CN105098839B - A kind of wind-electricity integration coordination optimizing method based on the uncertain output of wind-powered electricity generation - Google Patents

A kind of wind-electricity integration coordination optimizing method based on the uncertain output of wind-powered electricity generation Download PDF

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CN105098839B
CN105098839B CN201510566395.6A CN201510566395A CN105098839B CN 105098839 B CN105098839 B CN 105098839B CN 201510566395 A CN201510566395 A CN 201510566395A CN 105098839 B CN105098839 B CN 105098839B
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energy
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CN105098839A (en
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于东
孙欣
徐勤
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Jiangsu University
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Abstract

The invention discloses a kind of based on the uncertain wind-electricity integration coordination optimizing method contributed of wind-powered electricity generation, comprise the following steps：Acquisition system relevant parameter；Wind-powered electricity generation prediction error calculating and wind-powered electricity generation prediction error model of growth are established, error model of growth is predicted according to wind-powered electricity generation, obtains the uncertain output of wind-powered electricity generation；On the basis of establishing load and may participate in the weight sector model and introducing schedulable load and energy-storage system of scheduling, establish wind power cost model, and establish and consider schedulable load and energy-storage system wind-electricity integration coordination optimization scheduling model, according to the Optimized model, each unit output in dispatching cycle is obtained；Wind rate is abandoned by each unit output computing system, all kinds of costs of system and spare condition are analyzed；The present invention establishes online based on the uncertain wind-electricity integration Coordination and Optimization Model contributed with schedulable load weight sector of wind-powered electricity generation, provides the Optimized Operation scheme with obvious economic results in society when solving the problems, such as wind power integration for dispatching of power netwoks personnel.

Description

A kind of wind-electricity integration coordination optimizing method based on the uncertain output of wind-powered electricity generation
Technical field
It is more particularly to a kind of based on the uncertain wind-powered electricity generation contributed of wind-powered electricity generation the present invention relates to Operation of Electric Systems and scheduling field Grid-connected coordination optimization method.
Background technology
Currently, certain progress is had been achieved for for the be incorporated into the power networks research of economic load dispatching of large-scale wind power both at home and abroad. Due to the features such as wind power output randomness is big and fluctuation is strong, necessarily brought to the grid-connected economic load dispatching of large-scale wind power larger tired Difficulty, therefore many scholars have carried out numerous studies to wind power output prediction, but still be difficult to obtain accurate prediction result, wind-powered electricity generation work( Rate predicts error also by long-term existence.Energy-storage system can effectively solve the above problems, but it is envisaged that energy storage cost It is too high and relatively inefficient, blindly increase the stored energy capacitance of system, can equally reduce the economy of system.Load is special Property with load level be to influence important two factors of power grid wind electricity digestion capability.Build the background of intelligent grid energetically in country Under, load starts to play more and more important role, and it has no longer been single electricity consumption side, and initially as a kind of virtual plant Carried out with power network interactive.Power network can be by assessing load level, and reaching the modes such as related protocol with user melts a part of load Enter generation schedule.
The content of the invention
It is an object of the invention to provide a kind of based on the uncertain wind-electricity integration coordination optimizing method contributed of wind-powered electricity generation, building On the basis of the wind-powered electricity generation that the error that is based on increases does not know output model, for problem caused by the uncertain output of wind-powered electricity generation, build Wind power cost model is found；By the role that each type load is participated in system call is different, the present invention is according to each type load The degree of scheduling can be participated in, the index of comprehensive each type load, proposes the concept of schedulable load weight sector, and establish mould Type；Wind-electricity integration coordination optimization scheduling model is established with reference to energy-storage system, is solving the problems, such as wind power integration for dispatching of power netwoks personnel When provide with obvious economic results in society Optimized Operation scheme.
