CN114498611A - Wind power storage coordination control method considering wind power plant operation multiple targets - Google Patents

Wind power storage coordination control method considering wind power plant operation multiple targets Download PDF

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Publication number
CN114498611A
CN114498611A CN202111408545.2A CN202111408545A CN114498611A CN 114498611 A CN114498611 A CN 114498611A CN 202111408545 A CN202111408545 A CN 202111408545A CN 114498611 A CN114498611 A CN 114498611A
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energy storage
wind power
wind
bat
storage battery
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李国庆
褚孝国
陈卓
屠劲林
梁思超
李智伟
范晔
岳红轩
刘有金
段选锋
张小贝
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Huaneng Renewables Corp Ltd
Beijing Huaneng Xinrui Control Technology Co Ltd
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Huaneng Renewables Corp Ltd
Beijing Huaneng Xinrui Control Technology Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
    • H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy

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Abstract

The invention relates to a wind power storage coordination control method considering multiple targets of wind power plant operation, which takes wind power fluctuation quantity and economic benefit as optimization targets for a wind power plant configured with energy storage batteries, establishes a multi-target optimization model and constraint conditions under the wind power plant operation through designing an optimization configuration strategy, and performs actual wind power storage coordination control, so that wind power fluctuation is reduced, wind power grid-connected stability is improved, and the maximum economic benefit is achieved.

Description

Wind power storage coordination control method considering multiple targets of wind power plant operation
Technical Field
The invention relates to a wind power storage coordination control method considering multiple targets of wind power plant operation, and belongs to the technical field of wind power plant control.
Background
Wind power generation is intermittent and random, and large-scale grid connection brings voltage fluctuation, power fluctuation and other problems to a power system, and safe and stable operation of a power grid is influenced. In addition, with the continuous increase of the wind power proportion, the power grid dispatching can carry out wind abandoning and electricity limiting to a certain degree on the wind farm, so that the waste of wind energy is caused, and the income of the wind farm is reduced. In the research of wind storage coordination control, relatively more articles are provided in the aspect of scheduling strategies, and the two aspects of overall scheduling of a combined system and control of an energy storage system in the combined system are mainly focused. Regarding the aspect of overall scheduling of the wind storage combined system, the combined optimization control method of the wind storage system is provided by taking the maximum operation benefit of the wind storage combination as an optimization target. Regarding the control aspect of an energy storage system in a wind storage combined system, in order to enable wind storage grid-connected power to have good schedulability, a battery energy storage system optimization control method based on state quantity prediction is provided. However, at present, the multi-target wind storage coordination control on the operation of the wind power plant is still in a starting stage, and a certain model is not established yet.
Disclosure of Invention
The invention aims to solve the technical problem of providing a wind storage coordination control method considering multiple targets of wind power plant operation, and the wind storage coordination control method considering multiple targets of wind power plant operation can reduce wind power fluctuation and achieve optimal economic benefit.
In order to solve the technical problems, the invention adopts the following technical scheme: the invention designs a wind power storage coordination control method considering multiple targets of wind power plant operation, which is used for realizing wind power storage coordination control aiming at a wind power plant configured with an energy storage battery and comprises the following steps:
step A, obtaining the output power P of the wind power plant at each sampling moment t based on the sampling of the output power of the wind power plant at each sampling momentW(t) output power P at a time t-1 from its previous sampling instantW(t-1) and then entering step B;
b, respectively outputting power difference values delta P (t) at each sampling moment t based on the wind power plant, and the maximum charging power P of the energy storage batterybcmaxMaximum discharge power P of energy storage batterybdmaxLimit value P of output power fluctuation of wind power plant by power gridlimCharging the energy storage battery according to the condition that the delta P (t) is more than 0; Δ p (t) ═ 0, the energy storage cell is not charged or discharged; delta P (t) < 0, the energy storage battery performs discharging, and the charging and discharging power P of the energy storage battery at each sampling time t is constructedbat(t) modeling, then entering step C;
c, based on the charge and discharge power P of the energy storage battery at each sampling time tbat(t) establishing an energy storage capacity E of the energy storage battery at each sampling moment t by using a modelbat(t) modeling, then entering step D;
d, based on the charge and discharge power P of the energy storage battery at each sampling time tbat(t) model, energy storage capacity E of energy storage battery under each sampling time tbat(t) constructing a wind power storage coordination control economic benefit target by using the model, and then entering the step E;
e, constructing all constraint conditions corresponding to wind storage coordination control, including energy storage battery charging and discharging power constraint conditions, energy storage battery energy storage capacity constraint conditions, wind power plant output power constraint conditions and wind storage power balance constraint conditions, and then entering step F;
and F, aiming at the economic benefit target of the wind storage coordination control, combining all constraint conditions corresponding to the wind storage coordination control, and according to the charge and discharge power P of the energy storage battery at each sampling time tbat(t) model and energy storage capacity E of energy storage battery at each sampling time tbatAnd (t) the model realizes wind power storage coordination control aiming at the wind power plant configured with the energy storage battery.
