CN116454924A - Flexible load power regulation and control method based on correlation coefficient - Google Patents
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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
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
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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
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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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- 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
- H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
- H02J2310/10—The network having a local or delimited stationary reach
- H02J2310/12—The local stationary network supplying a household or a building
- H02J2310/14—The load or loads being home appliances
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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
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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Abstract
The invention discloses a flexible load power regulation and control method based on a correlation coefficient, and relates to the technical field of power load regulation and control. The flexible load power regulation and control method comprises the steps of firstly determining the load ratio of flexible expected power of load equipment, calculating the size of the flexible expected power, then calculating the probability of whether the flexible expected power is consistent with the instantaneous output power of the photovoltaic power generation system according to a given correlation coefficient, and finally calculating the flexible expected power of each load equipment, so as to guide the power regulation and control of the load equipment. The invention has important significance for guiding residents to orderly use electricity, avoiding the influence of excessive output power or excessive load power of the photovoltaic power generation system on the stability of the power system and reasonably absorbing the photovoltaic output power.
Description
Technical Field
The invention relates to the field of power load regulation and control, in particular to a flexible load power regulation and control method based on a correlation coefficient.
Background
The flexible load power is flexible and variable within a certain time, and the flexible load equipment participates in power grid interaction by combining the characteristics of output power data of the photovoltaic power generation system, so that the solar energy can be effectively utilized, the stability of the power system can be maintained, and the running stability of the power grid is ensured. How the flexible load power should respond to fluctuation of output power data of the photovoltaic power generation system is a key of participation regulation and control of the flexible load power. The existing method mainly comprises the steps of scheduling and managing power through an intelligent control algorithm according to electricity price change, so that the power can be adjusted according to fluctuation of output power data of a photovoltaic power generation system, or the power is combined with an energy storage system, so that fluctuation of the output power data of the photovoltaic power generation system is balanced. In the prior art, flexible load power is regulated and controlled through an intelligent control algorithm model or intelligent equipment, and the problems that an algorithm is difficult to adjust and decide according to new data in a short time, a user cannot respond to electricity price change in time, and energy storage scale and cost are limited exist.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a flexible load power regulation and control method based on a correlation coefficient, wherein a load power curve of each device is obtained through the correlation coefficient, and the power of the load device is regulated according to the load power curve so as to solve the problems in the background technology.
The technical problems solved by the invention are realized by adopting the following technical scheme:
a flexible load power regulation and control method based on a correlation coefficient comprises the following steps:
step 1: selecting a photovoltaic power generation system, connecting the photovoltaic power generation system with at least two load devices, collecting instantaneous output power of the photovoltaic power generation system at n sampling moments, and calculating average output power；
Step 2: determining the duty ratio of each load device, and calculating the average expected power of the load devices;
step 3: setting a correlation coefficient tau of flexible expected power of each load device and instantaneous output power of the photovoltaic power generation system;
step 4: calculating the consistent probability alpha and the inconsistent probability beta of the flexible expected power along with the change of the instantaneous output power according to the correlation coefficient tau;
step 5: calculating fluctuation amplitude of the instantaneous output power at adjacent sampling moments, calculating ideal fluctuation amplitude of flexible expected power according to the fluctuation amplitude of the instantaneous output power, calculating actual fluctuation amplitude of the flexible expected power according to the consistent probability alpha and the inconsistent probability beta, and calculating flexible expected power of load equipment;
step 6: and drawing a load power curve of the load equipment according to the flexible expected power at n sampling moments, and regulating and controlling the flexible load power of the load equipment according to the load power curve.
In the invention, in step 1, the instantaneous output power of the photovoltaic power generation system at n sampling moments is x respectively 1 ，x 2 ，…，x n Average output power。
In the present invention, in step 2, the average desired power of the load deviceK is the duty cycle of the load device.
In the present invention, in step 4, the coincidence probability α and the non-coincidence probability β satisfy the condition: α+β=1 and α - β=τ.
