CN110932301B - Method for improving wind power acceptance capacity based on participation of battery energy storage - Google Patents

Method for improving wind power acceptance capacity based on participation of battery energy storage Download PDF

Info

Publication number
CN110932301B
CN110932301B CN201911322354.7A CN201911322354A CN110932301B CN 110932301 B CN110932301 B CN 110932301B CN 201911322354 A CN201911322354 A CN 201911322354A CN 110932301 B CN110932301 B CN 110932301B
Authority
CN
China
Prior art keywords
energy storage
power
battery energy
soc
storage unit
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201911322354.7A
Other languages
Chinese (zh)
Other versions
CN110932301A (en
Inventor
滕云
刘硕
左浩
孙鹏
王泽镝
袁元缘
张俊久
弓玮
吴磊
钟磊
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenyang University of Technology
Original Assignee
Shenyang University of Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shenyang University of Technology filed Critical Shenyang University of Technology
Priority to CN201911322354.7A priority Critical patent/CN110932301B/en
Publication of CN110932301A publication Critical patent/CN110932301A/en
Application granted granted Critical
Publication of CN110932301B publication Critical patent/CN110932301B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/76—Power conversion electric or electronic aspects
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E70/00—Other energy conversion or management systems reducing GHG emissions
    • Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Supply And Distribution Of Alternating Current (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

The invention discloses a method for improving wind power receiving capacity based on participation of battery energy storage, which belongs to the technical field of power grid energy control. And on the premise of constraining the charging and discharging power and the state of charge (SOC) of the battery energy storage unit, introducing a charging optimization coefficient and a discharging optimization coefficient, optimizing the charging and discharging power of the whole battery energy storage device when the wind power of the power distribution network fluctuates to obtain the optimal charging and discharging power of the battery energy storage device when the wind power of the power distribution network fluctuates, so as to improve the wind power receiving capacity of the whole battery energy storage device.

