of the compensation electricity price of declaring; Δ D _iPwith Δ D _iEXbe respectively the adjustment amount of electricity price type load and stimulable type load in load agency; Cost _iPand cost _iEXbe respectively the Setup Cost of electricity price type load and stimulable type load;

Constraints comprises:

1. load proxy bid constraint:

L _{i min}≤L _iAk≤L _{i max}（4）；

In formula, L _{i min}, L _{i max}be respectively higher limit and lower limit that load agency reports load adjustment price;

2. Different time scales adjustable load adjustment amount restriction:

ΔD _{iEX min}≤ΔD _iEX≤ΔD _{iEX max}（5）；

ΔD _{iP min}≤ΔD _iP≤ΔD _{iP max}（6）；

In formula: Δ D _{iEX min}, Δ D _{iEX max}be respectively power adjustment higher limit and the lower limit of stimulable type load; Δ D _iPmin, Δ D _iPmax, be respectively the power adjustment higher limit and lower limit of price type load;

3. power-balance constraint:

ΔD _iV＝ΔD _ik+ΔD _iother（7）；

In formula: Δ D _iVfor the power adjustment total amount of system requirements; Δ D _iotherfor other load agency and the power adjustment of generating set;

When multiple load agency participates in the management and running of electrical network simultaneously, load agency needs by history bid information disclosed in study control centre and makes conjecture to the quotation strategy of other agency, optimize the quotation strategy of self on this basis further, based on current period system running state prediction, the running status that search is the most close with the current period in historical period, be called " same to scene " state, and using the quotation strategy of all for historical period rivals as the conjecture of present period, be expressed as:

$\begin{array}{c}{\left(A_m^t\right)}^{\text{'}}=A_m^{t_n}\\ {\left(B_m^t\right)}^{\text{'}}=B_m^{t_n}\end{array}(m\≠j)---\left(8\right);$

In formula: t _nfor the period the most close with t period running status in history, with for historical period acts on behalf of the quotation strategy parameter of m, with for the t period acts on behalf of j to the conjecture acting on behalf of m quotation strategy parameter; When each agency guesses the quotation strategy of other agencies right simultaneously, each agency all will reach the maximum return of expection, namely reach the Nash Equilibrium Solution accepted each other, and system running state prediction comprises load prediction, intermittent energy exerts oneself prediction and generator information.

Further, in described step 4), control centre's scheduling cost is minimum is that the decision model of target is as follows:

$\min \left\{c_{\mathrm{total}}\right\}=\min \left\{\underset{k=1}{\overset{N_A}{\mathrm{\Σ}}}{\cos t}_A\left({\mathrm{\ΔD}}_{\mathrm{iAk}}\right)\right\}---\left(9\right);$

In formula: Δ D _iAkfor the power adjustment of an i period kth load agency; Cost _a(Δ D _iAk) for acting on behalf of k Modulating Power Δ D by load in control centre _iAkthe reimbursement for expenses that Shi Suoxu pays; N _afor load acts on behalf of quantity;

Constraints comprises:

I, power-balance retrain

Constraints of Equilibrium for taking into account the probabilistic chance constraint of wind power, its expression formula as the formula (10):

P _r{|D _iG0+D _w-D _load0-ΔD _iV|≤ΔD}≥rλ ₀（10）；

After this formula represents the probability distribution taking into account wind power output, system power amount of unbalance is in the confidence level P in interval [-△ D, △ D] _rbe not less than r λ ₀; Wherein, Δ D _iVfor the power adjustment total amount of system requirements; D _iG0for i moment period unit output summation, D _load0for i period load summation, D _wfor i period wind-powered electricity generation gross capability, λ ₀for system power amount of unbalance is in the confidence level in interval [-△ D, △ D], r is relaxation factor;

II, load act on behalf of regulating power constraint:

ΔD _{iAk min}≤ΔD _iAk≤ΔD _{iAk max}（11）；

Wherein, Δ D _{iAk min}with Δ D _{iAk max}for load acts on behalf of lower limit and the higher limit of k regulating power.

Further, carry out returning step 1) after step 5) completes load scheduling task, carry out the load scheduling of subsequent period.

Compared with the prior art, the beneficial effect that the present invention reaches is:

1, a kind of hair electricity coordinated scheduling method taking into account flexible load that the uncertainty that the present invention be directed to wind power output proposes, the angle that the method is coordinated from Multiple Time Scales carries out United Dispatching to hair electric resources, to make full use of the flexible load resource of different response time yardstick, promote electrical network and to dissolve the ability of wind-powered electricity generation.

2, the unbalanced power amount caused by the uncertainty of wind power is in confidence level in a certain scope as constraints condition of opportunity by the present invention, and devise the relaxation factor of constraints condition of opportunity, be conducive to the constraint according to the suitable lax pair unbalanced power amount of wind-powered electricity generation predicated error size, thus be conducive to improving scheduling economy.

3, in the present invention, load agency, by the study to historical data or rival's information, can realize the maximization of self profit by strategic bidding, but there is the possibility of INFORMATION OF INCOMPLETE between different load agency.

Accompanying drawing explanation

Fig. 1 is the scheduling process figure of the flexible load that Multiple Time Scales provided by the invention is coordinated;

Fig. 2 is the load based on multi-agent technology provided by the invention agency scheduling flow figure interactive with control centre.

Embodiment

Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described in further detail.

The invention provides the interactive dispatching method of the probabilistic flexible load of a kind of Multiple Time Scales coordination wind-powered electricity generation, the method mainly comprises the following steps, its flow chart as shown in Figure 2:

1) the whole process that flexible load is dispatched is divided into 4 time scales, comprise 24h, in a few days 1h, in a few days 15min and Real-time Load scheduling a few days ago, control centre is prognoses system load, wind power generation on Different time scales, announces related system operation information, dispatching requirement information; The scheduling process figure that Multiple Time Scales provided by the invention is coordinated is as shown in Figure 1:

A, a few days ago 24 hour load scheduling, within every 24 hours, perform once, be divided into the power adjustment of 96 periods to following one day each load agency to make plan, its control object is the flexible load that response speed is comparatively slow, advance notification times is longer, as the industrial load of iron and steel, non-ferrous metals processing.

B, in a few days 1 hour load scheduling, within every 1 hour, perform once, on the basis taking into account Load Regulation amount a few days ago, plan is made to the power adjustment of following 1 hour each load agency, scheduler object is shorter, the response speed load faster of regulating cycle in each load agency, as the illumination in part business and communal facility and air conditioner load.

C, in a few days 15 minute load scheduling, within every 15 minutes, perform once, take into account a few days ago and in a few days 1 hour load scheduling effect basis on, the electric power of the quick load-responsive in agency is adjusted, as ice conserve cold, electric automobile etc., in this time scale, the precision of wind power prediction is very high, therefore, the raising that can try one's best to the constraint of unbalanced power amount, to reduce power adjustment or the AGC action of load Real-Time Scheduling.

D, Real-time Load control, and control object is the inner load participating in real-time response of agency, as energy storage, ice conserve cold etc. have the load of energy storage characteristic, can control to match with automatic generation AGC.

2) on Different time scales, control centre sets up wind power prediction uncertainty models, formulates conventional fire/Hydropower Unit operation plan, announces power system operation information and flexible load dispatching requirement information;

In each time scale, control centre takes into account wind-powered electricity generation predicated error, unbalanced power amount caused by the uncertainty of wind power is in confidence level in a certain scope as constraints condition of opportunity, and the relaxation factor of design opportunities constraints, its computing formula is:

r＝1-(σ/2D _wN)h （1）；

Wherein, σ is wind-powered electricity generation predicted power mean square deviation, D _wNfor the rated power of system wind-powered electricity generation, coefficient h regulates according to dispatching requirement at different levels; What deserves to be explained is, the constraint of lax pair unbalanced power amount, the power adjustment of scheduling at the corresponding levels can be reduced, thus be conducive to the economy improving scheduling at the corresponding levels.But overrelaxation can cause next stage to dispatch the pressure increase of (shorter time yardstick) to the constraint of unbalanced power amount, increases the cost of next stage scheduling.

The uncertainty of wind power is represented the distributed model adopting normal distribution as wind power prediction error by the error of wind power prediction; Suppose predicated error Normal Distribution N (0, σ ²), wherein σ ²depend on predicted time yardstick, setting wind energy turbine set active power of output analogue value D _wt () is approximate obeys N (D _wf(t), σ ²), average D _wft () is active power of wind power field predicted value, variances sigma ²value is carried out, accurately to reflect this power prediction error level according to different predicted time yardsticks; Wind field output of gaining merit is expressed as follows:

$D_w\left(t\right)=\frac{1}{\sqrt{2\mathrm{\π}}\mathrm{\σ}}\exp (-\frac{{(x-D_{\mathrm{Wf}}\left(t\right))}^2}{{2\mathrm{\σ}}^2})---\left(2\right).$

3) load agency is according to the response characteristic of dissimilar flexible controllable burden, analyze and coordinate to arrange 24 hours a few days ago, the controlled variable of flexible load in compass of competency in a few days 1 hour, in a few days 15 minutes and real-time time yardstick, flexible load dispatching requirement information, power system operation information and historical transactional information are learnt, the Offer Model being conducive to self benefits is formulated based on multi-agent technology, and reporting scheduling center;

In each time scale, carry out flexible load interaction scheduling based on multi-agent technology between load agency and control centre, load agency is target to the maximum with self benefits, and set up its Offer Model, expression formula is as follows:

max{Esy}＝max{|ΔD _ik|L _iAk-|ΔD _iEX|cost _iEX-|ΔD _iP|cost _iP} （3）；

In formula, i represents the period; Δ D _ikfor load acts on behalf of k power adjustment total amount; L _iAkfor load acts on behalf of the compensation electricity price of declaring; Δ D _iPwith Δ D _iEXbe respectively the adjustment amount of electricity price type load and stimulable type load in load agency; Cost _iPand cost _iEXbe respectively the Setup Cost of electricity price type load and stimulable type load;

Constraints comprises:

1. load proxy bid constraint:

L _{i min}≤L _iAk≤L _{i max}（4）；

In formula, L _{i min}, L _{i max}be respectively higher limit and lower limit that load agency reports load adjustment price;

2. Different time scales adjustable load adjustment amount restriction:

ΔD _{iEX min}≤ΔD _iEX≤ΔD _{iEX max}（5）；

ΔD _{iP min}≤ΔD _iP≤ΔD _{iP max}（6）；

In formula: Δ D _iEXmin, Δ D _iEXmaxbe respectively power adjustment higher limit and the lower limit of stimulable type load; Δ D _iPmin, Δ D _iPmax, be respectively the power adjustment higher limit and lower limit of price type load;

3. power-balance constraint:

ΔD _iV＝ΔD _ik+ΔD _iother（7）；

In formula: Δ D _iVfor the power adjustment total amount of system requirements; Δ D _iotherfor other load agency and the power adjustment of generating set;

When multiple load agency participates in the management and running of electrical network simultaneously, load agency needs by history bid information disclosed in study control centre and makes conjecture to the quotation strategy of other agency, optimize the quotation strategy of self on this basis further, based on current period system running state prediction, the running status that search is the most close with the current period in historical period, be called " same to scene " state, and using the quotation strategy of all for historical period rivals as the conjecture of present period, be expressed as:

$\begin{array}{c}{\left(A_m^t\right)}^{\text{'}}=A_m^{t_n}\\ {\left(B_m^t\right)}^{\text{'}}=B_m^{t_n}\end{array}(m\≠j)---\left(8\right);$

In formula: t _nfor the period the most close with t period running status in history, with for historical period acts on behalf of the quotation strategy parameter of m, with for the t period acts on behalf of j to the conjecture acting on behalf of m quotation strategy parameter; When each agency guesses the quotation strategy of other agencies right simultaneously, each agency all will reach the maximum return of expection, namely reach the Nash Equilibrium Solution accepted each other, and system running state prediction comprises load prediction, intermittent energy exerts oneself prediction and generator information.

4) the schedulable ability and quotation information that report are acted on behalf of by control centre according to load, minimum for target with control centre's scheduling cost, scheduling is optimized to the schedulable burdened resource that multiple load is acted on behalf of, and load adjustment instruction and final making up price are sent to load agency;

In described step 4), scheduling cost is minimum is that the decision model of target is as follows:

$\min \left\{c_{\mathrm{total}}\right\}=\min \left\{\underset{k=1}{\overset{N_A}{\mathrm{\Σ}}}{\cos t}_A\left({\mathrm{\ΔD}}_{\mathrm{iAk}}\right)\right\}---\left(9\right);$

In formula: Δ D _iAkfor the power adjustment of an i period kth load agency; Cost _a(Δ D _iAk) for acting on behalf of k Modulating Power Δ D by load in control centre _iAkthe reimbursement for expenses that Shi Suoxu pays; N _afor load acts on behalf of quantity;

Constraints comprises: regulating power constraint is acted on behalf of in power-balance constraint, load, constraint, the constraint of generator climbing rate and system reserve constraint are bidded in generating set power adjustment constraint;

I, power-balance retrain

Constraints of Equilibrium for taking into account the probabilistic chance constraint of wind power, its expression formula as the formula (10):

P _r{|D _iG0+D _w-D _load0-ΔD _iV|≤ΔD}≥rλ ₀（10）；

After this formula represents the probability distribution taking into account wind power output, system power amount of unbalance is in the confidence level P in interval [-△ D, △ D] _rbe not less than r λ ₀; Wherein, Δ D _iVfor the power adjustment total amount of system requirements; D _iG0for i moment period unit output summation, D _load0for i period load summation, D _wfor i period wind-powered electricity generation gross capability, λ 0 is in the confidence level in interval [-△ D, △ D] for system power amount of unbalance, and r is relaxation factor;

II, load act on behalf of regulating power constraint:

ΔD _{iAk min}≤ΔD _iAk≤ΔD _{iAk max}（11）；

Wherein, Δ D _{iAk min}with Δ D _{iAk max}for load acts on behalf of lower limit and the higher limit of k regulating power.

5), after each load agency obtains final dispatch command, minimum for target with load scheduling agent cost, by Price Mechanisms or incentive mechanism, the electric power to managed load adjusts, and completes scheduler task, returns step 1), carry out subsequent period scheduling.

Method provided by the invention has enriched the probabilistic scheduling method of reply wind power, enhances the regulating power of electrical network.

Finally should be noted that: above embodiment is only in order to illustrate that technical scheme of the present invention is not intended to limit, although with reference to above-described embodiment to invention has been detailed description, those of ordinary skill in the field are to be understood that: still can modify to the specific embodiment of the present invention or equivalent replacement, and not departing from any amendment of spirit and scope of the invention or equivalent replacement, it all should be encompassed in the middle of right of the present invention.

Claims (6)

1. tackle wind-powered electricity generation probabilistic Multiple Time Scales flexible load dispatching method, it is characterized in that, described method adopts Multiple Time Scales to coordinate, and described method comprises the steps:

1) control centre predicts power system load, wind power generation on Different time scales;

2) on Different time scales, control centre sets up wind power prediction uncertainty models, formulates conventional fire/Hydropower Unit operation plan, announces power system operation information and flexible load dispatching requirement information;

3) load agency is according to the response characteristic of dissimilar flexible controllable burden, analyze and coordinate to arrange 24 hours a few days ago, the controlled variable of flexible load in compass of competency in a few days 1 hour, in a few days 15 minutes and real-time time yardstick, flexible load dispatching requirement information, power system operation information and historical transactional information are learnt, the Offer Model being conducive to self benefits is formulated based on multi-agent technology, and reporting scheduling center;

4) the schedulable ability and quotation information that report are acted on behalf of by control centre according to load, minimum for target with control centre's scheduling cost, scheduling is optimized to the schedulable burdened resource that multiple load is acted on behalf of, and load adjustment instruction and final making up price are sent to load agency;

5), after load agency obtains final dispatch command, minimum for target with load scheduling agent cost, by Price Mechanisms or incentive mechanism, the electric power to institute's administrative loads adjusts.

2. flexible load dispatching method as claimed in claim 1, is characterized in that, in described step 1), the Different time scales of flexible load scheduling comprises 24 hours a few days ago, compass of competency in a few days 1 hour, in a few days 15min and real-time time yardstick,

A, a few days ago 24 hour load scheduling, within every 24 hours, perform once, be divided into the power adjustment of 96 periods to following one day load agency to make plan, its control object is the flexible load that response speed is slow, advance notification times is long, comprises the industrial load of iron and steel and non-ferrous metals processing;

B, in a few days 1 hour load scheduling, within every 1 hour, perform once, on the basis taking into account Load Regulation amount a few days ago, plan is made to the power adjustment of following 1 hour load agency, scheduler object is the load of short, the fast response time of regulating cycle in load agency, comprises the illumination in business and communal facility and air conditioner load;

C, in a few days 15 minute load scheduling, performs once for every 15 minutes, take into account 24 hours a few days ago and in a few days 1 hour load scheduling effect basis on, the electric power of the load-responsive in acting on behalf of load adjusts, and comprises ice conserve cold and electric automobile;

Compass of competency on D, real-time time yardstick, control object is the inner load participating in real-time response of load agency, comprises the load that energy storage and ice conserve cold have energy storage characteristic, controls to match with automatic generation AGC.

3. flexible load dispatching method as claimed in claim 1, it is characterized in that, described step 2) in, in each time scale, control centre takes into account wind-powered electricity generation predicated error, unbalanced power amount caused by the uncertainty of wind power is in confidence level in a certain scope as constraints condition of opportunity, and the relaxation factor of design opportunities constraints, its computing formula is:

r＝1-(σ/2D _wN)h （1）；

Wherein, σ is wind-powered electricity generation predicted power mean square deviation, D _wNfor the rated power of system wind-powered electricity generation, coefficient h regulates according to dispatching requirement at different levels;

The uncertainty of wind power is represented the distributed model adopting normal distribution as wind power prediction error by the error of wind power prediction; Suppose predicated error Normal Distribution N (0, σ ²), wherein σ ²depend on predicted time yardstick, setting wind energy turbine set active power of output analogue value D _wt () is approximate obeys N (D _wf(t), σ ²), average D _wft () is active power of wind power field predicted value, variances sigma ²value is carried out, accurately to reflect this power prediction error level according to different predicted time yardsticks; Wind field output of gaining merit is expressed as follows:

$D_w\left(t\right)=\frac{1}{\sqrt{2\mathrm{\π}}\mathrm{\σ}}\exp (-\frac{{(x-D_{\mathrm{Wf}}\left(t\right))}^2}{{2\mathrm{\σ}}^2})---\left(2\right).$

4. flexible load dispatching method as claimed in claim 1, it is characterized in that, in described step 3), in each time scale, flexible load interaction scheduling is carried out based on multi-agent technology between load agency and control centre, load agency is target to the maximum with self benefits, and set up its Offer Model, expression formula is as follows:

max{Esy}＝max{|ΔD _ik|L _iAk-|ΔD _iEX|cost _iEX-|ΔD _iP|cost _iP} （3）；

In formula, i represents the period; Δ D _ikfor load acts on behalf of k power adjustment total amount; L _iAkfor load acts on behalf of the compensation electricity price of declaring; Δ D _iPwith Δ D _iEXbe respectively the adjustment amount of electricity price type load and stimulable type load in load agency; Cost _iPand cost _iEXbe respectively the Setup Cost of electricity price type load and stimulable type load;

Constraints comprises:

1. load proxy bid constraint:

L _{i min}≤L _iAk≤L _{i max}（4）；

In formula, L _{i min}, L _{i max}be respectively higher limit and lower limit that load agency reports load adjustment price;

2. Different time scales adjustable load adjustment amount restriction:

ΔD _{iEX min}≤ΔD _iEX≤ΔD _{iEX max}（5）；

ΔD _{iP min}≤ΔD _iP≤ΔD _{iP max}（6）；

In formula: Δ D _iEXmin, Δ D _iEXmaxbe respectively power adjustment higher limit and the lower limit of stimulable type load; Δ D _iPmin, Δ D _iPmax, be respectively the power adjustment higher limit and lower limit of price type load;

3. power-balance constraint:

ΔD _iV＝ΔD _ik+ΔD _iother（7）；

In formula: Δ D _iVfor the power adjustment total amount of system requirements; Δ D _iotherfor other load agency and the power adjustment of generating set;

When multiple load agency participates in the management and running of electrical network simultaneously, load agency needs by history bid information disclosed in study control centre and makes conjecture to the quotation strategy of other agency, optimize the quotation strategy of self on this basis further, based on current period system running state prediction, the running status that search is the most close with the current period in historical period, be called " same to scene " state, and using the quotation strategy of all for historical period rivals as the conjecture of present period, be expressed as:

$\begin{array}{c}{\left(A_m^t\right)}^{\text{'}}=A_m^{t_n}\\ {\left(B_m^t\right)}^{\text{'}}=B_m^{t_n}\end{array}(m\≠j)---\left(8\right);$

In formula: t _nfor the period the most close with t period running status in history, with for historical period acts on behalf of the quotation strategy parameter of m, with for the t period acts on behalf of j to the conjecture acting on behalf of m quotation strategy parameter; When each agency guesses the quotation strategy of other agencies right simultaneously, each agency all will reach the maximum return of expection, namely reach the Nash Equilibrium Solution accepted each other, and system running state prediction comprises load prediction, intermittent energy exerts oneself prediction and generator information.

5. flexible load dispatching method as claimed in claim 1, is characterized in that, in described step 4), control centre's scheduling cost is minimum is that the decision model of target is as follows:

$\min \left\{c_{\mathrm{total}}\right\}=\min \left\{\underset{k=1}{\overset{N_A}{\mathrm{\Σ}}}{\cos t}_A\left({\mathrm{\ΔD}}_{\mathrm{iAk}}\right)\right\}---\left(9\right);$

In formula: Δ D _iAkfor the power adjustment of an i period kth load agency; Cost _a(Δ D _iAk) for acting on behalf of k Modulating Power Δ D by load in control centre _iAkthe reimbursement for expenses that Shi Suoxu pays; N _afor load acts on behalf of quantity;

Constraints comprises:

I, power-balance retrain

Constraints of Equilibrium for taking into account the probabilistic chance constraint of wind power, its expression formula as the formula (10):

P _r{|D _iG0+D _w-D _load0-ΔD _iV|≤ΔD}≥rλ ₀（10）；

After this formula represents the probability distribution taking into account wind power output, system power amount of unbalance is in the confidence level P in interval [-△ D, △ D] _rbe not less than r λ ₀; Wherein, Δ D _iVfor the power adjustment total amount of system requirements; D _iG0for i moment period unit output summation, D _load0for i period load summation, D _wfor i period wind-powered electricity generation gross capability, λ ₀for system power amount of unbalance is in the confidence level in interval [-△ D, △ D], r is relaxation factor;

II, load act on behalf of regulating power constraint:

ΔD _{iAk min}≤ΔD _iAk≤ΔD _{iAk max}（11）；

Wherein, Δ D _{iAk min}with Δ D _{iAk max}for load acts on behalf of lower limit and the higher limit of k regulating power.

6. flexible load dispatching method as claimed in claim 1, is characterized in that, carry out returning step 1) after step 5) completes load scheduling task, carry out the load scheduling of subsequent period.