In the invention, in step 5, according to the coincidence probability alpha and the non-coincidence probability beta, the number i of sampling points with consistent power variation and the number j of sampling points with inconsistent power variation are determined, and simultaneously, the i, j satisfy the conditions: i+j=n-1, i/j=α/β, and the fluctuation direction of i sampling points is adjusted to be the same direction, and the fluctuation direction of j sampling points is adjusted to be opposite direction.
In the present invention, in step 5, the flexibility of n sampling instants is calculated from the actual fluctuation amplitudes of adjacent sampling instantsDesired power y 1 ，y 2 ，…，y n 。
The flexible load power regulation and control method based on the correlation coefficient has the following beneficial effects: the invention takes the instantaneous output power of the photovoltaic power generation system as the basis, regulates and controls the flexible load power to change along with the change of the instantaneous output power, thereby weakening/counteracting the influence of the fluctuation of the instantaneous output power on a power grid, and has important significance for guiding residents to orderly use electricity and improving the photovoltaic absorption. The correlation coefficient in the invention can be set according to the needs, and the closeness degree of the flexible load power and the instantaneous output power is set according to the electricity utilization wish of residents, so as to scientifically guide the residential electricity. The invention has the advantages of less data needed, simple realization, and capability of obtaining a relatively clear flexible load power curve, thereby providing a feasible method for the management of the power consumer on the demand side.
Drawings
FIG. 1 is a flow chart of a flexible load power regulation method based on correlation coefficients of the present invention;
FIG. 2 is a schematic graph of the instantaneous output power of the photovoltaic power generation system of the present invention;
FIG. 3 is a schematic view showing a load power curve of a washing machine in accordance with a preferred embodiment of the present invention;
FIG. 4 is a schematic diagram showing a load power curve of an air conditioner according to a preferred embodiment of the present invention;
fig. 5 is a schematic diagram of a load power curve of an electric vehicle according to a preferred embodiment of the invention.
Detailed Description
In order that the manner in which the invention is practiced, features of the invention, and objects and features thereof are readily apparent, a more particular description of the invention will be rendered by reference to specific embodiments thereof.
Example 1
According to the flexible load power regulation and control method based on the correlation coefficient, the real-time data of the instantaneous output power in a time period is detected, the load ratio of each load device to the instantaneous output power is estimated, and then the correlation coefficient of each flexible expected power and the instantaneous output power is given, so that the specific value of the flexible expected power can be generated. According to the flexible expected power, a load power curve is generated, and the power user dissipates the photovoltaic power generation system according to the load power curve, so that the stability of the power system is effectively improved, and a guiding effect is provided for orderly power utilization of residents. Referring to fig. 1, the flexible load power regulation method based on the correlation coefficient comprises the following steps.
Step 11: selecting a photovoltaic power generation system, connecting the photovoltaic power generation system with at least two load devices, collecting instantaneous output power of the photovoltaic power generation system at n sampling moments, and calculating average output power. The instantaneous output power of the photovoltaic power generation system is x respectively 1 ，x 2 ，…，x n Average output power +.>。
Step 12: the load duty ratio of the load devices is determined, and the average expected power of each load device is calculated. Average desired power of load deviceK is the duty cycle of the load device.
Step 13: a correlation coefficient tau of the flexible expected power of each load device and the instantaneous output power of the photovoltaic power generation system is set. The correlation coefficient τ is a kendel (Kendall) correlation coefficient, and represents the strength of the power correlation between the load device and the photovoltaic power generation system. τ takes a positive number less than 1.
Step 14: and calculating the consistent probability alpha and the inconsistent probability beta of the flexible expected power along with the change of the instantaneous output power according to the correlation coefficient tau. The expected power of the flexibility varies with the output power data of the photovoltaic power generation system, either uniformly or non-uniformly, expressed with probability as α+β=1. From the definition of the kendel rank correlation coefficient, with α - β=τ, knowing τ, the simultaneous equations can calculate the coincidence probability α and the non-coincidence probability β.