Description

Method for improving wind power acceptance capacity based on participation of battery energy storage
Technical Field
The invention relates to the technical field of power grid energy control, in particular to a method for improving wind power acceptance capacity based on participation of battery energy storage.
Background
With the shortage of energy resources and the increase of the requirement for the environment, the development and utilization of clean energy for power generation become a hot spot of current research. The wind power generation has the greatest renewable energy development and application prospect as the wind power generation with mature technology in the development and utilization of the renewable clean energy at present. The fans in China are mainly distributed in the 'three-north' areas (northwest, northeast and north China) with rich wind power resources, but wind power output has the characteristics of uncertainty, randomness, intermittence and the like, so that the interference on the voltage, current, frequency, electric energy quality and the like of a power distribution network is generated, the problem of serious wind abandon is caused, and the wind power acceptance of the power distribution network is reduced.
Aiming at the problems of wind power generation, in the prior art, wind power receiving capacity is improved by technical methods such as configuring a large-capacity battery energy storage device, constructing a branch delivery channel, a hydrogen storage technology and a pumped storage technology, and for improving the wind power receiving capacity by the battery energy storage technology, the method mainly comprises the steps of improving a system power supply structure, such as newly building a flexible regulation power supply, a pumped storage power station and the like; secondly, the intelligent power grid technology is adopted, so that the operation level of a battery energy storage device in the power grid is improved; and thirdly, carrying out wind power prediction and load demand side management to carry out combined planning and optimal configuration on the battery energy storage device. The method for improving the system power supply structure can increase the investment cost and the operation cost of the power system, consume a large amount of resources and increase the operation difficulty of the power system; by adopting the smart grid technology, the smart grid technology is configured with an unsound power system, so that the technical limitation defect is generated, and the battery energy storage resource cannot be mobilized in an all-around manner; wind power prediction and demand side management cannot accurately achieve full wind power admission of the battery energy storage device during wind power fluctuation, wind power prediction is relatively large, and load demand side management has relatively large uncertainty.
The method for improving the wind power receiving capacity based on the participation of the battery energy storage can optimize the existing battery energy storage device on the basis of the existing battery energy storage device, does not increase the investment cost and the operation cost, does not change the existing power grid structure, increases the system operation scheduling difficulty, and does not have the limitation of technical bottlenecks. When wind power fluctuates, the method avoids the influence caused by wind power errors by calculating the unbalanced power of the wind power fluctuation, and can better improve the wind power receiving capacity. The method can well solve the disadvantages.
Disclosure of Invention
In view of the above deficiencies of the prior art, the present application provides a method for improving wind power acceptance based on battery energy storage participation.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: a method for improving wind power receiving capacity based on participation of battery energy storage is disclosed, the flow of which is shown in figure 1, and the method comprises the following steps:
step 1: the SOC value of the whole battery energy storage device is obtained by calculating the SOC parameter of the battery energy storage unit, and the charging and discharging capacity of the battery energy storage device is judged when wind power fluctuates;
step 1.1: calculating the SOC value of each energy storage unit:
Figure BDA0002327476320000021
therein, SOCBi(t) represents the SOC value of the ith unit in the battery energy storage device when the ith unit is charged and discharged at the time t, and the SOC value of the ith unit in the battery energy storage device can be measured by a measuring device when t is 0; f. ofBichAnd fBifRespectively representing the charge-discharge zone bit of the ith battery energy storage unit during chargingBich＝1、f Bif0, at discharge time fBich＝0、fBif＝1；PBi(t) represents the charging and discharging power of the ith battery energy storage unit at the moment t; eBiRepresenting the capacity of the ith battery energy storage unit; etach、ηf、ηtransRespectively representing the charging efficiency and the discharging efficiency of the battery energy storage unit and the battery energy storageConverter efficiency; delta t is the energy storage charging and discharging time of the battery;
step 1.2: calculating the overall SOC value of the whole battery energy storage device as follows:
Figure BDA0002327476320000022
