CN116865327A - Method and system for determining electric balance proportion of new energy incorporation - Google Patents
Method and system for determining electric balance proportion of new energy incorporation Download PDFInfo
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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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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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
- H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
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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
- H02J3/38—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
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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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- 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
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
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Abstract
The invention relates to the technical field of electric power and electric quantity balance, and provides a method and a system for determining the electric power balance proportion of new energy, wherein the method comprises the following steps: in each time interval, calculating the maximum value of the new energy prediction positive deviation and the average value of the new energy prediction positive deviation according to the new energy prediction positive deviation of all sampling points, and combining different coefficients to calculate to obtain an equivalent prediction positive error; or, calculating the maximum value of the new energy prediction positive deviation, the average value of the new energy prediction positive deviation and the positive deviation of different confidence coefficients according to the new energy prediction positive deviation of all sampling points in each new energy prediction output interval, and calculating to obtain an equivalent prediction positive error by combining different coefficients; calculating to obtain a balance margin based on the difference value of the equivalent prediction positive errors; and selecting the proportion of new energy to be brought into balance based on different coefficients and balance margin. The power supply reliability of the power system is improved, and new energy consumption is promoted.
Description
Technical Field
The invention belongs to the technical field of electric power and electric quantity balance, and particularly relates to a method and a system for determining a new energy intake electric power balance proportion.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The new energy power generation has obvious volatility and randomness, and brings great challenges to the power and electricity balance capability of the power system along with the continuous improvement of the installed duty ratio.
Currently, there are two problems with new energy balance considerations: firstly, the proportion of the load is not included in the balance according to the detail area of the quarter and the load peak; and secondly, the influence of the new energy power prediction deviation is not considered, so that the supporting capability of the new energy to balance is not easy to grasp, and the power system conservation capability and the new energy consumption level are influenced.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention provides a method and a system for determining the proportion of new energy to electric power balance, which reasonably evaluates the supporting capability of the new energy to electric power and electric quantity balance of a power grid, improves the power supply reliability of an electric power system and promotes the consumption of the new energy.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the first aspect of the present invention provides a method for determining a new energy incorporation power balance ratio, comprising:
acquiring operation data and prediction data of each sampling point in a plurality of continuous years;
calculating average daily load curve maximum values of new energy average synchronous rate, maximum net load and equivalent load based on the acquired operation data and prediction data in each time interval;
in each time interval, calculating the maximum value of the new energy prediction positive deviation and the average value of the new energy prediction positive deviation according to the new energy prediction positive deviation of all sampling points, and combining different coefficients to calculate to obtain an equivalent prediction positive error; or in each time interval, calculating the maximum value of the new energy prediction positive deviation, the average value of the new energy prediction positive deviation and the positive deviation of different confidence coefficients according to the new energy prediction positive deviation of all sampling points in each new energy prediction output interval, and calculating to obtain an equivalent prediction positive error by combining different coefficients;
in each time interval, modifying the proportion of new energy in the power output plan to be brought into balance into a difference value between the average synchronous rate of the new energy and the equivalent prediction positive error, and calculating to obtain a balance margin by combining the average synchronous rate of the new energy, the maximum net load and the average daily load curve maximum value of the equivalent load;
and selecting the proportion of the new energy source to be brought into balance based on different coefficients and balance margin in each time interval.
Further, according to the four seasons of spring, summer, autumn and winter, the early peak, the noon peak, the late peak and other time intervals are divided, 16 time intervals are obtained.
Further, the new energy prediction positive deviation of a certain sampling point is the maximum value of 0 and the prediction deviation of the sampling point.
Further, the calculation method of the prediction deviation of a certain sampling point comprises the following steps: (new energy predicted power of the sampling point-new energy actual power of the sampling point)/new energy installed capacity of the sampling point corresponding to month.
Further, the synchronous rate of the new energy at a certain sampling point is the ratio of the actual power generated by the new energy at the sampling point to the installed capacity of the new energy at the month corresponding to the sampling point.
Further, the balance margin is the sum of the power output planning values of various types of power supplies minus the maximum net load, the maximum tie-line output power and the average daily load curve maximum value of the equivalent load.
Further, the equivalent prediction positive error is the product of the maximum value of the new energy prediction positive error and the coefficient, and the average value of the new energy prediction positive error is added;
or alternatively, the process may be performed,
the equivalent prediction positive error is the product of the maximum value of the new energy prediction positive error and the coefficient, the average value of the new energy prediction positive error, and the weighted sum of the positive errors with different confidence coefficients.
A second aspect of the present invention provides a system for determining a new energy incorporation power balance ratio, comprising:
a data acquisition module configured to: acquiring operation data and prediction data of each sampling point in a plurality of continuous years;
a first computing module configured to: calculating average daily load curve maximum values of new energy average synchronous rate, maximum net load and equivalent load based on the acquired operation data and prediction data in each time interval;
a second computing module configured to: in each time interval, calculating the maximum value of the new energy prediction positive deviation and the average value of the new energy prediction positive deviation according to the new energy prediction positive deviation of all sampling points, and combining different coefficients to calculate to obtain an equivalent prediction positive error; or in each time interval, calculating the maximum value of the new energy prediction positive deviation, the average value of the new energy prediction positive deviation and the positive deviation of different confidence coefficients according to the new energy prediction positive deviation of all sampling points in each new energy prediction output interval, and calculating to obtain an equivalent prediction positive error by combining different coefficients;
a third computing module configured to: in each time interval, modifying the proportion of new energy in the power output plan to be brought into balance into a difference value between the average synchronous rate of the new energy and the equivalent prediction positive error, and calculating to obtain a balance margin by combining the average synchronous rate of the new energy, the maximum net load and the average daily load curve maximum value of the equivalent load;
a selection module configured to: and selecting the proportion of the new energy source to be brought into balance based on different coefficients and balance margin in each time interval.
A third aspect of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of a new energy source incorporation into a method of determining a power balance ratio as described above.
A fourth aspect of the invention provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps in a method of determining the proportion of new energy into the power balance as described above when the program is executed.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a method for determining the proportion of new energy to the power balance, which provides analysis methods such as new energy output distribution characteristics, new energy influence on load peaks, new energy prediction deviation analysis in load peaks and the like, and designs an analysis method for the proportion of new energy to the power balance of a power grid based on analysis results, wherein the method is used for reasonably evaluating the supporting capacity of the new energy to the power balance of the power grid so as to improve the power supply reliability of the system and promote the new energy consumption.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
FIG. 1 is a schematic diagram of a probability statistics and calculation method for probability values, confidence levels and quantiles according to a first embodiment of the present invention;
FIG. 2 is a probability distribution diagram of each time interval of new energy in the last three years of spring according to the first embodiment of the invention;
FIG. 3 is a probability distribution diagram of each time interval of new energy in the last three years of summer according to the first embodiment of the invention;
FIG. 4 is a probability distribution diagram of each time interval of new energy in autumn of the first embodiment of the invention;
fig. 5 is a probability distribution diagram of each time interval of new energy in winter of the first embodiment of the present invention.
Detailed Description
The invention will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
Example 1
The embodiment provides a method for determining the power balance proportion of new energy incorporation.
The method for determining the power balance ratio of new energy inclusion provided by the embodiment comprises the following steps:
and step 1, data acquisition. Operational data and predictive data are obtained for consecutive years.
Wherein, the operation data and the prediction data comprise:
(1) Wind power actual generation power and predicted power;
(2) Centralized photovoltaic actual power generation and predicted power;
(3) The actual power generation and the predicted power of the distributed photovoltaic;
(4) Actual load power, predicted load power;
(5) Transmitting power by the connecting wire;
(6) Wind power and centralized photovoltaic month-by-month installed capacity.
For items (1) to (5), the data is required to be one acquisition point (sampling point) every 15 minutes.
As one embodiment, near three years of operating data and forecast data are obtained.
And 2, data processing. And performing preliminary processing on the acquired operation data and the prediction data.
Wherein, preliminary treatment includes:
step 201, defining load early peak, noon peak, late peak and other time periods according to actual load power for a plurality of continuous years; the peak load time is shown in table 1 according to the actual load data of the last three years;
TABLE 1 load peak time
| Early peak | 06:00-08:00 |
| Peak noon | 11:00-13:00 |
| Late peak | 17:00-20:00 |
| Other time periods | 00:00-05:00，09:00-10:00，14:00-16:00，21:00-23:00 |
Step 202, dividing the operation data and the prediction data into 16 intervals according to spring, summer, autumn and winter seasons, early peak, noon peak, late peak and other time periods;
step 203, summing the actual power generation power and the predicted power of the wind power and the centralized photovoltaic in each interval to obtain the actual power generation power and the predicted power of the new energy source of each acquisition point;
step 204, subtracting the actual power generation power and the predicted power of the distributed photovoltaic from the actual load power and the predicted load power in each interval to obtain the actual net load power and the predicted net load power of each acquisition point;
step 205, in each interval, calculating the synchronous rate of wind power, centralized photovoltaic and new energy of each collection point, wherein the calculation method comprises the following steps: actual generated power/corresponding month installed capacity.
Wherein, the synchronous rate of wind power at a certain collection point=the actual power generation of wind power at the collection point/the installed capacity of wind power in corresponding months;
the synchronous rate of the centralized photovoltaic at a certain collection point=the actual power generation of the centralized photovoltaic at the collection point/the centralized photovoltaic installed capacity of the corresponding month;
the new energy synchronous rate of a certain collection point=the new energy actual power generation power of the collection point/the new energy installed capacity of the corresponding month; the new energy installed capacity is the sum of the installed capacities of wind power and centralized photovoltaic.
And step 3, counting the output distribution characteristics of the new energy.
(1) According to the new energy output data of the last three years, the distribution conditions of the new energy synchronous rate in early peak, noon peak, late peak and other time periods, the maximum synchronous rate and the average synchronous rate in each section are counted, and the synchronous rate section statistical analysis is carried out according to month from four seasons of spring, summer, autumn and winter, and the statistical results are shown in table 2, fig. 3, fig. 4 and fig. 5.
Table 2, new energy synchronization Rate statistics index in recent three years (%)
(2) And (3) counting the new energy source guarantee synchronous rate according to the data of the last three years, analyzing the supporting effect of the new energy source in the early peak, the noon peak, the late peak and other time periods, counting the guarantee synchronous rate under different confidence levels, and carrying out new energy source supporting effect analysis from four seasons of spring, summer, autumn and winter for three years, wherein the counting results are shown in tables 3, 4, 5 and 6. Taking 95% as an example, the guaranteed synchronization rate is defined as that the new energy synchronization rate is not lower than the new energy synchronization rate within a 95% statistical period.
Table 3, new energy guarantee timing rate in recent three years-spring (%)
Table 4, new energy guarantee timing rate in recent three years-summer (%)
Table 5, new energy guarantee timing rate in recent three years-autumn (%)
Table 6, new energy guarantee timing rate in recent three years-winter (%)
And 4, analyzing the influence of the new energy on the load peak.
According to the new energy and load data of the last three years, calculating an average daily load curve of each season, and counting the influence of the new energy output on the maximum load peak value and the occurrence period. Firstly, calculating an equivalent load (actual net load power-new energy actual power), wherein the new energy actual power is the sum of wind power actual power and centralized photovoltaic power, and analyzing the change relation between the average daily load curve maximum value of the equivalent load and the average daily load curve maximum value of the original net load and the change relation between the occurrence time of the maximum value of the equivalent load and the occurrence time of the maximum value of the original net load, as shown in table 7. Description of average daily load curve: for example, the data are all 15 minutes and one point, 96 points are provided for each day, the load at the time of 00:00:00 of each day of the corresponding season of the last three years is averaged, the average values of 00:15:00, 00:30:00 are also averaged, and the like, so that the load data of the final 96 points form an average daily load curve.
Table 7 New energy impact on load maximum (%), thousands of watts
And 5, analyzing the new energy prediction positive deviation in the peak load time.
And according to the actual data of the new energy output in the last three years and the short-term prediction result of the new energy before the day, counting the distribution condition of the per unit value of the new energy prediction positive deviation in the early peak, the noon peak, the late peak and other time periods. The statistical indexes comprise the maximum value and the average value of the predicted positive deviation, the positive deviation under different confidence levels and the like.
Wherein, the predicted positive deviation, i.e. the deviation is zero and the positive value is included in the statistics, the negative deviation is not included in the statistics, the calculating method is MAX (0, predicted deviation), the predicted deviation is per unit value, and the calculating method is: (predicted power-actual power)/corresponding month installed capacity.
(1) And the new energy prediction deviation in different seasons is distributed.
The statistical results are shown in tables 8 and 9, 10, 11 and 12.
Table 8, new energy forecast positive deviation statistical index (percent) for recent three years
Table 9, new energy forecast bias distribution of recent three years-spring (%)
Table 10, new energy prediction bias distribution in recent three years-summer (%)
Table 11, new energy forecast bias distribution of recent three years-autumn (%)
Table 12, new energy forecast bias distribution of recent three years-winter (%)
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(2) Deviations of different power prediction intervals are distributed.
Firstly, dividing a new energy prediction synchronous rate interval, for example [80, 90% ] new energy prediction synchronous rate interval, wherein the predicted force per unit value (new energy prediction output/corresponding month installation capacity) is in the range of 80% -90%, the predicted value in each interval has a corresponding positive deviation value, and the positive deviation of each interval is counted respectively, as shown in fig. 1, and the method comprises the following steps:
(1) sequencing the predicted force per unit values (output/loading) from small arrival, and dividing the predicted force per unit values into a plurality of predicted output intervals;
(2) each predicted output level has a corresponding positive error, and statistics is carried out on all positive errors in each predicted output interval respectively;
(3) and obtaining statistical indexes such as positive errors under 95% confidence level.
The new energy prediction power is new energy prediction power, namely the sum of wind power prediction power and centralized photovoltaic prediction power.
Wherein, the deviation value corresponding to the 95% confidence coefficient is defined as that the new energy prediction positive deviation is smaller than the deviation value within the 95% statistical period. The statistical results are shown in tables 13, 14 and 15.
TABLE 13 predicted Positive deviation distribution for New energy different predicted output intervals (%)
TABLE 14 predicted Positive deviation distribution for different wind Power predicted output intervals (%)
TABLE 15 predicted positive deviation distribution for different photovoltaic output intervals (%)
And step 6, calculating the new energy intake balance proportion.
The power balance margin of the power system is the sum of the maximum load, the maximum tie-line outgoing power and the conventional power supply standby requirement subtracted from the sum of the power output planning values of various power supplies in a statistical period (in a certain interval), namely:
P＝P G -P L -P C -P R (1)
calculating the new energy intake balance proportion according to the following steps:
(1) According to the data preliminary processing result, maximum load P L Modifying to an actual payload power maximum;
(2) According to the results of Table 7, the conventional Power supply reserve Capacity P R Modifying the average daily load curve maximum value of the equivalent load; it should be noted that, considering the situation of the residence to be covered by the power balance margin of the power system, the equivalent load maximum value of the corresponding season in table 7 is used for the normal power supply reserve capacity PR in a certain season, and the details are not refined according to the peak period, and the same steps are carried out in step (1);
(3) According to the results of Table 2, the average synchronous rate of new energy corresponding to a certain peak period in a certain season is recorded as S a The maximum timing rate is recorded as S m ；
(4) If the season and time interval distribution of the prediction positive error is considered, the equivalent prediction positive error of the corresponding time interval in the step (3) is E equal1 Can be calculated by the following formula:
E equal1 ＝E a1 +K 1 ×E m1 ，K 1 ∈(0,1) (2)
wherein E is a1 For the average positive prediction error (average of the new energy source prediction positive deviation) in Table 8, E m1 The maximum predicted positive error (maximum value of the positive deviation predicted by the new energy source) is shown in table 8.
If the interval distribution of the synchronous rate of the prediction positive errors is considered, the equivalent prediction positive error of the corresponding time period in the step (3) is E equal2 Can be calculated by the following formula:
E equal2 ＝E a2 +K 2 ×E m2 +0.05E 95％ +0.1E 90％ ，K 2 ∈(0,1) (3)
wherein E is a2 For S in tables 13, 14 and 15 and in step (3) m Average predictive positive error, E, of the time interval in which m2 For S in tables 13, 14 and 15 and in step (3) m Maximum predictive positive error, E, of the time interval in which 95％ For S in tables 13, 14 and 15 and in step (3) m A 95% confidence prediction positive error, E, of the time interval in which 90％ For S in tables 13, 14 and 15 and in step (3) m The 90% confidence in the time interval where it is located predicts the positive error.
(5) Planning power output P G The proportion of new energy intake balance is modified to S a -E equal1 Or S a -E equal2 ；
(6) Calculating balance margin P, and solving for satisfying P>Coefficient K of 0 1 Or K 2 A minimum value;
(7) Will satisfy P>K of 0 1 Or K 2 Comparing the new energy intake balance ratio calculated by the minimum value with the data in the tables 3, 4, 5 and 6, and positioning the guaranteed synchronous rate with the minimum absolute value difference, namely the new energy intake balance ratio in the period (the interval); for example, the wind power intake balance proportion of early spring peak is calculated to be 11%, the wind power intake balance proportion is closest to the wind power early peak synchronous rate of 2021 in table 3 of 10.54%, the corresponding guaranteed synchronous rate is 80%, and the new energy intake balance proportion in the period corresponds to the guaranteed synchronous rate of 80%;
(8) Checking the balance margin P, if P>0, stop calculation, if P<0, explaining that the calculation is wrong, and recalculating K 1 Or K 2 Is checked again until P is satisfied>0。
By using the method, the guarantee synchronous rate of the new energy intake balance proportion of each period of each season of the power grid is calculated as shown in table 16.
TABLE 16 guaranteed timing rate for New energy intake balance ratio
According to the method, based on historical actual operation data and prediction data of different load peak periods in each quarter of the last three years, analysis methods such as new energy output distribution characteristics, new energy influence on load peaks, new energy prediction deviation analysis in the load peak periods and the like are provided, and an intake balance proportion analysis method considering new energy power distribution and prediction confidence coefficient is designed based on analysis results and used for reasonably evaluating the supporting capacity of new energy on electric power and electric quantity balance of a power grid so as to improve the power supply reliability of a system and promote new energy consumption.
Compared with the traditional method, the method of the embodiment is characterized in that the balance proportion is included according to the quarterly and load peak period refinement and division, and the influence of new energy power distribution and prediction deviation is considered.
Example two
The embodiment provides a system for determining a new energy intake power balance ratio, which specifically comprises:
a data acquisition module configured to: acquiring operation data and prediction data of each sampling point in a plurality of continuous years;
a first computing module configured to: calculating average daily load curve maximum values of new energy average synchronous rate, maximum net load and equivalent load based on the acquired operation data and prediction data in each time interval;
a second computing module configured to: in each time interval, calculating the maximum value of the new energy prediction positive deviation and the average value of the new energy prediction positive deviation according to the new energy prediction positive deviation of all sampling points, and combining different coefficients to calculate to obtain an equivalent prediction positive error; or in each time interval, calculating the maximum value of the new energy prediction positive deviation, the average value of the new energy prediction positive deviation and the positive deviation of different confidence coefficients according to the new energy prediction positive deviation of all sampling points in each new energy prediction output interval, and calculating to obtain an equivalent prediction positive error by combining different coefficients;
a third computing module configured to: in each time interval, modifying the proportion of new energy in the power output plan to be brought into balance into a difference value between the average synchronous rate of the new energy and the equivalent prediction positive error, and calculating to obtain a balance margin by combining the average synchronous rate of the new energy, the maximum net load and the average daily load curve maximum value of the equivalent load;
a selection module configured to: and selecting the proportion of the new energy source to be brought into balance based on different coefficients and balance margin in each time interval.
It should be noted that, each module in the embodiment corresponds to each step in the first embodiment one to one, and the implementation process is the same, which is not described here.
Example III
The present embodiment provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of a new energy source incorporation into a method of determining a power balance ratio as described in the above embodiment.
Example IV
The present embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor executes the program to implement the steps in the method for determining a proportion of new energy to be included in electric power balance according to the above embodiment.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random access Memory (Random AccessMemory, RAM), or the like.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The method for determining the proportion of new energy into electric power balance is characterized by comprising the following steps:
acquiring operation data and prediction data of each sampling point in a plurality of continuous years;
calculating average daily load curve maximum values of new energy average synchronous rate, maximum net load and equivalent load based on the acquired operation data and prediction data in each time interval;
in each time interval, calculating the maximum value of the new energy prediction positive deviation and the average value of the new energy prediction positive deviation according to the new energy prediction positive deviation of all sampling points, and combining different coefficients to calculate to obtain an equivalent prediction positive error; or in each time interval, calculating the maximum value of the new energy prediction positive deviation, the average value of the new energy prediction positive deviation and the positive deviation of different confidence coefficients according to the new energy prediction positive deviation of all sampling points in each new energy prediction output interval, and calculating to obtain an equivalent prediction positive error by combining different coefficients;
in each time interval, modifying the proportion of new energy in the power output plan to be brought into balance into a difference value between the average synchronous rate of the new energy and the equivalent prediction positive error, and calculating to obtain a balance margin by combining the average synchronous rate of the new energy, the maximum net load and the average daily load curve maximum value of the equivalent load;
and selecting the proportion of the new energy source to be brought into balance based on different coefficients and balance margin in each time interval.
2. The method for determining the power balance ratio of new energy according to claim 1, wherein 16 time intervals are obtained according to the four seasons of spring, summer, autumn and winter and the early peak, the noon peak, the late peak and other time intervals.
3. The method of claim 1, wherein the positive deviation of the new energy prediction at a sampling point is 0 and the predicted deviation at the sampling point is the maximum value.
4. The method for determining a new energy intake power balance ratio according to claim 3, wherein the calculating method of the prediction deviation of a certain sampling point is as follows: (new energy predicted power of the sampling point-new energy actual power of the sampling point)/new energy installed capacity of the sampling point corresponding to month.
5. The method for determining a new energy intake power balance ratio according to claim 1, wherein the new energy synchronous rate at a sampling point is a ratio of the actual power generated by the new energy at the sampling point to the installed new energy capacity at the month corresponding to the sampling point.
6. The method of claim 1, wherein the balance margin is a sum of power output planning values of each type of power source minus a maximum net load, a maximum link output power and an average daily load curve maximum value of an equivalent load.
7. The method for determining a new energy intake power balance ratio according to claim 1, wherein the equivalent predictive positive error is a product of a maximum value of the new energy predictive positive deviation and a coefficient, and an average value of the new energy predictive positive deviation is added;
or alternatively, the process may be performed,
the equivalent prediction positive error is the product of the maximum value of the new energy prediction positive error and the coefficient, the average value of the new energy prediction positive error, and the weighted sum of the positive errors with different confidence coefficients.
8. A system for determining a proportion of new energy to be taken into electric power balance, comprising:
a data acquisition module configured to: acquiring operation data and prediction data of each sampling point in a plurality of continuous years;
a first computing module configured to: calculating average daily load curve maximum values of new energy average synchronous rate, maximum net load and equivalent load based on the acquired operation data and prediction data in each time interval;
a second computing module configured to: in each time interval, calculating the maximum value of the new energy prediction positive deviation and the average value of the new energy prediction positive deviation according to the new energy prediction positive deviation of all sampling points, and combining different coefficients to calculate to obtain an equivalent prediction positive error; or in each time interval, calculating the maximum value of the new energy prediction positive deviation, the average value of the new energy prediction positive deviation and the positive deviation of different confidence coefficients according to the new energy prediction positive deviation of all sampling points in each new energy prediction output interval, and calculating to obtain an equivalent prediction positive error by combining different coefficients;
a third computing module configured to: in each time interval, modifying the proportion of new energy in the power output plan to be brought into balance into a difference value between the average synchronous rate of the new energy and the equivalent prediction positive error, and calculating to obtain a balance margin by combining the average synchronous rate of the new energy, the maximum net load and the average daily load curve maximum value of the equivalent load;
a selection module configured to: and selecting the proportion of the new energy source to be brought into balance based on different coefficients and balance margin in each time interval.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, realizes the steps of a new energy source inclusion power balance ratio determination method according to any one of claims 1-7.
10. A 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 implements the steps of a method for determining the proportion of new energy into the electric power balance according to any of claims 1-7 when the program is executed by the processor.
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