CN107834580A - One kind reduces network load peak valley difference method based on battery energy storage - Google Patents
One kind reduces network load peak valley difference method based on battery energy storage Download PDFInfo
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- CN107834580A CN107834580A CN201710996851.XA CN201710996851A CN107834580A CN 107834580 A CN107834580 A CN 107834580A CN 201710996851 A CN201710996851 A CN 201710996851A CN 107834580 A CN107834580 A CN 107834580A
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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
- H02J3/28—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
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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
- 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]
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- 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
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Abstract
Network load peak valley difference method is reduced based on battery energy storage the invention discloses one kind, belongs to power system automatic field.Seek the method for optimal reduction power network peak-valley difference using battery energy storage, it is monitored and records for the data of possible influence factor layer and direct acting factor layer, and then draw peak regulation coefficient, then introduce certainty factor, and then build and draw direct acting factor destination layer, draw battery charging and discharging power.The present invention gives full play to electric energy storage technology advantage, play reduction peak-valley difference effect of the electric energy storage in Operation of Electric Systems, and the permanent mechanism established and promote regenerative resource consumption can be promoted, electric energy storage facility is run by scientific dispatch, plays the effect in terms of battery energy storage reduces peak-valley difference.
Description
Technical Field
The invention belongs to the field of power system automation, and relates to a method for reducing load peak-valley difference of a power grid based on battery energy storage.
Background
The battery energy storage has the advantages of high response speed, no geographic condition limitation and the like, and is more and more widely applied to power systems. At present, the load peak-valley difference of a power grid in some areas is large, which can cause frequent start and stop of a unit and reduction of operation efficiency, the power supply reliability is also reduced, and the power failure risk of a user is increased. The method for carrying out peak clipping and valley filling by using a battery energy storage technology is an effective way for solving the phenomenon.
In China, energy storage modes such as lead-carbon batteries, lithium ion batteries and all-vanadium redox flow batteries exist, however, various short plates exist in various energy storage modes in the aspects of environmental protection, cost, economy, sustainability and the like, and most of the energy storage modes do not enter a large-scale application stage, so thermal power is still a main peak regulation mode of new energy; and almost all AGC frequency modulation power supplies in the power grid are thermal power generating units. At present, in a large number of new energy power generation projects all over the country, the phenomenon of electricity abandonment of the power grid is severe day by day, wherein the construction loss of energy storage equipment is one of important factors influencing the incapability of successfully surfing the Internet in the new energy power generation.
For the operation control problem of reducing the peak-valley difference of the energy storage battery system in the power system, research and discussion are carried out in the prior art, and the prior art 1: a dynamic programming-based real-time optimization method for peak clipping and valley filling of a battery energy storage system (2012, 36 th volume 12 of an electric power system) provides a dynamic programming-based real-time correction optimization control strategy, discontinuous constraint conditions such as charging and discharging frequency limitation and discharging depth limitation can be introduced into an optimization model, and the peak clipping and valley filling real-time control method is provided by combining the influences of the charging and discharging frequency and the discharging depth of the battery on the service life of the battery based on the dynamic programming. Prior art 2: in the research on constant-power peak clipping and valley filling optimization strategies of battery energy storage systems (vol. 36, no. 9 of the power grid technology), a constant-power peak clipping and valley filling optimization model of the battery energy storage system and a practical simplified algorithm for solving the model are provided with the background of MW-level battery energy storage demonstration engineering of a southern power grid and the aim of solving the peak clipping and valley filling strategies of the battery energy storage system which operates by adopting a constant-power charge-discharge strategy. And a constant-power peak clipping and valley filling optimization model is established for 2 groups of actual load data of a certain station, and the effectiveness of the algorithm is verified.
However, these techniques do not take distributed new energy power generation systems into consideration, and are not applicable to power generation systems including distributed new energy power generation systems. The battery energy storage system is an essential part of a distributed new energy power generation system, a great deal of scientific research and practical demonstration has been made on the related technology of the battery energy storage system, the power generation system containing the distributed new energy has greater and greater proportion in the current power system along with the development of the times, however, the prior art has not appeared in the control technology of carrying out peak clipping and valley filling on the power generation system of the distributed new energy in the energy storage battery.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, seeks an optimal method for reducing the peak-valley difference of a power grid by using battery energy storage, and is a control technology for performing peak clipping and valley filling on an energy storage battery in a distributed new energy power generation system. And monitoring and recording data of the possible influence factor layer and the direct influence factor layer to obtain a peak regulation coefficient, introducing a credible factor, and further constructing a target layer of the direct influence factor to obtain the charge and discharge power of the battery.