therein, SOCB(t) represents the overall SOC value of the whole battery energy storage device at time t; n represents the number of energy storage units contained in the whole battery energy storage device; w is aiA weighting value is calculated for the individual energy storage unit SOC values.
Step 2: the charge and discharge power of each energy storage unit of the battery energy storage device is distributed and calculated by calculating the wind power fluctuation unbalanced power of the power distribution network when the wind power fluctuates;
step 2.1: calculating wind power fluctuation unbalance power delta P (t):
ΔP(t)＝PF(t)-PG(t)-PL(t)
wherein, PF(t) represents wind power generation output power; pG(t) represents the power of the power distribution network exchange electric energy; pL(t) represents the electrical power used by the conventional load;
step 2.2: and (3) performing charge and discharge power distribution calculation on the battery energy storage device according to the calculated unbalanced power delta P (t):
ΔPi(t)＝Kh(fBich(SOCBi,max-SOCBi(t))+fBif(SOCBi(t)-SOCBi,min))ΔPhi
Figure BDA0002327476320000023
Figure BDA0002327476320000024
Figure BDA0002327476320000025
wherein, Δ Pi(t) distributing the unbalanced power of the wind power distribution network to the power of the ith energy storage unit; khThe proportion coefficient is distributed; SOCBi,maxAnd SOCBi,minRespectively representing the maximum value and the minimum value of the SOC value of the ith battery energy storage unit; delta PhiDistributing reference values for the power of each energy storage unit; eiminAnd EimaxThe minimum and maximum allowable remaining charge for the ith battery energy storage unit, respectively.
And step 3: calculating the maximum charge-discharge power of the battery energy storage unit when the battery energy storage fluctuates along with wind power, and constraining the charge-discharge power and the state of charge (SOC) of the battery energy storage unit;
step 3.1: calculating the maximum charging and discharging power of the ith unit of the battery energy storage device:
Figure BDA0002327476320000031
wherein, Pich,max(t) and Pif,max(t) the maximum charging power and the maximum discharging power of the ith battery energy storage unit at the moment t respectively; eBi(t-1) is the residual electric quantity at the moment immediately before the ith battery energy storage unit is charged and discharged, namely the moment t-1;
step 3.2: charging power P of ith battery energy storage unit at time tich(t) discharge Power Pif(t) and energy storage cell SOCBi(t) constraints to be satisfied:
Figure BDA0002327476320000032
Figure BDA0002327476320000033
wherein, Pich(t) and Pif(t) charging power and discharging power, SOC, of the ith battery energy storage unit at time tBiAnd (t) is the SOC value of the ith battery energy storage unit at the moment t.
And 4, step 4: introducing a charge optimization coefficient schAnd discharge optimization coefficient sfAnd calculating the optimized charging and discharging power of the battery energy storage device on the basis of the unbalanced wind power distribution power distributed by each unit of the battery energy storage device, and optimizing the charging and discharging power of the battery energy storage device to improve the wind power receiving capacity.
Step 4.1: calculating a charge optimization coefficient schAnd discharge optimization coefficient sf：
Figure BDA0002327476320000034
Step 4.2: under the condition of satisfying the constraint condition in the step 3, introducing a battery random optimization coefficient M to perform random sliding on the time t, wherein the method for performing random sliding on the time t is to add or subtract t
Figure BDA0002327476320000041
And then optimizing the wind power unbalance power of the battery energy storage device in the M-1 time period, wherein the optimized charging and discharging power of the battery energy storage device is as follows:
Figure BDA0002327476320000042
wherein, PBS(t) is the charge-discharge power of the battery energy storage device after optimization; delta Pi(t) the unbalanced power of the power distribution network containing wind power distributed by the ith battery energy storage unit; and M is a random optimization coefficient of the battery, and the value of M is an odd number greater than 1.
And 5: calculating the wind power receiving capacity of the power distribution network:
Figure BDA0002327476320000043
ΔP'(t)＝PF(t)-PG(t)-PL(t)-PBS(t)
ΔP*(t)＝PF(t)-PG(t)-PL(t)-PB(t)
wherein, delta' represents the proportion of the difference value of the power of the battery energy storage used for the wind power to accept the charging and discharging to the wind power; delta*The ratio of the difference value of the wind power receiving charge and discharge power of the battery energy storage without adopting the method to the wind power, namely delta P' (t) and delta P (t)*And (t) respectively representing the difference value of the power of the battery energy storage adopting the method after the wind power receiving charge and discharge and the difference value of the power of the battery energy storage not adopting the method after the wind power receiving charge and discharge.
Adopt the produced beneficial effect of above-mentioned technical scheme to lie in:
1. according to the method for calculating the SOC parameter of the whole battery energy storage device in the step 1, the SOC parameter of the whole battery energy storage device at the current moment is accurately calculated, so that the charging and discharging capacity of the battery energy storage device for improving the wind power receiving capacity can be judged in advance, and the wind power fluctuation unbalanced power of a power distribution network during wind power fluctuation can be better distributed and calculated;