As a preferred technical scheme of the invention: the method also comprises the following steps D-E, after the step D is executed, the step D-E is started;
D-E, based on the charging and discharging power P of the energy storage battery at each sampling time tbat(t) model, energy storage capacity E of energy storage battery under each sampling time tbat(t) constructing a wind storage coordination control wind power fluctuation target, and then entering the step E;
and step F, aiming at the economic benefit target of wind storage coordination control and the wind power fluctuation target of wind storage coordination control, combining all constraint conditions corresponding to the wind storage coordination control, and according to the charge and discharge power P of the energy storage battery at each sampling time tbat(t) model and energy storage capacity E of energy storage battery at each sampling time tbatAnd (t) the model realizes wind power storage coordination control aiming at the wind power plant configured with the energy storage battery.
As a preferred technical scheme of the invention: in the steps D-E, based on the charging and discharging power P of the energy storage battery at each sampling time tbat(t) model, energy storage capacity E of energy storage battery under each sampling time tbat(t) constructing a wind storage coordination control wind power fluctuation target minf2The following were used:
minf2＝Eδ
wherein E isδThe index of the stationarity of the output power of the wind power plant is represented,
Figure BDA0003373154280000031
Figure BDA0003373154280000032
n denotes the number of sampling instants, Δ t denotes the data sampling duration from the sampling instant, PNRepresenting a rated installed capacity of the wind farm; pw(t +1) represents the sampling time t + of the wind power plantOutput power at 1; pw(t)＝PWp(t)+Pbat(t)，PWp(t) represents the wind power forecast for the wind farm at the sampling time t.
As a preferred technical scheme of the invention: in the step B, the charge and discharge power P of the constructed energy storage battery at each sampling time tbat(t) model is as follows:
Figure BDA0003373154280000033
as a preferred technical scheme of the invention: in the step C, based on the charge and discharge power P of the energy storage battery at each sampling time tbat(t) establishing a storage energy capacity E of the energy storage battery at each sampling time t by using a modelbat(t) model is as follows:
Figure BDA0003373154280000034
wherein E isbat(t-1) represents the energy storage capacity, eta, of the energy storage battery at the sampling time t-1cRepresenting the charging efficiency of the energy storage battery, at represents the data sampling time length from the sampling moment, etadIndicating the discharge efficiency of the energy storage cell.
As a preferred technical scheme of the invention: in the step D, based on the charge and discharge power P of the energy storage battery at each sampling time tbat(t) model, energy storage capacity E of energy storage battery under each sampling time tbat(t) constructing a wind power storage coordination control economic benefit target maxf by using a model1The following were used:
maxf1＝Cw-Cbat
wherein, CwRepresenting the generation income of the wind power plant; cbatRepresents the operating cost of the energy storage battery;
Figure BDA0003373154280000035
n denotes the number of sampling instants, at denotes the data sampling duration from the sampling instant,pwrepresenting the corresponding on-line electricity price, P, of the wind power sitew(t)＝PWp(t)+Pbat(t)，PWp(t) representing a wind power predicted value of the wind power plant at a sampling time t; cbat＝pbatEbat(t)max，pbatRepresenting the cost of the energy storage capacity of the energy storage battery after conversion, Ebat(t)maxRepresenting the maximum energy storage capacity of the energy storage battery at the sampling instant t.