The present invention is addressed by the following technical programs：
A kind of wind-electricity integration coordination optimizing method based on the uncertain output of wind-powered electricity generation, comprises the following steps：
Step 1, the setting and collection of the relevant parameter such as wind-powered electricity generation, fired power generating unit, energy-storage system and schedulable load；
Wind-powered electricity generation parameter includes being used for the related data for determining wind power cost：Wind-powered electricity generation prediction output PWF.jt, system it is active negative Lotus PD.t, in dispatching cycle operation Wind turbines number NW, wind-powered electricity generation precision of prediction AW.jt；
Fired power generating unit relevant parameter：The number N of the fired power generating unit of operation in dispatching cycleG, fired power generating unit linearisation cost Function coefficients ai, fired power generating unit units limits upper limit lower limitThe climbing and rate of descent that conventional power unit is contributed
Energy-storage system relevant parameter：Efficiency for charge-discharge ψ, the energy storage system capacity bound E of energy-storage systemmin、Emax, t when The power output P of section energy-storage systemE(t), energy-storage system charge-discharge electric power bound P in the unit intervalE.min、PE.max, energy storage system Unite cost coefficient kE(t)；
Schedulable load relevant parameter：Correction factor a, b, function coefficients k1(t)、k2(t), t period r type load sizes PD.rt, system loading number of types l；
Step 2, according to the setting of step 1 wind-powered electricity generation relevant parameter, the pre- permeability of wind-powered electricity generation is drawn on this basis, according to wind-powered electricity generation Pre- permeability and wind power output precision of prediction, wind power output prediction error is obtained, based on wind-powered electricity generation error model of growth, obtains air-out The uncertain output calculation model of electricity；
Step 3, wind-powered electricity generation is obtained according to step 2 and does not know output calculation model, establishing load and may participate in the weight of scheduling Interval model and introducing schedulable load weight sector model are with the basis of energy-storage system model, establishing wind power cost mould Type, and establish and consider schedulable load and energy-storage system wind-electricity integration coordination optimization scheduling model, according to the Optimized model, obtain Each unit output in dispatching cycle；
Step 4, wind rate is abandoned by each unit output computing system, all kinds of costs of system and spare condition is analyzed.
Further, the building process of wind-powered electricity generation error model of growth is in described step 2：
Step 2.1, if certain given wind power output prediction data is in t0The error of period is et0, and do not introducing it Under conditions of its period error, in the t periods, by et0Caused error isIf in the presence of unrelated with t and normal more than 0 Number A so thatThe growth for then claiming error is linear；In the presence of the constant B more than 1, make Then the growth of title error makes exponential；
Step 2.2, present invention definition, prediction error are stable by the wind power output prediction of linear increase, predict error Exponentially-increased wind power output prediction is unstable；Assuming that wind power output prediction is in t0、t1、t2、…、tnThe error of period For et0、et1、et2、…、etnIf wind power output prediction is stable, in t1、t2、…、tn、tn+1During the period, by et0、et1、 et2、…、etnCaused error increment value is
Equally, if wind power output prediction error is unstable, in t1、t2、…、tn、tn+1During the period, by et0、et1、 et2、…、etnCaused error increment value is
Further, the uncertain output calculation model of wind-powered electricity generation is in described step 2：If wind power output prediction is stable, Then not knowing output calculation model based on the wind-powered electricity generation that error increases is：
Further, energy-storage system model is in the step 3：
The current state (capacity) of energy-storage system meets for E (t)：E (t)=E (t-1)+ψ PE(t) Δ t, Emin≤E(t)≤ Emax,
The charge-discharge electric power P of day partE(t) meet：PE.min≤PE(t)≤PE.max,
Then t periods system calling energy-storage system cost model is：CE(t)=kE(t)PE(t)。
Further, the process of establishing of schedulable load weight sector model is in the step 3：
Step S3.1, because the degree that can each type load in system participate in dispatching in each period is different, so handle These loads are melted into the rank in different sections；Therefore in system call, each type load is can be obtained by with reference to actual conditions Rank, and take the span of properties level as the initial weight section of each type load, as r type loads are initial in the t periods Weight sector is：
Step S3.2, above formula is subjected to Fuzzy Processing using fuzzy mathematics relevant knowledge, made：Then Power interval numbers of each type load in the t periods are：Each type load may participate in the weight sector exponential model of scheduling For：The weight that then present invention defines that each type load participates in dispatching in the t periods is：
Step S3.3, finally draw each type load cost calculation model：ED.rt=k1(t)sr.tPD.rt+k2(t)(sr.tPD.rt )2, then t periods system call schedulable load weight sector model be：
Further, wind-powered electricity generation cost model is in described step 3：
The present invention builds wind power cost model and includes two parts：When energy storage cost cost, second, schedulable load cost； Then：
PE(t)=(1- ζt)PWU.t
Further, the economic load dispatching object function in the step 3 and constraints are：
Object function：
Constraints：
(1) power-balance constraint
(2) unit power output constrains
(3) ramping rate constraints
(4) energy-storage system constrains
Therefore there is following technique effect herein：
The wind-powered electricity generation increased based on error that the present invention establishes does not know the uncertain output of wind-powered electricity generation that output model calculates Than more comprehensive response error information more accurate data can be provided for follow-up scheduling；Schedulable weight sector model can Think that different stage load formulates corresponding standard in the schedulability of different periods, avoid the resource wave under unified standard Take, schedulable load is substantially effectively participated in the regulation to the uncertain output of wind-powered electricity generation, so as to reduce to energy storage system The usage amount of system, reduce the spare capacity for abandoning wind rate and system.The participation of energy-storage system, it can make up adjustable under extreme case Degree load can not participate in the shortcomings that wind-powered electricity generation regulation, be undertaken during weight sector division is carried out to schedulable load certain Standby acts on；The present invention provides for dispatching of power netwoks personnel when solving the problems, such as wind power integration has the excellent of obvious economic results in society Change scheduling scheme.