2. according to the wind power fluctuation unbalanced power distribution calculation method of the whole battery energy storage device in the power distribution network wind power fluctuation in the step 2, wind power fluctuation unbalanced power in the power distribution network wind power fluctuation is calculated, and then the calculated wind power fluctuation unbalanced power is judged to be distributed and calculated according to the charging and discharging capacity of each battery energy storage unit, so that each energy storage unit in the battery energy storage device can receive wind power with the maximum charging and discharging capacity;
3. according to the maximum charge-discharge power and SOC parameter constraint calculation method for the whole battery energy storage device in the step 3, the maximum charge-discharge power and the maximum SOC parameter value and the minimum SOC parameter value of each unit of the battery energy storage device are calculated, so that the charge-discharge capacity of the whole battery energy storage device is constrained when the wind power of a power distribution network fluctuates, each energy storage unit can better receive the wind power, and a foundation is laid for realizing the optimal wind power receiving of the whole battery energy storage device;
4. according to the charging and discharging power calculation method after the whole battery energy storage device is optimized during the wind power fluctuation of the power distribution network in the step 4, the charging and discharging power of the whole battery energy storage device during the wind power fluctuation of the power distribution network is optimized by introducing the charging optimization coefficient and the discharging optimization coefficient, so that the optimal charging and discharging power of the battery energy storage device during the wind power fluctuation of the power distribution network is obtained, and the wind power receiving capacity of the whole battery energy storage device is improved;
5. according to the method for calculating the wind power receiving capacity of the whole battery energy storage device during the wind power fluctuation of the power distribution network in the step 5, the ratio of the difference value of the power of the battery energy storage device which is used for receiving the charging and discharging of the wind power and the power of the battery energy storage device which is not used in the method to the wind power is calculated and compared to the ratio of the power of the battery energy storage device which is used in the method to the wind power receiving capacity to the wind power is judged, and the degree of improving the wind power receiving capacity based on the participation of the battery energy storage is judged so as to show that the method has a remarkable effect on improving the wind power receiving capacity.
Drawings
FIG. 1 is a flow chart of a method for improving wind power acceptance capability based on battery energy storage participation in accordance with the present invention;
FIG. 2 is a comparison graph before and after optimization of wind power received by the battery energy storage in the embodiment of the invention;
FIG. 3 is a comparison graph before and after the battery energy storage and wind power receiving power difference ratio is optimized in the embodiment of the invention.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
In this embodiment, wind power generation with a rated capacity of 2.5MW, power distribution network exchange electric energy power actual measurement data and conventional load actual measurement data are selected in a certain area, and the rated powers and the rated capacities of 4 energy storage units of a battery energy storage device configured in a power distribution network system are 1.5MW and 6 MWh. Efficiency eta of battery energy storage convertertrans95%, and the charging efficiency eta of each energy storage unit of the battery energy storage devicech85%, discharge efficiency etaf85 percent. Setting a battery energy storage device to be in a charging state at a starting time, Kh＝0.8，M＝3。
Setting a battery energy storage device start timeIn the charged state, i.e. fBich＝1、f Bif0. And the battery energy storage charging and discharging time delta t is 0.1 h. Simultaneously, the SOC value of each battery energy storage unit of 0h is detected to be SOC through a measuring deviceB1(0)＝0.3、SOCB2(0)＝0.4、SOCB3(0)＝0.5、SOCB4(0)＝0.6。
As shown in fig. 1, the method of the present embodiment is as follows.
Step 1: the SOC value of the whole battery energy storage device is obtained by calculating the SOC parameter of the battery energy storage unit, and the charging and discharging capacity of the battery energy storage device is judged when wind power fluctuates;
step 1.1: and calculating the SOC value of each energy storage unit when t is 0.1 h:
Figure BDA0002327476320000061
obtaining SOCB1(0.1)＝0.51，SOCB2(0.1)＝0.43，SOCB3(0.1)＝0.56，SOCB4(0.1)＝0.61
Step 1.2: when t is 0.1h, the SOC value of the whole battery energy storage device is calculated as follows:
Figure BDA0002327476320000062
therein, SOCB(t) represents the overall SOC value of the whole battery energy storage device at time t; n-4 represents the number of energy storage units contained in the whole battery energy storage device; w is aiA weighting value is calculated for the individual energy storage unit SOC values.