Step 15: calculating fluctuation amplitude of the instantaneous output power at adjacent sampling moments, calculating ideal fluctuation amplitude of the flexible expected power according to the fluctuation amplitude of the instantaneous output power, calculating actual fluctuation amplitude of the flexible expected power according to the consistent probability alpha and the inconsistent probability beta, and calculating flexible expected power of the load equipment. The ideal fluctuation range refers to the fluctuation range in which the fluctuation direction of the flexible expected power is identical. Due to the different actual working conditions, the fluctuation direction of the actual fluctuation amplitude of the load equipment is not completely the same as that of the photovoltaic power generation equipment, namely, the consistency probability alpha and the inconsistency probability beta of the flexible expected power along with the change of the instantaneous output power exist.
And determining the number i of sampling points with consistent power change and the number j of sampling points with inconsistent power change according to the consistent probability alpha and the inconsistent probability beta, wherein i/j=alpha/beta. For n samples, the power change relative to the previous sample is calculated from the second sample, so i+j=n-1. And adjusting the fluctuation directions of the i sampling points to be in the same direction, and adjusting the fluctuation directions of the j sampling points to be in opposite directions, so as to obtain the actual fluctuation amplitude. Calculating the flexible expected power y of n sampling moments according to the actual fluctuation amplitude of the adjacent sampling moments 1 ，y 2 ，…，y n 。
Step 16: and drawing a load power curve of the load equipment according to the flexible expected power at n sampling moments, and regulating and controlling the flexible load power of the load equipment according to the load power curve.
Example two
In this embodiment, a load power curve is generated for a period of time by using a washing machine, an air conditioner, and an electric vehicle as load devices, and detailed steps are described below.
Step 21: the interval of the preset sampling time is 5s, 11 data obtained by 55s are taken as a group, namely n=11, and the instantaneous output power is x respectively 1 ，x 2 ，…，x 11 . The actual measurement values are shown in the following table, in kW.
TABLE 1 instantaneous output Power of a photovoltaic Power System
| Instantaneous output power | x 1 | x 2 | x 3 | x 4 | x 5 | x 6 | x 7 | x 8 | x 9 | x 10 | x 11 |
| Time/s | 5 | 10 | 15 | 20 | 25 | 30 | 35 | 40 | 45 | 50 | 55 |
| power/kW | 0.0585 | 0.9390 | 2.6340 | 5.2560 | 7.3860 | 7.8510 | 6.4785 | 6.1155 | 3.0840 | 0.4605 | 0.0000 |
Calculating the average value of the photovoltaic power:(0.0585+0.939+2.634+5.256+7.386+7.851+6.4785+6.1155+3.084+0.4605+0)/11, calculated +.>kW. As shown in fig. 2, the photovoltaic instantaneous output power has strong fluctuation, and if the power of the unregulated load equipment is changed, serious damage is necessarily caused to the whole power system.
Step 22: the duty ratio of the washing machine was 20%, the duty ratio of the air conditioner was 30%, the duty ratio of the electric car was 40%, and the fixed duty ratio was 10% in addition. Calculating average expected power of each washing machineAverage desired power of kW, air conditioner +.>kW, average desired power of electric vehicle +.> kW。
Step 23: the higher the correlation coefficient τ of each load device is set, the closer the flexible desired power is to the instantaneous output power of the photovoltaic power generation device. Presetting a correlation coefficient tau of a washing machine, an air conditioner and an electric automobile 1 =0.2、τ 2 =0.4、τ 3 =0.6。
Step 24: and respectively calculating the consistent probability alpha and the inconsistent probability beta of the instantaneous output power data change of the washing machine, the air conditioner and the electric automobile along with the photovoltaic power generation system. Correlation coefficient τ of washing machine A =0.2, the coincidence probability α=0.6, and the non-coincidence probability β=0.4 can be obtained from the binary system of primary equations. Correlation coefficient tau of air conditioner B =0.4, a coincidence probability α=0.7, and a non-coincidence probability β=0.3 can be obtained. Correlation coefficient tau of electric automobile C =0.6, a coincidence probability α=0.8, and a non-coincidence probability β=0.2 can be obtained.
Step 251: calculating the fluctuation amplitude of instantaneous output power at adjacent sampling time, e.g. Deltax 1 =x 2 -x 1 . The 10 fluctuation amplitudes obtained from the 11 sampling moments are as follows.
TABLE 2 fluctuation amplitude of instantaneous output Power of certain photovoltaic Power System
| Amplitude of fluctuation | Δx 1 | Δx 2 | Δx 3 | Δx 4 | Δx 5 | Δx 6 | Δx 7 | Δx 8 | Δx 9 | Δx 10 |
| power/kW | 0.8805 | 1.6950 | 2.6220 | 2.1300 | 0.4650 | -1.3725 | -0.3630 | -3.0315 | -2.6235 | -0.4605 |
Step 252: and calculating the ideal fluctuation range of the flexible expected power of the washing machine, the air conditioner and the electric automobile.
Ideal fluctuation amplitude deltay of washing machine at adjacent sampling time according to load duty ratio of washing machine A =The calculation results are shown in table 3.
Table 3 ideal fluctuation width of washing machine
| Ideal fluctuation amplitude | Δy A1 | Δy A2 | Δy A3 | Δy A4 | Δy A5 | Δy A6 | Δy A7 | Δy A8 | Δy A9 | Δy A10 |
| power/kW | 0.1761 | 0.3390 | 0.5244 | 0.4260 | 0.0930 | -0.2745 | -0.0726 | -0.6063 | -0.5247 | -0.0921 |
Ideal fluctuation amplitude delta y of air conditioner at adjacent sampling time according to load duty ratio of air conditioner B =0.3 Δx, and the calculation results are shown in table 4.
TABLE 4 ideal fluctuation amplitude of air conditioner adjacency
| Ideal fluctuation amplitude | Δy B1 | Δy B2 | Δy B3 | Δy B4 | Δy B5 | Δy B6 | Δy B7 | Δy B8 | Δy B9 | Δy B10 |
| power/kW | 0.2642 | 0.5085 | 0.7866 | 0.6390 | 0.1395 | -0.4118 | -0.1089 | -0.9095 | -0.7871 | -0.1382 |
According to the load duty ratio of the electric automobile, the ideal fluctuation amplitude delta y of the electric automobile at adjacent sampling moments C =0.4Δx, and the calculation results are shown in table 5.
TABLE 5 ideal wave amplitude for electric vehicles
| Ideal fluctuation amplitude | Δy C1 | Δy C2 | Δy C3 | Δy C4 | Δy C5 | Δy C6 | Δy C7 | Δy C8 | Δy C9 | Δy C10 |
| power/kW | 0.3522 | 0.6780 | 1.0488 | 0.8520 | 0.1860 | -0.5490 | -0.1452 | -1.2126 | -1.0494 | -0.1842 |
Step 253: and determining the number i of sampling points with consistent power change and the number j of sampling points with inconsistent power change according to the consistent probability alpha and the inconsistent probability beta.
In the case of a washing machine in which a washing machine is used,. The number of sampling points with consistent power variation and the number of sampling points with inconsistent power variation of the washing machine are 6 and 4.
In the air conditioner of the present invention,. The number of sampling points with consistent power change and the number of sampling points with inconsistent power change of the air conditioner are 7 and 3.
In the case of an electric vehicle such as an electric car,. The number of sampling points with consistent power change of the electric automobile is 8, and the power change is not changedThe number of the consistent sampling points is 2.
Step 254: the actual fluctuation amplitude of the flexible desired power is calculated.
When the load device is a washing machine, j=4. May choose deltay A3 、Δy A4 、Δy A6 、Δy A8 The actual fluctuation amplitude was made equal to the negative value of the ideal fluctuation amplitude, and the remaining actual fluctuation amplitudes were the same as the ideal fluctuation amplitude, as shown in table 6.
TABLE 6 actual wave amplitude of washing machine
| Actual wave amplitude | Δy' A1 | Δy' A2 | Δy' A3 | Δy' A4 | Δy' A5 | Δy' A6 | Δy' A7 | Δy' A8 | Δy' A9 | Δy' A10 |
| power/kW | 0.1761 | 0.3390 | -0.5244 | -0.4260 | 0.0930 | 0.2745 | -0.0726 | 0.6063 | -0.5247 | -0.0921 |
When the load device is an air conditioner, j=3. May choose deltay B3 、Δy B5 、Δy B6 The actual fluctuation amplitude was made equal to the negative value of the ideal fluctuation amplitude, and the remaining actual fluctuation amplitudes were the same as the ideal fluctuation amplitude, as shown in table 7.
Table 7 actual fluctuation width of air conditioner
| Actual wave amplitude | Δy' B1 | Δy' B2 | Δy' B3 | Δy' B4 | Δy' B5 | Δy' B6 | Δy' B7 | Δy' B8 | Δy' B9 | Δy' B10 |
| power/kW | 0.2642 | 0.5085 | -0.7866 | 0.6390 | -0.1395 | 0.4118 | -0.1089 | -0.9095 | -0.7871 | -0.1382 |
The load device is when the electric vehicle, j=2. May choose deltay C4 、Δy C6 The actual fluctuation amplitude was made equal to the negative value of the ideal fluctuation amplitude, and the remaining actual fluctuation amplitudes were the same as the ideal fluctuation amplitude, as shown in table 8.
Table 8 actual wave amplitude of electric automobile
| Actual wave amplitude | Δy' C1 | Δy' C2 | Δy' C3 | Δy' C4 | Δy' C5 | Δy' C6 | Δy' C7 | Δy' C8 | Δy' C9 | Δy' C10 |
| power/kW | 0.3522 | 0.6780 | 1.0488 | -0.8520 | 0.1860 | 0.5490 | -0.1452 | -1.2126 | -1.0494 | -0.1842 |
Step 255: the flexible desired power of the load device is calculated.
When the load device is a washing machine, solving an equation set:
the flexible expected power y of the washing machine can be solved A1 ，y A2 ，…，y A11 As shown in table 9.
Table 9 flexible desired power for washing machine
| Flexible desired power | y A1 | y A2 | y A3 | y A4 | y A5 | y A6 | y A7 | y A8 | y A9 | y A10 | y A11 |
| Time/s | 5 | 10 | 15 | 20 | 25 | 30 | 35 | 40 | 45 | 50 | 55 |
| power/kW | 0.6065 | 0.7826 | 1.1216 | 0.5972 | 1.0232 | 0.9302 | 1.2047 | 0.2773 | 0.8836 | 0.3589 | 0.2668 |
When the load equipment is an air conditioner, solving an equation set:
the flexible expected power y of the air conditioner can be solved B1 ，y B2 ，…，y B11 As shown in table 10.
Table 10 flexible desired power of air conditioner
| Flexible desired power | y B1 | y B2 | y B3 | y B4 | y B5 | y B6 | y B7 | y B8 | y B9 | y B10 | y B11 |
| Time/s | 5 | 10 | 15 | 20 | 25 | 30 | 35 | 40 | 45 | 50 | 55 |
| power/kW | 0.9395 | 1.2037 | 1.7122 | 0.9256 | 1.5646 | 1.4251 | 1.8369 | 1.7280 | 0.8185 | 0.0314 | 0.0000 |
When the load equipment is an electric car, solving an equation set:
the flexible expected power output y of the electric automobile can be solved C1 ，y C2 ，…，y C11 As shown in table 11.
Table 11 flexible desired power of electric vehicle
| Flexible desired power | y C1 | y C2 | y C3 | y C4 | y C5 | y C6 | y C7 | y C8 | y C9 | y C10 | y C11 |
| Time/s | 5 | 10 | 15 | 20 | 25 | 30 | 35 | 40 | 45 | 50 | 55 |
| power/kW | 0.6087 | 0.9609 | 1.6389 | 2.6877 | 1.8357 | 2.0217 | 2.5707 | 2.4255 | 1.2129 | 0.1635 | 0.0000 |
Step 6: and (3) drawing load power curves of the load equipment washing machine, the air conditioner and the electric automobile by taking time as an abscissa, taking the unit as s, taking the flexible expected power as an ordinate and taking the unit as kW, as shown in fig. 3, 4 and 5.
In fig. 3, 4 and 5, the correlation coefficient of each flexible desired power is set to 0.2, 0.4 and 0.6. The whole trend of the load power curve generated by the three correlation coefficients is the same as the whole trend of the instantaneous output power data curve of the photovoltaic power generation system, and meanwhile, the load power curve is different due to the different correlation coefficients. The correlation coefficient of the washing machine is set to be 0.2, the overall increasing and decreasing trend of the curve is not obvious, and the correlation degree with the photovoltaic instantaneous output power data is not high. The correlation coefficient of the air conditioner and the electric automobile is set to be 0.4 and 0.6, and the fluctuation amplitude of the load power curve of the electric automobile is larger compared with that of the load power curve of the air conditioner, and the load power curve of the electric automobile is closer to the photovoltaic output power data curve. The user can regulate the flexible load power of the load device according to the load power curve.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
Claims (6)
1. The flexible load power regulation and control method based on the correlation coefficient is characterized by comprising the following steps of:
step 1: selected photovoltaic power generation systemThe photovoltaic power generation system is connected with at least two load devices, the instantaneous output power of the photovoltaic power generation system is collected at n sampling moments, and the average output power is calculated；
Step 2: determining the duty ratio of each load device, and calculating the average expected power of the load devices;
step 3: setting a correlation coefficient tau of flexible expected power of each load device and instantaneous output power of the photovoltaic power generation system;
step 4: calculating the consistent probability alpha and the inconsistent probability beta of the flexible expected power along with the change of the instantaneous output power according to the correlation coefficient tau;
step 5: calculating fluctuation amplitude of the instantaneous output power at adjacent sampling moments, calculating ideal fluctuation amplitude of flexible expected power according to the fluctuation amplitude of the instantaneous output power, calculating actual fluctuation amplitude of the flexible expected power according to the consistent probability alpha and the inconsistent probability beta, and calculating flexible expected power of load equipment;
step 6: and drawing a load power curve of the load equipment according to the flexible expected power at n sampling moments, and regulating and controlling the flexible load power of the load equipment according to the load power curve.
2. The flexible load power regulation method of claim 1 wherein the instantaneous output power of the photovoltaic power generation system at n sampling instants is x respectively 1 ，x 2 ，…，x n Average output power。
3. The flexible load power regulation method of claim 1, wherein the average desired power of the load deviceK is the duty cycle of the load device.
4. The flexible load power regulation method according to claim 1, wherein the coincidence probability α and the non-coincidence probability β satisfy the condition: α+β=1 and α - β=τ.
5. The flexible load power regulation and control method according to claim 1, wherein the number i of sampling points with consistent power variation and the number j of sampling points with inconsistent power variation are determined according to the consistent probability alpha and the inconsistent probability beta, and the conditions are satisfied by i, j: i+j=n-1, i/j=α/β, and the fluctuation direction of i sampling points is adjusted to be the same direction, and the fluctuation direction of j sampling points is adjusted to be opposite direction.
6. The flexible load power regulation method of claim 1 wherein the flexible expected power y for n sampling instants is calculated from the actual fluctuation amplitude for adjacent sampling instants 1 ，y 2 ，…，y n 。
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