Brief description of the drawings
Accompanying drawing 1 is that wind power output change does not know output schematic diagram with wind-powered electricity generation；
Accompanying drawing 2 is energy-storage system charge and discharge electrical schematic；
Accompanying drawing 3 is system reserve demand schematic diagram in dispatching cycle.
Embodiment
The present invention program is described in further detail with reference to the accompanying drawings and detailed description.
Accompanying drawing 1 illustrates the uncertain composition part contributed of wind-powered electricity generation, because error is sustainable growth to a certain extent, wind Uncertain contribute of electricity predicts that error and wind-powered electricity generation wind-powered electricity generation are predicted that error increases and formed by wind-powered electricity generation；
Accompanying drawing 2 is to use energy-storage system charge and discharge electrical schematic, because energy-storage system is by capacity and its charging and discharging capabilities Limitation, depends merely on energy-storage system and carrys out uncertain contribute of regulating wind power and implement relatively difficult in some cases, therefore, the present invention Introducing schedulable load, to handle, wind-powered electricity generation is uncertain to contribute to cooperate with energy-storage system；
The present invention is specifically implemented as follows based on the uncertain wind-electricity integration coordination optimizing method contributed of wind-powered electricity generation：
The setting and collection of step 1, relevant parameter
The setting and collection of step 1.1, wind-powered electricity generation relevant parameter
Wind-powered electricity generation parameter mainly includes：Wind-powered electricity generation prediction output PWF.jt, system burden with power PD.t、Operation in dispatching cycle Wind turbines number NW, wind-powered electricity generation precision of prediction AW.jt；
The setting and collection of step 1.2, fired power generating unit relevant parameter
Fired power generating unit relevant parameter：The number N of the fired power generating unit of operation in dispatching cycleG, fired power generating unit linearisation cost Function coefficients ai, fired power generating unit units limits upper limit lower limitThe climbing and rate of descent that conventional power unit is contributed
The setting and collection of step 1.3, energy-storage system relevant parameter
Energy-storage system relevant parameter：Efficiency for charge-discharge ψ, the energy storage system capacity bound E of energy-storage systemmin、Emax, unit Energy-storage system charge-discharge electric power bound P in timeE.min、PE.max, energy-storage system cost coefficient kE(t)；
The setting and collection of step 1.4, schedulable load relevant parameter
Schedulable load relevant parameter：Correction factor a, b, function coefficients k1(t)、k2(t), t period r type load sizes PD.rt, system loading number of types l.
Step 2, the setting according to step 1 wind-powered electricity generation relevant parameter, the pre- permeability of wind-powered electricity generation are drawn on this basis, according to wind-powered electricity generation Pre- permeability and wind power output precision of prediction, wind power output prediction error is obtained, based on error model of growth, draws wind-powered electricity generation not It is determined that contribute.