Step 2: the charge and discharge power of each energy storage unit of the battery energy storage device is distributed and calculated by calculating the wind power fluctuation unbalanced power of the power distribution network when the wind power fluctuates;
step 2.1: calculating wind power fluctuation unbalance power delta P (t) when t is 0.1 h:
ΔP(t)＝PF(t)-PG(t)-PL(t)
wherein, PF(t) wind power generationOutputting power; pG(t) represents the power of the power distribution network exchange electric energy; pL(t) represents the electrical power used by the conventional load;
step 2.2: and (3) performing charge and discharge power distribution calculation on the battery energy storage device according to the calculated unbalanced power delta P (0.1):
ΔPi(t)＝Kh(fBich(SOCBi,max-SOCBi(t))+fBif(SOCBi(t)-SOCBi,min))ΔPhi
Figure BDA0002327476320000063
Figure BDA0002327476320000064
Figure BDA0002327476320000065
wherein, Δ Pi(t) distributing the unbalanced power of the wind power distribution network to the power of the ith energy storage unit; khThe proportion coefficient is distributed; SOCBi,maxAnd SOCBi,minRespectively representing the maximum value and the minimum value of the SOC value of the ith battery energy storage unit; delta PhiDistributing reference values for the power of each energy storage unit; eiminAnd EimaxThe minimum and maximum allowable remaining charge for the ith battery energy storage unit, respectively.
And step 3: calculating the maximum charge-discharge power of the battery when the battery energy storage fluctuates along with the wind power when t is 0.1h, and constraining the charge-discharge power and the state of charge (SOC) of the battery energy storage unit;
step 3.1: calculating the maximum charging and discharging power of the ith unit of the battery energy storage device:
Figure BDA0002327476320000071
wherein, Pich,max(t) andPif,max(t) the maximum charging power and the maximum discharging power of the ith battery energy storage unit at the moment t respectively; eBi(t-1) is the residual electric quantity at the moment immediately before the ith battery energy storage unit is charged and discharged, namely the moment t-1;
step 3.2: when t is 0.1h, the charging power P of the ith battery energy storage unitich(t) discharge Power Pif(t) and energy storage cell SOCBi(t) constraints to be satisfied:
Figure BDA0002327476320000072
Figure BDA0002327476320000073
wherein, Pich(t) and Pif(t) charging power and discharging power, SOC, of the ith battery energy storage unit at time tBiAnd (t) is the SOC value of the ith battery energy storage unit at the moment t.
And 4, step 4: introducing a charge optimization coefficient schAnd discharge optimization coefficient sfAnd calculating the optimized charging and discharging power of the battery energy storage device on the basis of the unbalanced wind power distribution power distributed by each unit of the battery energy storage device, and optimizing the charging and discharging power of the battery energy storage device to improve the wind power receiving capacity.
Step 4.1: calculating the charge optimization coefficient s when t is 0.1hchAnd discharge optimization coefficient sf：
Figure BDA0002327476320000074
Step 4.2: under the condition of satisfying the constraint condition in step 3, introducing a battery random optimization coefficient M-3 to perform a random sliding on the time t-0.1 h, wherein the method for performing a random sliding on the time t is to add or subtract t
Figure BDA0002327476320000081
Then to M-1Wind power unbalance power of the battery energy storage device in the period is optimized, and the charge and discharge power after the battery energy storage device is optimized is as follows:
Figure BDA0002327476320000082
sch＝SOCBi,max-SOCBi(0)
wherein, PBS(t) is the charge-discharge power of the battery energy storage device after optimization; delta Pi(t) the unbalanced power of the power distribution network containing wind power distributed by the ith battery energy storage unit; and M is a random optimization coefficient of the battery, and the value of M is an odd number greater than 1.
And 5: and calculating the wind power receiving capacity of the power distribution network when t is 0.1 h:
Figure BDA0002327476320000083
Figure BDA0002327476320000084
calculating the optimized charge and discharge power P of the battery energy storage device with t equal to 0.2,0.3,0.4, … and 24h in sequence according to the stepsBS(t) (t ═ 0.2,0.3,0.4, …,24), and calculating the wind power receiving capacity of the distribution network, and obtaining:
Figure BDA0002327476320000085
Figure BDA0002327476320000086
Figure BDA0002327476320000087
the calculation process is simulated by using an Mtalab software programming program, results before and after optimization are compared as shown in figures 2 and 3, after the battery energy storage is subjected to new charge and discharge quantitative improvement by adopting the method disclosed by the invention, the charge and discharge power of the battery energy storage is closer to the unbalanced power of the system wind power, the wind power receiving proportion of a power distribution network is obviously improved, the power difference proportion after optimization is obviously lower than the proportion when the optimization is not carried out, and the wind power receiving capacity of the power distribution network system is improved by the method disclosed by the invention.