In order to achieve the purpose, the invention adopts the following technical scheme that firstly, data of possible influence factors and data of direct influence factors are collected and processed to respectively obtain a peak regulation coefficient A and a peak regulation coefficient B; and credibility factors of the two peak regulation coefficients are introduced through fusion with historical data, so that the credibility of the peak regulation coefficients is increased. Finally substituting the current charge and discharge power into a mathematical model of the current battery charge and discharge power to obtain the current battery charge and discharge power P B 。
Modeling relevant factors for reducing peak-valley difference of battery energy storage, wherein the relevant factors are separated in the design and divided into a possible influence factor layer, a direct influence factor constraint layer and a direct influence factor target layer; the possible influencing factor layer mainly comprises the temperature, the air relative humidity, the altitude and the weather state of a power supply area, the direct influencing factor constraint layer is the capacity and the battery charging/discharging speed of the battery, and the direct influencing factor target layer reduces the expected value of the peak-valley difference, and the specific method comprises the following steps:
the method comprises the following steps: the data of the possible influence factor layer is effectively processed to obtain a peak regulation coefficient A and is expressed in a mathematical modeling mode, and the expression formula is as follows:
in the formula: n is the area of the battery responsible for peak regulation is divided into n areas;
c j a temperature value for each divided region;
H j each divided zone air relative humidity value;
h altitude value of the battery energy storage area;
k r 、k c a weather condition related coefficient value;
S j the trusted function is a function of the network,
m number of untrustworthy.
The credible function: when calculating the peak regulation coefficient A, data fusion is carried out on the temperature and the humidity of each area, and the data obtained by fusion is substituted into a test functionIf phi (x) is more than or equal to 0.0148 and less than or equal to 0.1768, marking as a credible interval, otherwise, the credible interval is determined.
The power load curve shows a constantly changing trend along with the time, and the peak regulation coefficient A of the previous two time periods is used in the design i-1 、A i-2 Deriving a confidence factor lambda that may influence the current time period of the factor layer li The expression is as follows:
confidence factor lambda li A value that is close to 1 and less than 1 under normal conditions.
Step two: performing mathematical modeling on the peak regulation coefficient B of the direct influence factor constraint layer, wherein the expression is as follows:
in the formula: t is B The battery energy storage temperature;
η Ii battery charging efficiency;
V BIi a battery charge rate;
η Oi the efficiency of battery discharge;
V BOi the rate of discharge of the battery;
C r a battery capacity;
ε r thermal conductivity of the battery material.
Similarly, a credible factor lambda directly influencing the current time interval of the factor constraint layer is led out 2i The expression is as follows:
step three: establishing a mathematical model of the current battery charge and discharge power according to the expected value of the peak-valley difference required to be reduced and the peak regulation coefficients obtained in the previous two steps, wherein the expression is as follows:
in the formula:
e desired reduction in the percentage of peak-to-valley difference;
P Ii current load usage.
Calculated current battery charging and discharging power P B I.e. energy storage battery with power P B Charging and discharging, if P B &0, discharging the battery; when P is B &And lt, 0, charging the battery.
Compared with the prior art, the invention has the following beneficial effects:
the method can not only meet the control effect of reducing the peak-valley difference by using the battery energy storage in the prior art, but also better inhibit the load fluctuation brought by the peak regulation process by fusing the historical data; by adding analysis and fusion of data of factors such as weather with large influence on distributed new energy power generation, the method is very suitable for a control method for reducing peak-valley difference by battery energy storage of a power system comprising a distributed new energy system. Nowadays, national policies strongly support the development of new energy power generation to replace traditional thermal power generation, the proportion of the new energy power generation is more and more, the new energy power generation is considered to be necessary in a control technology for reducing peak-valley difference through battery energy storage in an analysis power system, and the invention brings huge economic benefits.
Drawings
Fig. 1 is a flowchart of a method for reducing a peak-to-valley difference of a power system based on battery energy storage according to the present invention.
Fig. 2 is a comparison graph of load curves after the battery energy storage provided by the present invention reduces the peak-to-valley difference.
Detailed Description
According to the technical scheme, as shown in figure 1, firstly, data of possible influence factors and data of direct influence factors are collected and processed to respectively obtain a peak regulation coefficient A and a peak regulation coefficient B; and credibility factors of the two peak regulation coefficients are introduced through fusion with historical data, so that the credibility of the peak regulation coefficients is increased. Finally, substituting the current charge-discharge power into a mathematical model of the current battery charge-discharge power to obtain the current battery charge-discharge power P B The specific scheme is as follows:
step one, effectively processing data of a possible influence factor layer to obtain a peak regulation coefficient A and expressing the peak regulation coefficient A in a mathematical modeling mode, wherein an expression formula is as follows:
in the formula: n is the area of the battery responsible for peak regulation is divided into n areas;
c j a temperature value for each divided region;
H j each divided zone air relative humidity value;
h altitude value of the battery energy storage area;
k r 、k c a weather condition related coefficient value;
S j the trusted function is a function of the received data,
m number of untrustworthy.
A trusted function: when calculating the peak regulation coefficient A, each time the peak regulation coefficient A needs to be calculated firstFusing the data of the temperature and the humidity of each area, and substituting the fused data into a test functionIf phi (x) is more than or equal to 0.0148 and less than or equal to 0.1768, marking as a credible interval, otherwise, the credible interval is determined.
The power load curve shows a constantly changing trend along with the time, and the peak regulation coefficient lambda of the previous two time periods is used in the design i-1 、A i-2 Deriving a confidence factor lambda that may influence the current time period of the factor layer li The expression is as follows:
confidence factor lambda li A value that is close to 1 and less than 1 under normal conditions.
Step two, performing mathematical modeling on the peak regulation coefficient B of the direct influence factor constraint layer, wherein the expression is as follows:
in the formula: t is B The battery energy storage temperature;
η Ii battery charging efficiency;
V BIi a battery charge rate;
η Oi the efficiency of battery discharge;
V BOi a rate of battery discharge;
C r a battery capacity;
ε r the thermal conductivity of the battery material.
Similarly, a confidence factor lambda directly influencing the current time interval of the factor constraint layer is led out 2i The expression is as follows:
step three, establishing a mathematical model of the current battery charge and discharge power according to the expected value of the peak-valley difference required to be reduced and the peak regulation coefficients obtained in the previous two steps, wherein the expression is as follows:
in the formula:
e desired reduction in the percentage of peak-to-valley difference;
P Ii current load usage.
Calculated current battery charging and discharging power P B I.e. energy storage battery with power P B Charging and discharging, if P B &0, discharging the battery; when P is present B &And lt, 0, charging the battery.
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
For example, a set of complete battery energy storage peak shaving equipment is established in a certain area containing a distributed new energy power generation system grid connection, the area is divided into 10 areas, and a current temperature value c is obtained through detection j = {27.2, 26.7, 30.1, 28.2, 27.1, 29.7, 28.8, 30.2, 28.3, 29.9}, unit ° celsius; humidity value H of each area j = {33, 56, 45, 87, 65, 32, 78, 55, 57, 61}, unit%; the altitude value h =659 m in the battery energy storage area; the value of the weather condition correlation coefficient is empirically k r ＝1.0147，k c =0.9915; calculating the peak regulation coefficient A at the moment i The value:
and according to the peak regulation coefficients A of the first two times i-1 ＝1.0117、A i-2 =0.9991 calculation confidence factor λ Ii ：
The material thermal conductivity coefficient epsilon of the energy storage battery is also known r =4.172W; battery energy storage temperature T B =27 ℃; capacity C of battery r =10MW; battery charging efficiency eta Ii =97.77%; battery discharge efficiency η Oi =98.79%; battery charging rate V BIi =2.3C/h; rate of battery charging V BOi =2.1C/h, the value of the peak shaver coefficient B at that moment was calculated i ：
And according to the first two peak regulation coefficients B i-1 ＝0.1997、B i-2 =0.2015 calculation confidence factor λ 2i ：
If the desired percentage reduction in peak-to-valley difference is 15%, the current load usage P Ii And =120MW, the charge-discharge power of the battery at this moment is:
the above is an introduction to the use of the example designed by the present invention, and we can compare the results of the monitoring experiment of one day: FIG. 2 shows, in the upper diagram, a dotted line portion is an original loader curve, which is implemented as a load curve after peak clipping and valley filling; the lower graph shows the real-time charging efficiency of the energy storage battery, the charging power is greater than 0 to represent that the battery is charged, and when the charging power is less than 0 to represent that the battery is discharged; comparing the two load curves, the control method for reducing the peak-valley difference by using the battery energy storage can well play a role in peak clipping and valley filling, well inhibit the problem of load fluctuation in the peak clipping and valley filling process, and lead the load curve after peak clipping and valley filling to be stable, thereby providing great help for the economic operation of a power system and the consumption of a new energy power generation system.
Table 1 below shows the typical time node raw load during a day compared to the load after the peak-to-valley difference is reduced by using the battery energy storage of the present invention, and the real-time charging power of the battery.
TABLE 1 load curves and Battery charging Power for typical times of day
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (2)
1. A method for reducing load peak-valley difference of a power grid based on battery energy storage is characterized in that data of possible influence factors and data of direct influence factors are collected and processed to respectively obtain a peak regulation coefficient A and a peak regulation coefficient B; credibility factors of the two peak regulation coefficients are introduced through fusion with historical data, and the credibility of the peak regulation coefficients is increased; finally substituting the current charge and discharge power into a mathematical model of the current battery charge and discharge power to obtain the current battery charge and discharge power P B 。
2. The method for reducing the peak-to-valley difference of the load of the power grid based on the stored energy of the battery as claimed in claim 1, characterized in that the method comprises the following steps:
step one, effectively processing data of a possible influence factor layer to obtain a peak regulation coefficient A and expressing the peak regulation coefficient A in a mathematical modeling mode, wherein an expression formula is as follows:
in the formula:
n is the area of the battery responsible for peak regulation is divided into n areas;
c j a temperature value for each divided region;
H j each divided zone air relative humidity value;
h altitude value of the battery energy storage area;
k r 、k c a weather condition related coefficient value;
S j the trusted function is a function of the received data,
m is the number of untrustworthy;
a trusted function: when calculating the peak regulation coefficient A, data fusion is carried out on the temperature and the humidity of each area, and the data obtained by fusion is substituted into a test functionIf phi (x) is more than or equal to 0.0148 and less than or equal to 0.1768, recording as a credible interval, otherwise, determining as an incredible interval;
the power load curve shows a constantly changing trend along with the time, and the peak regulation coefficient A of the previous two time periods is used in the design i-1 、A i-2 Deriving a confidence factor lambda that may influence the current time period of the factor layer 1i The expression is as follows:
confidence factor lambda 1i A value that is close to 1 and less than 1 under normal conditions;
step two, performing mathematical modeling on the peak regulation coefficient B of the direct influence factor constraint layer, wherein the expression is as follows:
in the formula:
T B the battery energy storage temperature;
η Ii battery charging efficiency;
V BIi a battery charge rate;
η Oi the efficiency of battery discharge;
V BOi a rate of battery discharge;
C r a battery capacity;
ε r the thermal conductivity of the battery material;
similarly, a credible factor lambda directly influencing the current time interval of the factor constraint layer is led out 2i The expression is as follows:
step three, establishing a mathematical model of the current battery charge and discharge power according to the expected value of the peak-valley difference required to be reduced and the peak regulation coefficients obtained in the previous two steps, wherein the expression is as follows:
in the formula:
e desired reduction in the percentage of peak-to-valley difference;
P Li current load usage;
calculated current battery charging and discharging power P B I.e. energy storage battery with power P B Charging and discharging, if P B &0, discharging the battery; when P is present B &And lt, 0, charging the battery.
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| CN111106615A (en) * | 2020-01-03 | 2020-05-05 | 国网内蒙古东部电力有限公司 | Method for reducing peak-valley difference of power grid based on battery energy storage device and electric heat storage device |
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| CN111106615B (en) * | 2020-01-03 | 2023-03-31 | 国网内蒙古东部电力有限公司 | Method for reducing peak-valley difference of power grid based on battery energy storage device and electric heat storage device |
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