As a preferred technical scheme of the invention: in the step E, the energy storage battery charge and discharge power constraint conditions corresponding to the wind storage coordination control are constructed as follows:
-Pbdmax≤Pbat(t)≤Pbcmax；
the energy storage capacity constraint conditions of the energy storage battery are as follows:
Ebatmin≤Ebat(t)≤EbatN；
in the formula: ebatminIndicating the minimum energy storage capacity allowed for the energy storage cell, EbatNThe maximum energy storage capacity allowed by the energy storage battery is represented, namely the rated capacity of the energy storage battery;
the constraint conditions of the output power of the wind power plant are as follows:
Figure BDA0003373154280000041
wherein, PNRepresenting the rated installed capacity, P, of the wind farmw(t +1) represents the output power of the wind farm at sampling time t + 1.
As a preferred technical scheme of the invention: in the step E, the wind storage power balance constraint condition corresponding to the wind storage coordination control is constructed as follows:
PWp(t)+Pbat(t)＝Pwr(t)；
wherein, PWp(t) represents the predicted value of the wind power of the wind farm at the sampling time t, PwrAnd (t) represents the output power of the wind power plant at the sampling time t before the energy storage battery is not configured.
In view of the above, the present invention provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the wind farm operation multi-objective wind farm coordination control method when executing the computer program.
And to design a computer readable storage medium on which a computer program is stored which, when being executed by a processor, carries out the steps of the wind park coordination control method taking into account multiple objectives of wind park operation.
Compared with the prior art, the wind power storage coordination control method considering the multiple targets of the operation of the wind power plant has the following technical effects:
the invention designs a wind power storage coordination control method considering multiple targets of wind power plant operation, which takes the wind power fluctuation amount and economic benefit as optimization targets for a wind power plant configured with an energy storage battery, establishes a multi-target optimization model and constraint conditions under the wind power plant operation through designing an optimization configuration strategy, and performs actual wind power storage coordination control, so that the wind power fluctuation is reduced, the stability of wind power integration is improved, and the maximum economic benefit is achieved.
Drawings
FIG. 1 is a flow chart of a wind power storage coordination control method designed by the invention and considering multiple targets of wind power plant operation.
Detailed Description
The following description will explain embodiments of the present invention in further detail with reference to the accompanying drawings.
When the energy storage battery is applied to a wind power plant, the fluctuation of wind power is reduced, the storage and the release of electric energy depend on the fluctuation delta P of the wind power, and the specific charging and discharging strategy is as follows: and when the output power fluctuation delta P of the wind turbine generator is greater than 0, the energy storage battery is charged. If the electric quantity of the energy storage battery reaches the maximum capacity, the energy storage battery is not charged at the next moment. When the output power fluctuation delta P of the wind turbine generator is smaller than 0, the energy storage battery discharges, and if the electric quantity of the energy storage battery reaches the minimum capacity of the energy storage battery, the energy storage battery does not discharge any more at the next moment.
The invention designs a wind power storage coordination control method considering multiple targets of wind power plant operation, which is used for realizing wind power storage coordination control aiming at a wind power plant configured with an energy storage battery, and in practical application, as shown in figure 1, the following steps are specifically executed.
Step A, obtaining the output power P of the wind power plant at each sampling moment t based on the sampling of the output power of the wind power plant at each sampling momentW(t) output power P at a time t-1 from its previous sampling instantW(t-1) and then step B.
B, respectively outputting power difference values delta P (t) at each sampling moment t based on the wind power plant, and the maximum charging power P of the energy storage batterybcmaxMaximum discharge power P of energy storage batterybdmaxLimit value P of output power fluctuation of wind power plant by power gridlimCharging the energy storage battery according to the condition that the delta P (t) is more than 0; Δ p (t) ═ 0, the energy storage cell is not charged or discharged; delta P (t) < 0, the energy storage battery performs discharging, and the charging and discharging power P of the energy storage battery at each sampling time t is constructedbat(t) model is as follows:
Figure BDA0003373154280000051
then step C is entered.