Claims (2)

1. A method for improving wind power receiving capacity based on participation of battery energy storage is characterized by comprising the following steps:
step 1: the SOC value of the whole battery energy storage device is obtained by calculating the SOC parameter of the battery energy storage unit, and the charging and discharging capacity of the battery energy storage device is judged when wind power fluctuates, wherein the process is as follows;
step 1.1: calculating the SOC value of each energy storage unit:
Figure FDA0003254564590000011
therein, SOCBi(t) represents the SOC value of the ith unit in the battery energy storage when the ith unit is charged and discharged at the time t; f. ofBichAnd fBifRespectively representing the charge-discharge zone bit of the ith battery energy storage unit during chargingBich＝1、fBif0, at discharge time fBich＝0、fBif＝1；PBi(t) represents the charging and discharging power of the ith battery energy storage unit at the moment t; eBiRepresenting the capacity of the ith battery energy storage unit; etach、ηf、ηtransRespectively representing the charging efficiency and the discharging efficiency of the battery energy storage unit and the efficiency of the battery energy storage converter; delta t is the energy storage charging and discharging time of the battery;
step 1.2: calculating the overall SOC value of the whole battery energy storage device as follows:
Figure FDA0003254564590000012
therein, SOCB(t) represents the overall SOC value of the whole battery energy storage device at time t; n represents the number of energy storage units contained in the whole battery energy storage device; w is aiCalculating a weighted value for the SOC value of the single energy storage unit;
step 2: the method comprises the steps of calculating the wind power fluctuation unbalanced power of a power distribution network when wind power fluctuates, and performing distribution calculation on the charge and discharge power of each energy storage unit of a battery energy storage device, wherein the process is as follows;
step 2.1: calculating wind power fluctuation unbalance power Delta P (t):
△P(t)＝PF(t)-PG(t)-PL(t)
wherein, PF(t) represents wind power generation output power; pG(t) represents the power of the power distribution network exchange electric energy; pL(t) represents the electrical power used by the conventional load;
step 2.2: and (3) performing charge and discharge power distribution calculation on the battery energy storage device according to the calculated unbalanced power delta P (t):
△Pi(t)＝Kh(fBich(SOCBi,max-SOCBi(t))+fBif(SOCBi(t)-SOCBi,min))△Phi
Figure FDA0003254564590000013
Figure FDA0003254564590000021
Figure FDA0003254564590000022
wherein, Δ Pi(t) distributing the unbalanced power of the wind power distribution network to the power of the ith energy storage unit; khThe proportion coefficient is distributed; SOCBi,maxAnd SOCBi,minRespectively represent the ith battery energy storage unitMaximum value and minimum value of SOC value; delta PhiDistributing reference values for the power of each energy storage unit; eiminAnd EimaxRespectively allowing the minimum and maximum residual electric quantity for the ith battery energy storage unit;
and step 3: calculating the maximum charge-discharge power of the battery energy storage unit when the battery energy storage fluctuates along with wind power, and constraining the charge-discharge power and the state of charge (SOC) of the battery energy storage unit, wherein the process is as follows;
step 3.1: calculating the maximum charging and discharging power of the ith unit of the battery energy storage device:
Figure FDA0003254564590000023
wherein, Pich,max(t) and Pif,max(t) the maximum charging power and the maximum discharging power of the ith battery energy storage unit at the moment t respectively; eBi(t-1) is the residual electric quantity at the moment immediately before the ith battery energy storage unit is charged and discharged, namely the moment t-1;
step 3.2: charging power P of ith battery energy storage unit at time tich(t) discharge Power Pif(t) and energy storage cell SOCBi(t) constraints to be satisfied:
Figure FDA0003254564590000024
Figure FDA0003254564590000025
wherein, Pich(t) and Pif(t) charging power and discharging power, SOC, of the ith battery energy storage unit at time tBi(t) is the SOC value of the ith battery energy storage unit at the moment t;
and 4, step 4: introducing a charge optimization coefficient schAnd discharge optimization coefficient sfCalculating the advantages of the battery energy storage device based on the wind power unbalanced distribution power distributed by each unit of the battery energy storage deviceThe changed charge and discharge power optimizes the charge and discharge power of the battery energy storage device to improve the wind power receiving capacity, and the process is as follows:
step 4.1: calculating a charge optimization coefficient schAnd discharge optimization coefficient sf：
Figure FDA0003254564590000031
Step 4.2: introducing a battery random optimization coefficient M to perform random sliding on time t under the constraint condition in the step 3, and then optimizing the wind power unbalanced power of the battery energy storage device in the M-1 time period, wherein the optimized charging and discharging power of the battery energy storage device is as follows:
Figure FDA0003254564590000032
wherein, PBS(t) is the charge-discharge power of the battery energy storage device after optimization; delta Pi(t) distributing the unbalanced power of the wind power distribution network to the power of the ith energy storage unit; and M is a random optimization coefficient of the battery, and the value of M is an odd number greater than 1.
2. The method for improving wind power acceptance capacity based on participation of battery energy storage according to claim 1, characterized in that: the method for performing a random sliding on the time t is to add or subtract t
Figure FDA0003254564590000033
CN201911322354.7A 2019-12-20 2019-12-20 Method for improving wind power acceptance capacity based on participation of battery energy storage Active CN110932301B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201911322354.7A CN110932301B (en) 2019-12-20 2019-12-20 Method for improving wind power acceptance capacity based on participation of battery energy storage