Wind-powered electricity generation error increases computation model：
If certain given wind power output prediction data is in t0The error of period is et0, and do not introducing other periods mistakes Under conditions of difference, in the t periods, by et0Caused error isIf
(1) constant A unrelated with t and more than 0 be present so that
The growth for then claiming error is linear；
(2) the constant B more than 1 be present so that
Then the growth of title error makes exponential；
Present invention definition, prediction error are stable by the wind power output prediction of linear increase, and prediction error is increased by index Long wind power output prediction is unstable；
Assuming that wind power output prediction is in t0、t1、t2、…、tnThe error of period is et0、et1、et2、…、etnIf wind power output Prediction is stable, then in t1、t2、…、tn、tn+1During the period, by et0、et1、et2、…、etnCaused error increment value is
Equally, if wind power output prediction error is unstable, in t1、t2、…、tn、tn+1During the period, by et0、et1、 et2、…、etnCaused error increment value is
Wind-powered electricity generation does not know output calculation model：
Because wind-powered electricity generation prediction is that stable being predicted with wind-powered electricity generation is the wind-powered electricity generation based on error growth in the case of unstable two kinds Uncertain output calculation method is identical, situation of the present invention when this discussion wind power output is predicted as stablizing.Wind power output is pre- Survey and similar can be tried to achieve for unstable timing cases；
If wind power output prediction is stable, output calculation model such as following formula institute is not known based on the wind-powered electricity generation that error increases Show：
Step 3, obtain according to step 2 that wind-powered electricity generation is uncertain to contribute, establishing load and may participate in the weight sector model of scheduling And schedulable load weight sector model is introduced with the basis of energy-storage system model, establishing wind power cost model, and build Consideration schedulable load and energy-storage system wind-electricity integration coordination optimization scheduling model have been found, according to the Optimized model, has been dispatched Each unit output in cycle.
Energy-storage system (ESS) model is：
ESS current state (capacity) meets for E (t)：
E (t)=E (t-1)+ψ PE(t) Δ t,
Emin≤E(t)≤Emax, through substantial amounts of optimum experimental, wherein, PE(t) it is the power output of t period energy-storage systems, Emin=0, Emax=40, ψ=0.95,
The charge-discharge electric power P of day partE(t) meet：
PE.min≤PE(t)≤PE.max, through substantial amounts of optimum experimental wherein, PE.min=-25, PE.max=25,
Then t periods system calling energy-storage system ESS cost models are：
CE(t)=kE(t)PE(t)。
Schedulable load weight sector model is：
Load weight represents that each type load could participate in the degree of scheduling in systems, because each type load is in system call Middle participated in role is different, so the degree of scheduling can be participated according to each type load, and the index of comprehensive each type load, Load is divided into based on interval number by 3 types；
Because the degree that can each type load in system participate in dispatching in each period is different, so these loads Into the rank in different sections.Therefore in system call, the rank of each type load is can be obtained by with reference to actual conditions, and take category Initial weight section of the span of property rank as each type load, as r type loads in the initial weight section of t periods are：
Above formula is subjected to Fuzzy Processing using fuzzy mathematics relevant knowledge, made：
Through substantial amounts of optimum experimental wherein, a, b are respectively 0.5,1,
Then power interval numbers of each type load in the t periods are：
The weight sector exponential model that each type load may participate in scheduling is：
Then defining the weight that each type load participates in dispatching in the t periods herein is：
Each type load cost calculation model：
ED.rt=k1(t)sr.tPD.rt+k2(t)(sr.tPD.rt)2,
Then t periods system calling schedulable load weight sector model is：
Wind power cost model is：
Wind-powered electricity generation, which abandons wind reason, mainly includes the following aspects：1. Wind turbines growth is too fast, grid connected wind power capacity is far super System digestion capability, then power network is caused can not fully to dissolve wind-powered electricity generation amount in time；2. the ability to send outside deficiency of wind-powered electricity generation, if working as local nothing When method fully dissolves wind-powered electricity generation amount, if the transmittability deficiency of circuit, will cause part to abandon wind；3. wind-powered electricity generation predicts error；4. electricity Net dispatching deficiency.
Wind reason is abandoned with reference to above-mentioned wind-powered electricity generation, building wind power cost model includes two parts herein：First, energy storage cost cost； Second, schedulable load cost.
PE(t)=(1- ζt)PWU.t
Object function and constraints are：
Object function：
Constraints：
(1) power-balance constraint
(2) unit power output constrains
(3) ramping rate constraints
(4) ESS is constrained
Step 4, wind rate abandoned by each unit output computing system, all kinds of costs of system and spare condition are analyzed.
The present invention is planned using the 10 machine systems with Large-scale Wind Power field as example using 24h, but to be within 15 minutes between Every (T=96), emulation is optimized by MATLAB simulation softwares.
Due to carrying out the division of interval weight to schedulable load so that all kinds of schedulable loads can be at different periods Reason wind-powered electricity generation plays certain complementation on uncertain the problem of contributing, and is acted on plus energy-storage system standby so that schedulable is born Lotus is fully participated in in the uncertain regulation contributed of wind-powered electricity generation, not only saving system cost, and is reduced system and abandoned wind rate.
Accompanying drawing 3 is that system reserve demand schematic diagram, it can be seen from the figure that, stand-by requirement are all expired in dispatching cycle Foot, it is standby that can not regulate and control the period by energy-storage system and provide, energy-storage system power storage quota or during without power storage by The offer of schedulable load is standby, serves the effect of complementation.Simultaneously because A class schedulable loads and B class schedulable loads can Scheduling property is opposition within most of period, therefore two class schedulable loads also play certain complementation within dispatching cycle Effect；
The present invention, which proposes, a kind of to contribute and the wind-powered electricity generation of schedulable load weight sector and coordinates excellent based on wind-powered electricity generation is uncertain Change method.First, the present invention has carried out correlative study to wind-powered electricity generation prediction error, it is proposed that the concept of the pre- permeability of wind-powered electricity generation, with reference to Wind-powered electricity generation precision of prediction, establish wind-powered electricity generation prediction error model；Secondly, wind-powered electricity generation prediction error model of growth is established, and establishes and is based on The wind-powered electricity generation that error increases does not know output model；In view of the schedulable ability of different load, it is proposed that schedulable load weight The concept in section, and establish model；On above Research foundation, establish based on the uncertain output of wind-powered electricity generation and schedulable load power The wind-electricity integration Coordination and Optimization Model in weight section, being provided for dispatching of power netwoks personnel when solving the problems, such as wind power integration has obvious society The Optimized Operation scheme of meeting economic benefit.
It should be appreciated that although the present specification is described in terms of embodiments, not each embodiment only includes one Individual independent technical scheme, this narrating mode of specification is only that those skilled in the art will should say for clarity For bright book as an entirety, the technical scheme in each embodiment may also be suitably combined to form those skilled in the art can With the other embodiment of understanding.
Those listed above is a series of to be described in detail only for feasibility embodiment of the invention specifically Bright, they simultaneously are not used to limit the scope of the invention, all equivalent implementations made without departing from skill spirit of the present invention Or change should be included in protection scope of the present invention.

Claims (6)

  1. It is 1. a kind of based on the uncertain wind-electricity integration coordination optimizing method contributed of wind-powered electricity generation, it is characterised in that to comprise the following steps：
    Step 1, the setting and collection of wind-powered electricity generation, fired power generating unit, energy-storage system and schedulable load relevant parameter；
    Wind-powered electricity generation parameter includes being used for the related data for determining wind power cost：Wind power output predicts PWF.jt, system burden with power PD.t, in dispatching cycle operation Wind turbines number NW, wind power output precision of prediction AW.jt；
    Fired power generating unit relevant parameter：The number N of the fired power generating unit of operation in dispatching cycleG, fired power generating unit linearisation cost function system Number ai, fired power generating unit units limits upper limit lower limitThe climbing and rate of descent that conventional power unit is contributed
    Energy-storage system relevant parameter：Efficiency for charge-discharge ψ, the energy storage system capacity bound E of energy-storage systemmin、Emax, the t periods store up The power output P of energy systemE(t), energy-storage system charge-discharge electric power bound P in the unit intervalE.min、PE.max, energy-storage system into This coefficient kE(t)；
    Schedulable load relevant parameter：Correction factor a, b, function coefficients k1(t)、k2(t), t period r type load sizes PD.rt, be Load type quantity of uniting l；
    Step 2, according to the setting of step 1 wind-powered electricity generation relevant parameter, the pre- permeability of wind-powered electricity generation is drawn on this basis, is oozed in advance according to wind-powered electricity generation Saturating rate and wind power output precision of prediction, wind power output prediction error is obtained, error model of growth is predicted based on wind power output, obtained Go out wind-powered electricity generation and do not know output calculation model；
    Step 3, wind-powered electricity generation is obtained according to step 2 and does not know output calculation model, establishing load and may participate in the weight sector of scheduling Exponential model and introducing schedulable load weight sector model are with the basis of energy-storage system model, establishing wind power cost mould Type, and the wind-electricity integration coordination optimization scheduling model for considering schedulable load and energy-storage system is established, according to the wind-electricity integration Scheduling model is coordinated and optimized, obtains each unit output in dispatching cycle；
    The process of establishing of schedulable load weight sector model is in the step 3：
    Step S3.1, because the degree that can the r type loads in system participate in dispatching in each period is different, so these are born Lotus is melted into the rank in different sections；Therefore in system call, the rank of r type loads is can be obtained by with reference to actual conditions, and Taking the span of properties level, r type loads are in the initial weight section of t periods as the initial weight section of r type loads： For initial weight interval limit of the r type loads in the t periods,For r type loads the t periods initial power The weight section upper limit；
    Step S3.2, above formula is subjected to Fuzzy Processing using fuzzy mathematics relevant knowledge, made：Then r classes are born Power interval numbers of the lotus in the t periods are：The weight sector exponential model that r type loads may participate in scheduling is：Then r type loads participated in the t periods scheduling weight be：
    Step S3.3, finally draw r type load cost calculation models：ED.rt=k1(t)sr.tPD.rt+k2(t)(sr.tPD.rt)2, then t Period system call schedulable load weight sector model be：L is system loading Number of types；
    Step 4, wind rate is abandoned by each unit output computing system, all kinds of costs of system and spare condition is analyzed.
  2. It is 2. according to claim 1 based on the uncertain wind-electricity integration coordination optimizing method contributed of wind-powered electricity generation, it is characterised in that The building process of wind power output prediction error model of growth is in described step 2：
    Step 2.1, if certain given wind power output prediction data is in t0The error of period is et0, and when not introducing other Under conditions of section error, in the t periods, by et0Caused error isIf in the presence of it is unrelated with t and more than 0 constant A, So thatT=t0+ 1, t0+ 2 ..., then the growth for claiming error is linear；In the presence of the constant B more than 1, So thatT=t0+ 1, t0+ 2 ..., then the growth for claiming error is exponential；
    Step 2.2, it is stable, the exponentially-increased wind-powered electricity generation of prediction error to predict that error is predicted by the wind power output of linear increase Prediction of contributing is unstable；Assuming that wind power output prediction is in t0、t1、t2、…、tnThe error of period is et0、et1、et2、…、 etnIf wind power output prediction is stable, in t1、t2、…、tn、tn+1During the period, by et0、et1、et2、…、etnCaused mistake Poor increment value is
    Equally, if wind power output prediction error is unstable, in t1、t2、…、tn、tn+1During the period, by et0、et1、 et2、…、etnCaused error increment value is
  3. It is 3. according to claim 2 based on the uncertain wind-electricity integration coordination optimizing method contributed of wind-powered electricity generation, it is characterised in that The uncertain output calculation model of wind-powered electricity generation is in described step 2：If wind power output prediction is stable, increased based on error Wind-powered electricity generation does not know output calculation model PWU.tFor：etFor in the error of t periods.
  4. It is 4. according to claim 1 based on the uncertain wind-electricity integration coordination optimizing method contributed of wind-powered electricity generation, it is characterised in that Energy-storage system model is in the step 3：
    The current state of energy-storage system meets for E (t)：E (t)=E (t-1)+ψ PE(t) Δ t, Emin≤E(t)≤Emax, when △ t are Between variable quantity；
    The charge-discharge electric power P of day partE(t) meet：PE.min≤PE(t)≤PE.max,
    Then t periods system calling energy-storage system cost model is：CE(t)=kE(t)PE(t)。
  5. It is 5. according to claim 1 based on the uncertain wind-electricity integration coordination optimizing method contributed of wind-powered electricity generation, it is characterised in that Wind-powered electricity generation cost model is in described step 3：
    Wind power cost model includes two parts：When energy storage cost, second, schedulable load cost；Then：
    FW.jtTo be built wind power cost model, PWU.tOutput calculation model, ζ are not known for wind-powered electricity generationtOutput calculation is not known for wind-powered electricity generation Model coefficient.
  6. It is 6. according to claim 1 based on the uncertain wind-electricity integration coordination optimizing method contributed of wind-powered electricity generation, it is characterised in that Economic load dispatching object function and constraints in the step 3 are：
    Object function：
    Constraints：
    (1) power-balance constraint
    (2) unit power output constrains
    (3) ramping rate constraints
    (4) energy-storage system constrains
    Wherein, PG.itFor fired power generating unit units limits, FG.itFor fired power generating unit cost model, FW.jtTo be built wind power cost model, PW.jtTo be built wind power；E (t) be energy-storage system current state, Emin、EmaxRespectively energy storage system capacity bound.
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