C, based on the charge and discharge power P of the energy storage battery at each sampling time tbat(t) model, namely constructing the energy storage capacity E of the energy storage battery at each sampling moment tbat(t) model is as follows:
Figure BDA0003373154280000061
wherein E isbat(t-1) represents the energy storage capacity, eta, of the energy storage battery at the sampling time t-1cRepresenting the charging efficiency of the energy storage battery, at represents the data sampling time length from the sampling moment, etadRepresenting the discharge efficiency of the energy storage battery, and then entering the step D.
And D, step D.Based on charge and discharge power P of energy storage battery under each sampling time tbat(t) model, energy storage capacity E of energy storage battery under each sampling time tbat(t) constructing a wind power storage coordination control economic benefit target maxf by using a model1The following were used:
maxf1＝Cw-Cbat
wherein, CwRepresenting the generation income of the wind power plant; cbatRepresents the operating cost of the energy storage battery;
Figure BDA0003373154280000062
n denotes the number of sampling instants, Δ t denotes the data sampling duration from the sampling instant, pwRepresenting the corresponding on-line electricity price, P, of the wind power sitew(t)＝PWp(t)+Pbat(t)，PWp(t) representing a wind power predicted value of the wind power plant at a sampling time t;
Cbat＝pbatEbat(t)max，pbatrepresenting the cost of the energy storage capacity of the energy storage battery after conversion, Ebat(t)maxRepresenting the maximum energy storage capacity of the energy storage battery at the sampling time t, and then entering the step D-E.
D-E, based on the charge and discharge power P of the energy storage battery at each sampling moment tbat(t) model, energy storage capacity E of energy storage battery under each sampling time tbat(t) constructing a wind storage coordination control wind power fluctuation target minf2The following:
minf2＝Eδ
wherein E isδRepresenting the output power stability index of the wind power plant, selecting EδDescribing the fluctuation of the output power of the wind power plant, reflecting the fluctuation characteristic of the output power of the wind power plant in the inspected time window, wherein the smaller the value of the fluctuation is, the smaller the fluctuation is; on the contrary, the larger the fluctuation is,
Figure BDA0003373154280000063
n denotes the number of sampling instants, Δ t denotes the data sampling duration from the sampling instant, PNRepresenting a rated installed capacity of the wind farm; pw(t +1) represents the output power of the wind power plant at the sampling time t + 1; p isw(t)＝PWp(t)+Pbat(t)，PWpAnd (t) representing the wind power predicted value of the wind power plant at the sampling time t, and then entering the step E.
And E, constructing various constraint conditions corresponding to wind storage coordination control, including energy storage battery charging and discharging power constraint conditions, energy storage battery energy storage capacity constraint conditions, wind power plant output power constraint conditions and wind storage power balance constraint conditions, and then entering the step F.
In practical application, in the step E, the energy storage battery charge and discharge power constraint conditions corresponding to the wind storage coordination control are constructed as follows:
-Pbdmax≤Pbat(t)≤Pbcmax；
the energy storage capacity constraint conditions of the energy storage battery are as follows:
Ebatmin≤Ebat(t)≤EbatN；
in the formula: ebatminIndicating the minimum energy storage capacity allowed for the energy storage cell, EbatNThe maximum energy storage capacity allowed by the energy storage battery is represented, namely the rated capacity of the energy storage battery;
the constraint conditions of the output power of the wind power plant are as follows:
Figure BDA0003373154280000071
wherein, PNRepresenting the rated installed capacity, P, of the wind farmw(t +1) represents the output power of the wind farm at sampling time t + 1.
As a preferred technical scheme of the invention: in the step E, the wind storage power balance constraint condition corresponding to the wind storage coordination control is constructed as follows:
PWp(t)+Pbat(t)＝Pwr(t)；
wherein, PWp(t) represents the predicted value of the wind power of the wind farm at the sampling time t, Pwr(t) represents the power output of the wind power plant at the sampling time t before the energy storage battery is not configuredAnd (6) outputting power.
And F, taking a wind storage coordination control economic benefit target and a wind storage coordination control wind power fluctuation target as targets, combining all constraint conditions corresponding to the wind storage coordination control, and according to the charge and discharge power P of the energy storage battery at each sampling time tbat(t) model and energy storage capacity E of energy storage battery at each sampling time tbatAnd (t) the model realizes wind power storage coordination control aiming at the wind power plant configured with the energy storage battery.
The invention designs a wind storage coordination control method considering multiple targets of wind power plant operation, and when the method is applied to practice, a computer device is designed, wherein the computer device comprises a memory, a processor and a computer program which is stored in the memory and can be operated on the processor, and the processor realizes the steps of the wind storage coordination control method considering multiple targets of wind power plant operation when executing the computer program; meanwhile, a computer-readable storage medium is provided, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the wind park coordination control method taking into account multiple objectives of wind park operation.
According to the wind power storage coordination control method considering multiple targets of wind power plant operation, aiming at the wind power plant configured with the energy storage battery, the wind power fluctuation amount and the economic benefit are used as optimization targets, an optimization configuration strategy is designed, a multi-target optimization model and constraint conditions under the wind power plant operation are established, actual wind power storage coordination control is carried out, wind power fluctuation is reduced, meanwhile, the stability of wind power grid connection is improved, and the maximum economic benefit is achieved.
The embodiments of the present invention have been described in detail with reference to the drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.

Claims (10)

1. A wind power storage coordination control method considering multiple targets of wind power plant operation is used for realizing wind power storage coordination control aiming at a wind power plant configured with an energy storage battery, and is characterized by comprising the following steps:
step A, obtaining the output power P of the wind power plant at each sampling moment t based on the sampling of the output power of the wind power plant at each sampling momentW(t) output power P at a time t-1 from its previous sampling instantW(t-1) and then entering step B;
b, respectively outputting power difference values delta P (t) at each sampling moment t based on the wind power plant, and the maximum charging power P of the energy storage batterybcmaxMaximum discharge power P of energy storage batterybdmaxLimit value P of output power fluctuation of wind power plant by power gridlimCharging the energy storage battery according to the condition that the delta P (t) is more than 0; Δ p (t) ═ 0, the energy storage cell is not charged or discharged; delta P (t) < 0, the energy storage battery performs discharging, and the charging and discharging power P of the energy storage battery at each sampling time t is constructedbat(t) modeling, then entering step C;
c, based on the charge and discharge power P of the energy storage battery at each sampling time tbat(t) establishing an energy storage capacity E of the energy storage battery at each sampling moment t by using a modelbat(t) modeling, then entering step D;
d, based on the charge and discharge power P of the energy storage battery at each sampling time tbat(t) model, energy storage capacity E of energy storage battery under each sampling time tbat(t) constructing a wind power storage coordination control economic benefit target by using the model, and then entering the step E;
e, constructing all constraint conditions corresponding to wind storage coordination control, including energy storage battery charging and discharging power constraint conditions, energy storage battery energy storage capacity constraint conditions, wind power plant output power constraint conditions and wind storage power balance constraint conditions, and then entering step F;
and F, aiming at the economic benefit target of the wind storage coordination control, combining all constraint conditions corresponding to the wind storage coordination control, and according to the charge and discharge power P of the energy storage battery at each sampling time tbat(t) model and energy storage capacity E of energy storage battery at each sampling time tbatAnd (t) the model realizes wind power storage coordination control aiming at the wind power plant configured with the energy storage battery.
2. The wind power storage coordination control method considering wind power plant operation multiple targets is characterized by comprising the following steps of: the method also comprises the following steps D-E, after the step D is executed, the step D-E is started;
D-E, based on the charge and discharge power P of the energy storage battery at each sampling moment tbat(t) model, energy storage capacity E of energy storage battery under each sampling time tbat(t) constructing a wind storage coordination control wind power fluctuation target, and then entering the step E;
and step F, aiming at the economic benefit target of wind storage coordination control and the wind power fluctuation target of wind storage coordination control, combining all constraint conditions corresponding to the wind storage coordination control, and according to the charge and discharge power P of the energy storage battery at each sampling time tbat(t) model and energy storage capacity E of energy storage battery at each sampling time tbatAnd (t) the model is used for realizing wind power storage coordination control aiming at the wind power plant configured with the energy storage battery.
3. The wind power storage coordination control method considering wind power plant operation multiple targets is characterized by comprising the following steps of: in the steps D-E, based on the charge and discharge power P of the energy storage battery at each sampling time tbat(t) model, energy storage capacity E of energy storage battery under each sampling time tbat(t) constructing a wind storage coordination control wind power fluctuation target minf2The following were used:
minf2＝Eδ
wherein E isδThe index of the stability of the output power of the wind power plant is represented,
Figure RE-FDA0003576601500000021
n denotes the number of sampling instants, Δ t denotes the data sampling duration from the sampling instant, PNRepresenting a rated installed capacity of the wind farm; pw(t +1) represents the output power of the wind power plant at the sampling time t + 1; pw(t)＝PWp(t)+Pbat(t)，PWp(t) represents the wind power forecast for the wind farm at the sampling time t.
4. The wind power storage coordination control method considering wind power plant operation multiple targets is characterized by comprising the following steps of: in the step B, the charge and discharge power P of the constructed energy storage battery at each sampling time tbat(t) model is as follows:
Figure RE-FDA0003576601500000022
5. the wind power storage coordination control method considering wind power plant operation multiple targets is characterized by comprising the following steps of: in the step C, based on the charge and discharge power P of the energy storage battery at each sampling time tbat(t) establishing a storage energy capacity E of the energy storage battery at each sampling time t by using a modelbat(t) model is as follows:
Figure RE-FDA0003576601500000023
wherein E isbat(t-1) represents the energy storage capacity, eta, of the energy storage battery at the sampling time t-1cRepresenting the charging efficiency of the energy storage battery, at represents the data sampling time length from the sampling moment, etadIndicating the discharge efficiency of the energy storage cell.
6. The wind power storage coordination control method considering wind power plant operation multiple targets is characterized by comprising the following steps of: in the step D, based on the charge and discharge power P of the energy storage battery at each sampling time tbat(t) model, energy storage capacity E of energy storage battery under each sampling time tbat(t) constructing a wind power storage coordination control economic benefit target maxf by using a model1The following were used:
maxf1＝Cw-Cbat
wherein, CwRepresenting the generation income of the wind power plant; cbatRepresents the operating cost of the energy storage battery;
Figure RE-FDA0003576601500000031
n denotes the number of sampling instants, Δ t denotes the data sampling duration from the sampling instant, pwRepresenting the corresponding on-line electricity price, P, of the wind power sitew(t)＝PWp(t)+Pbat(t)，PWp(t) representing a wind power predicted value of the wind power plant at a sampling time t; cbat＝pbatEbat(t)max，pbatRepresenting the cost of the energy storage capacity of the energy storage battery after conversion, Ebat(t)maxRepresenting the maximum energy storage capacity of the energy storage battery at the sampling instant t.
7. The wind power storage coordination control method considering wind power plant operation multiple targets is characterized by comprising the following steps of: in the step E, the energy storage battery charge and discharge power constraint conditions corresponding to the wind storage coordination control are constructed as follows:
-Pbdmax≤Pbat(t)≤Pbcmax；
the energy storage capacity constraint conditions of the energy storage battery are as follows:
Ebatmin≤Ebat(t)≤EbatN；
in the formula: ebatminIndicating the minimum energy storage capacity allowed for the energy storage cell, EbatNThe maximum energy storage capacity allowed by the energy storage battery is represented, namely the rated capacity of the energy storage battery;
the constraint conditions of the output power of the wind power plant are as follows:
Figure RE-FDA0003576601500000032
wherein, PNRepresenting the rated installed capacity, P, of the wind farmw(t +1) represents the output power of the wind farm at sampling time t + 1.
8. The wind power storage coordination control method considering wind power plant operation multiple targets is characterized by comprising the following steps of: in the step E, the wind storage power balance constraint condition corresponding to the wind storage coordination control is constructed as follows:
PWp(t)+Pbat(t)＝Pwr(t)；
wherein, PWp(t) represents the predicted value of the wind power of the wind farm at the sampling time t, PwrAnd (t) represents the output power of the wind power plant at the sampling time t before the energy storage battery is not configured.
9. Computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor, when executing the computer program, implements the steps of the wind park coordination control method considering wind park operation multiple objectives as claimed in any one of claims 1 to 8.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method for coordinated control of wind park according to any one of claims 1 to 8, taking into account multiple objectives of operation of the wind park.
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