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201911322354.7A CN110932301B (en) 2019-12-20 2019-12-20 Method for improving wind power acceptance capacity based on participation of battery energy storage

Publications (2)

Publication Number Publication Date
CN110932301A CN110932301A (en) 2020-03-27
CN110932301B true CN110932301B (en) 2021-11-16

Family

ID=69864473

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201911322354.7A Active CN110932301B (en) 2019-12-20 2019-12-20 Method for improving wind power acceptance capacity based on participation of battery energy storage

Country Status (1)

Country Link
CN (1) CN110932301B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113612272B (en) * 2021-07-19 2024-01-02 科华数据股份有限公司 Charging control method and device for uninterruptible power supply of new energy power generation system

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2014167928A1 (en) * 2013-04-12 2014-10-16 三菱電機株式会社 Storage battery charge/discharge control device and storage battery charge/discharge control method
CN104882897A (en) * 2015-06-18 2015-09-02 中国电力科学研究院 Active power optimal dispatching method for suppressing photovoltaic power fluctuation
CN105262117A (en) * 2015-11-12 2016-01-20 四川大学 Wind power climbing optimization control method
CN107465204A (en) * 2017-08-31 2017-12-12 中国电力科学研究院 More battery power optimizing distribution methods and device in a kind of energy-accumulating power station
CN109888874A (en) * 2019-03-14 2019-06-14 珠海吉瓦科技有限公司 A kind of energy-storage system power distribution optimization method based on active volume

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2014167928A1 (en) * 2013-04-12 2014-10-16 三菱電機株式会社 Storage battery charge/discharge control device and storage battery charge/discharge control method
CN104882897A (en) * 2015-06-18 2015-09-02 中国电力科学研究院 Active power optimal dispatching method for suppressing photovoltaic power fluctuation
CN105262117A (en) * 2015-11-12 2016-01-20 四川大学 Wind power climbing optimization control method
CN107465204A (en) * 2017-08-31 2017-12-12 中国电力科学研究院 More battery power optimizing distribution methods and device in a kind of energy-accumulating power station
CN109888874A (en) * 2019-03-14 2019-06-14 珠海吉瓦科技有限公司 A kind of energy-storage system power distribution optimization method based on active volume

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
基于风电消纳时序场景的电池储能系统配置策略;蔡霁霖 等;《高电压技术》;20190331;第45卷(第3期);全文 *
电池储能系统用于风电功率部分"削峰填谷"控制及容量配置;靳文涛 等;《中国电力》;20130831;第46卷(第8期);全文 *

Also Published As

Publication number Publication date
CN110932301A (en) 2020-03-27

Similar Documents

Publication Publication Date Title
CN108667052B (en) Multi-type energy storage system planning configuration method and system for virtual power plant optimized operation
CN112163700A (en) Electrochemical energy storage power station planning method considering cycle life of energy storage battery
CN113326467B (en) Multi-target optimization method, storage medium and optimization system for multi-station fusion comprehensive energy system based on multiple uncertainties
CN112736952A (en) Calendar life-considered capacity optimization method for offshore wind power configuration energy storage system
CN116365506A (en) Energy-saving and loss-reducing optimization method and system for active power distribution network containing distributed photovoltaic
CN111313444A (en) Energy storage system optimal configuration method for high-density photovoltaic distribution network side
CN110932301B (en) Method for improving wind power acceptance capacity based on participation of battery energy storage
CN114123280A (en) Battery energy storage power station energy management method considering system efficiency
CN114362153A (en) Multi-target capacity optimal configuration method and system for grid-connected wind-solar energy storage system
CN109245143B (en) Energy storage peak regulation power station optimized operation method considering lithium ion battery service life
CN112365299A (en) Comprehensive energy source electricity/heat mixed energy storage configuration method considering battery life loss
CN111525597A (en) Method for optimizing double-battery imbalance state in wind storage combined system
CN115940284B (en) Operation control strategy of new energy hydrogen production system considering time-of-use electricity price
CN116885761A (en) Capacity optimization method for power-energy hybrid energy storage system
CN117114281A (en) Determination method of flexible resource multi-stage planning scheme
CN115642620A (en) Double-layer optimization method for energy storage participation low-carbon flexible peak regulation
Gaetani-Liseo et al. Identification of ESS Degradations Related to their Uses in Micro-Grids: application to a building lighting network with VRLA batteries
CN108183498B (en) Vehicle storage hybrid configuration method under background of wind and light containing storage and distribution power grid
CN112861376A (en) Unit scheduling model-based assessment method and device
Shi et al. Optimal Configuration of Battery Energy Storage System in Bus Charging Station Considering Load Uncertainty
CN114019382B (en) Method and system for determining service life attenuation of lithium ion battery energy storage power station
CN116896096B (en) Low-carbon optimal operation method and system for power distribution network containing energy storage equipment
Gao et al. Optimal configuration of industrial user-side energy storage considering power demand income in life cycle
CN112039057B (en) Low-voltage treatment method based on two-stage scheduling
CN112039129B (en) Wind power output guarantee rate determination method and system based on energy storage optimization configuration

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant