New energy power generation side power prediction method considering energy storage system

Abstract

The invention belongs to the technical field of new energy power generation, and particularly relates to a new energy power generation side power prediction method considering an energy storage system, and the method comprises the steps: carrying out the analysis through combining temperature data, illumination intensity data, energy storage electric quantity data, load data and a photovoltaic panel dust deposition factor, and obtaining a power generation coefficient; comparing the power generation coefficient FD with a preset power generation coefficient threshold YF; whether the new energy power generation side power meets the supply and demand requirements or not can be accurately predicted through analysis of the power generation coefficient, power failure and large economic loss caused by insufficient power supply are avoided, and after a second-level alarm signal is obtained, accumulated dust of a photovoltaic panel is cleaned, which is the simplest and effective measure for improving the power generation power of the photovoltaic panel, so that the method is suitable for large-scale popularization and application. After a photovoltaic panel is cleaned, power generation coefficients are obtained again for comparison, signal type output is changed, and prediction of power generation power of a new energy power generation side is judged more intelligently.

Description

Technical Field

[0001] The present invention belongs to the technical field of renewable energy power generation, and in particular is a method for predicting power on the renewable energy power generation side taking into account an energy storage system. Background Art

[0002] With the rapid development of renewable energy power generation technology, how to accurately predict the power of renewable energy power generation has become a key issue. Due to the volatility and uncontrollability of renewable energy power generation, traditional prediction methods often have problems such as low prediction accuracy and poor stability. At the same time, although the introduction of energy storage systems can alleviate the fluctuations of renewable energy power generation to a certain extent, how to reasonably configure energy storage systems and accurately predict their power output is also a problem that needs to be solved urgently.

[0003] A patent with publication number CN113193553B discloses a method and system for predicting power on the power generation side of a new energy source combined with an energy storage system. The method comprises the following steps: observing information on clouds in the sky based on real-time satellite cloud images, weather radars, and ground imaging to obtain a trend of cloud changes in the area where the photovoltaic power station is located in a future set time period; analyzing the operating status of the photovoltaic power station in a future set time period in combination with the cloud change trend and the photovoltaic power station power generation model, and obtaining the expected output of the energy storage system by comparing the short-term power prediction value and the real-time prediction value of the photovoltaic power station; establishing an energy storage model for the energy storage system, taking the income of the photovoltaic power station, the income from recovering abandoned power, and the reduction of assessment income as the objective function, and taking the energy storage model as a constraint condition, so that the objective function obtains the optimal solution of the energy storage charge and discharge judgment result, that is, the power generation side power of the combined power station is obtained; improving the accuracy of the prediction and irradiance forecast, and ensuring the reliability of the ultra-short-term power prediction of the photovoltaic power station.

[0004] In the above-mentioned prior art, only the impact of meteorological factors on the power prediction of the renewable energy power generation side is considered, but the factors of the state of the renewable energy power generation side itself are not taken into comprehensive consideration, and only the power generation size is predicted, and different types of measures cannot be adjusted according to the power generation prediction results.

[0005] To this end, the present invention provides a method for predicting power on the renewable energy generation side taking into account an energy storage system. Summary of the invention

[0006] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0007] The technical solution adopted by the present invention to solve the technical problem is: a power prediction method for the renewable energy power generation side considering the energy storage system described in the present invention comprises: S1: Set the collection cycle and divide the collection cycle into several sub-collection time periods, marked as i, where i=1,2,3...n, and n is the last sub-collection time period; S2: Real-time acquisition of temperature data, light intensity data, energy storage data, load data and photovoltaic panel dust accumulation data within the sub-collection time period, and marked as temperature value WDi, light intensity value GDi, energy storage data CNi, load power FZi and photovoltaic panel dust accumulation thickness value HDi respectively; S3: According to the temperature data, light intensity data, energy storage data, load power data, and photovoltaic panel dust accumulation data in the sub-collection time period, the temperature difference value WC, light difference value GC, average energy storage value JCN, average load value JFZ, and photovoltaic panel dust accumulation value JH are obtained through analysis; S4: Process the temperature difference value WC, the light difference value GC, the average energy storage value JCN, the average load value JFZ and the photovoltaic panel dust accumulation value JH to obtain the power generation coefficient FD within the collection period, compare the power generation coefficient FD with the preset power generation coefficient threshold value YF, and generate a control signal; S5: Take corresponding control measures based on the type of control signal.

[0008] Preferably, the specific method for obtaining the temperature difference value WC is: The highest temperature value WDg and the lowest temperature value WDd among all the temperature values ​​WDi in the acquisition period are obtained, the difference between the highest temperature value WDg and the lowest temperature value WDd is calculated, and the obtained difference is marked as the temperature difference value WC.

[0009] Preferably, the method for obtaining the light difference value GC is: The maximum light intensity value GDg and the minimum light intensity value GDd of all the light intensity values ​​GDi in the acquisition period are obtained, the difference between the maximum light intensity value GDg and the minimum light intensity value GDd is calculated, and the obtained difference is marked as the light difference value GC.

[0010] Preferably, the energy storage capacity CNi is obtained in the following manner: All energy storage capacities CNi within the acquisition period are obtained, summed and averaged, and marked as the average energy storage value JCN.

[0011] Preferably, the method for obtaining the average load value JFZ is specifically as follows: All load powers FZi within the collection period are obtained, summed and averaged, and marked as the average load value JFZ.

[0012] Preferably, the photovoltaic panel dust accumulation value JH is obtained in the following manner: Obtain the dust accumulation thickness value HDi of the photovoltaic panel in each sub-collection time period within the collection cycle, obtain the dust accumulation thickness value HD1 of the photovoltaic panel collected in the first collection time period t1, and the dust accumulation thickness value HDn of the photovoltaic panel collected in the last sub-collection time period tn, through the formula The photovoltaic panel dust accumulation growth value HX is obtained, the time difference YDC between the current time and the predicted time is obtained, and the time difference YDC is multiplied by the photovoltaic panel dust accumulation growth value HX to obtain the photovoltaic panel dust accumulation value JH.

[0013] Preferably, the specific method of obtaining the power generation coefficient FD is: Substitute the temperature difference value WC, light difference value GC, average energy storage value JCN, average load value JFZ and photovoltaic panel dust accumulation value JH into the formula The power generation coefficient FD within the collection period is obtained, where a1, a2, a3, a4, and a5 are all preset proportional coefficients, and a1+a2+a3+a4+a5=1.

[0014] Preferably, the preset power generation coefficient threshold value YF includes a first preset power generation coefficient threshold value YF1 and a second preset power generation coefficient threshold value YF2; If the power generation coefficient FD> the first preset power generation coefficient threshold value YF1, it means that the power supply cannot be normal, and a first-level alarm signal is generated; If the second preset power generation coefficient threshold value YF2 ≤ power generation coefficient FD ≤ first preset power generation coefficient threshold value YF1, it indicates that power supply is barely sufficient and a level 2 alarm signal is generated; If the power generation coefficient FD is less than the second preset power generation coefficient threshold value YF2, it means that the power supply can be normal, a normal signal is generated, and no operation is required.

[0015] Preferably, after receiving the first-level alarm signal, the load power on the renewable energy power generation side is reduced and regulated.

[0016] Preferably, after receiving the secondary alarm signal, the photovoltaic panel is cleaned to reduce the dust accumulation value JH of the photovoltaic panel, and the power generation coefficient FD is obtained again after cleaning, and compared with the preset power generation coefficient threshold value YF again; If the power generation coefficient FD ≥ the second preset power generation coefficient threshold value YF2, the secondary alarm signal is converted into a primary alarm signal output; If the power generation coefficient FD is less than the second preset power generation coefficient threshold value YF2, the secondary alarm signal is converted into a normal signal output.

[0017] The beneficial effects of the present invention are as follows: 1. The present invention describes a method for predicting power on the renewable energy power generation side taking into account an energy storage system. According to the load power and energy storage capacity on the renewable energy power generation side, if normal power supply is to be met, there needs to be a requirement for the power generation power. By combining temperature data, light intensity data, energy storage capacity data, load data and photovoltaic panel dust accumulation factors, the power generation coefficient is analyzed and obtained, and the power generation coefficient FD is compared with a preset power generation coefficient threshold value YF. Through the analysis of the power generation coefficient, it is possible to accurately predict whether the power on the renewable energy power generation side meets the supply and demand requirements, thereby avoiding power outages caused by insufficient power supply and causing large economic losses.

[0018] 2. The present invention describes a method for predicting the power of a new energy power generation side taking into account an energy storage system. After obtaining a secondary alarm signal, since the second preset power generation coefficient threshold value YF2≤power generation coefficient FD≤first preset power generation coefficient threshold value YF1, power is barely supplied, indicating that there is still a risk of insufficient power supply, and the power supply demand can be met by increasing the power generation power. Cleaning the dust on the photovoltaic panel is the simplest and most effective measure to increase the power generation power of the photovoltaic panel. After cleaning the photovoltaic panel, the power generation coefficient is obtained again. If the power generation coefficient is still greater than or equal to the second preset power generation coefficient threshold value YF2, it indicates that the load demand cannot be met by increasing the power generation efficiency. Therefore, the secondary alarm signal is converted into a primary alarm signal output for more insurance. When the power generation coefficient is less than the second preset power generation coefficient threshold value YF2, it indicates that the power generation power is improved after cleaning the photovoltaic panel, which can meet the power supply demand, and there is no need to take load reduction measures, which effectively guarantees the normal power supply of the region, avoids economic losses caused by power outages, and makes a more intelligent judgment on the prediction of the power generation power of the new energy power generation side. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The present invention will be further described below in conjunction with the accompanying drawings.

[0020] Figure 1 It is a method flow chart of a method for predicting power on the renewable energy generation side considering an energy storage system of the present invention; Figure 2 It is a structural schematic diagram of the mobile mechanism of the present invention; Figure 3 is a schematic diagram of an electronic device of the present invention; Figure 4 It is a schematic diagram of the storage medium of the present invention. DETAILED DESCRIPTION

[0021] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0022] Embodiment 1 like Figure 1As shown, a method for predicting power on the renewable energy generation side considering an energy storage system according to an embodiment of the present invention includes: S1: Set the collection cycle and divide the collection cycle into several sub-collection time periods, marked as i, where i=1,2,3...n, and n is the last sub-collection time period; S2: Real-time acquisition of temperature data, light intensity data, energy storage data, load data and photovoltaic panel dust accumulation data within the sub-collection time period, and marked as temperature value WDi, light intensity value GDi, energy storage data CNi, load power FZi and photovoltaic panel dust accumulation thickness value HDi respectively; S3: According to the temperature data, light intensity data, energy storage data, load power data, and photovoltaic panel dust accumulation data in the sub-collection time period, the temperature difference value WC, light difference value GC, average energy storage value JCN, average load value JFZ, and photovoltaic panel dust accumulation value JH are obtained through analysis; S4: Process the temperature difference value WC, the light difference value GC, the average energy storage value JCN, the average load value JFZ and the photovoltaic panel dust accumulation value JH to obtain the power generation coefficient FD within the collection period, compare the power generation coefficient FD with the preset power generation coefficient threshold value YF, and generate a control signal; S5: Take corresponding control measures based on the type of control signal.

[0023] The specific method for obtaining the temperature difference value WC is: The highest temperature value WDg and the lowest temperature value WDd among all the temperature values ​​WDi in the acquisition period are obtained, the difference between the highest temperature value WDg and the lowest temperature value WDd is calculated, and the obtained difference is marked as the temperature difference value WC.

[0024] The method for obtaining the light difference value GC is: The maximum light intensity value GDg and the minimum light intensity value GDd of all the light intensity values ​​GDi in the acquisition period are obtained, the difference between the maximum light intensity value GDg and the minimum light intensity value GDd is calculated, and the obtained difference is marked as the light difference value GC.

[0025] The method for obtaining the energy storage capacity CNi is specifically as follows: All energy storage capacities CNi within the acquisition period are obtained, summed and averaged, and marked as the average energy storage value JCN.

[0026] The method for obtaining the average load value JFZ is specifically as follows: All load powers FZi within the collection period are obtained, summed and averaged, and marked as the average load value JFZ.

[0027] The photovoltaic panel dust accumulation value JH is obtained as follows: Obtain the dust accumulation thickness value HDi of the photovoltaic panel in each sub-collection time period within the collection cycle, obtain the dust accumulation thickness value HD1 of the photovoltaic panel collected in the first collection time period t1, and the dust accumulation thickness value HDn of the photovoltaic panel collected in the last sub-collection time period tn, through the formula The photovoltaic panel dust accumulation growth value HX is obtained, the time difference YDC between the current time and the predicted time is obtained, and the time difference YDC is multiplied by the photovoltaic panel dust accumulation growth value HX to obtain the photovoltaic panel dust accumulation value JH.

[0028] The specific method of obtaining the power generation coefficient FD is: Substitute the temperature difference value WC, light difference value GC, average energy storage value JCN, average load value JFZ and photovoltaic panel dust accumulation value JH into the formula The power generation coefficient FD within the collection period is obtained, where a1, a2, a3, a4, and a5 are all preset proportional coefficients, and a1+a2+a3+a4+a5=1.

[0029] In some embodiments, according to the load power and energy storage capacity on the new energy power generation side, if normal power supply is to be met, requirements for power generation power are required. The power generation coefficient is obtained by combining temperature data, light intensity data, energy storage capacity data, load data and photovoltaic panel dust accumulation factors, and the power generation coefficient FD is compared with the preset power generation coefficient threshold YF. Through the analysis of the power generation coefficient, it is possible to accurately predict whether the power on the new energy power generation side meets the supply and demand requirements, thereby avoiding power outages caused by insufficient power supply and causing large economic losses.

[0030] Embodiment 2 Comparative Example 1, wherein another embodiment of the present invention is: like Figure 2 As shown, the control signal types specifically include a first-level alarm signal, a second-level alarm signal and a normal signal.

[0031] The preset power generation coefficient threshold value YF includes a first preset power generation coefficient threshold value YF1 and a second preset power generation coefficient threshold value YF2; If the power generation coefficient FD> the first preset power generation coefficient threshold value YF1, it means that the power supply cannot be normal, and a first-level alarm signal is generated; If the second preset power generation coefficient threshold value YF2 ≤ power generation coefficient FD ≤ first preset power generation coefficient threshold value YF1, it indicates that power supply is barely sufficient and a level 2 alarm signal is generated; If the power generation coefficient FD is less than the second preset power generation coefficient threshold value YF2, it means that the power supply can be normal, a normal signal is generated, and no operation is required.

[0032] After receiving the first-level alarm signal, the load power on the renewable energy power generation side is reduced and regulated.

[0033] It is understandable that the first-level alarm signal means that at the predicted moment, the power generation side of the renewable energy power generation side will certainly be insufficient. If it is not notified in time, the factory or enterprise will suddenly lose power during normal product processing, which may easily cause heavy losses. The present invention can carry out load early warning regulation in advance, and can notify the factories or enterprises in the area in advance to carry out regulation, so as to minimize economic losses.

[0034] After receiving the secondary alarm signal, the photovoltaic panel is cleaned to reduce the dust accumulation value JH of the photovoltaic panel, and the power generation coefficient FD is obtained again after cleaning, and compared with the preset power generation coefficient threshold value YF again; If the power generation coefficient FD ≥ the second preset power generation coefficient threshold value YF2, the secondary alarm signal is converted into a primary alarm signal output; If the power generation coefficient FD is less than the second preset power generation coefficient threshold value YF2, the secondary alarm signal is converted into a normal signal output.

[0035] It can be understood that after obtaining the secondary alarm signal, since the second preset power generation coefficient threshold value YF2≤power generation coefficient FD≤first preset power generation coefficient threshold value YF1, power supply is barely provided, indicating that there is still a risk of insufficient power supply, and the power supply demand can be met by increasing the power generation capacity. Cleaning the dust on the photovoltaic panel is the simplest and most effective measure to increase the power generation capacity of the photovoltaic panel. After cleaning the photovoltaic panel, the power generation coefficient is obtained again. If the power generation coefficient is still greater than or equal to the second preset power generation coefficient threshold value YF2, it indicates that the load demand cannot be met by increasing the power generation efficiency. Therefore, the secondary alarm signal is converted into a first-level alarm signal output for more insurance. When the power generation coefficient is less than the second preset power generation coefficient threshold value YF2, it indicates that the power generation capacity is improved after cleaning the photovoltaic panel, which can meet the power supply demand, and there is no need to take load reduction measures, which effectively guarantees the normal power supply in the area, avoids economic losses caused by power outages, and makes it possible to more intelligently judge the prediction of the power generation capacity on the new energy power generation side.

[0036] See also Figure 3 , Figure 3 Schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, an embodiment of the present invention provides an electronic device 500, including a memory 510, a processor 520, and a computer program 511 stored in the memory 510 and executable on the processor 520. When the processor 520 executes the computer program 511, the following steps are implemented: S1: setting a collection period, dividing the collection period into a plurality of sub-collection time periods, marked as i, where i=1, 2, 3...n, and n is the last sub-collection time period; S2: Real-time acquisition of temperature data, light intensity data, energy storage data, load data and photovoltaic panel dust accumulation data within the sub-collection time period, and marked as temperature value WDi, light intensity value GDi, energy storage data CNi, load power FZi and photovoltaic panel dust accumulation thickness value HDi respectively; S3: According to the temperature data, light intensity data, energy storage data, load power data, and photovoltaic panel dust accumulation data in the sub-collection time period, the temperature difference value WC, light difference value GC, average energy storage value JCN, average load value JFZ, and photovoltaic panel dust accumulation value JH are obtained through analysis; S4: Process the temperature difference value WC, the light difference value GC, the average energy storage value JCN, the average load value JFZ and the photovoltaic panel dust accumulation value JH to obtain the power generation coefficient FD within the collection period, compare the power generation coefficient FD with the preset power generation coefficient threshold value YF, and generate a control signal; S5: Take corresponding control measures based on the type of control signal.

[0037] See also Figure 4 , Figure 4 A schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present invention. Figure 4 As shown, this embodiment provides a computer-readable storage medium 600, on which a computer program 611 is stored. When the computer program 611 is executed by a processor, the following steps are implemented: S1: setting a collection period, dividing the collection period into a plurality of sub-collection time periods, marked as i, where i=1, 2, 3...n, and n is the last sub-collection time period; S2: Real-time acquisition of temperature data, light intensity data, energy storage data, load data and photovoltaic panel dust accumulation data within the sub-collection time period, and marked as temperature value WDi, light intensity value GDi, energy storage data CNi, load power FZi and photovoltaic panel dust accumulation thickness value HDi respectively; S3: According to the temperature data, light intensity data, energy storage data, load power data, and photovoltaic panel dust accumulation data in the sub-collection time period, the temperature difference value WC, light difference value GC, average energy storage value JCN, average load value JFZ, and photovoltaic panel dust accumulation value JH are obtained through analysis; S4: Process the temperature difference value WC, the light difference value GC, the average energy storage value JCN, the average load value JFZ and the photovoltaic panel dust accumulation value JH to obtain the power generation coefficient FD within the collection period, compare the power generation coefficient FD with the preset power generation coefficient threshold value YF, and generate a control signal; S5: Take corresponding control measures based on the type of control signal.

[0038] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0039] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0040] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0041] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0042] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0043] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0044] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for predicting power on the renewable energy generation side considering an energy storage system, characterized in that: include S1: Set the collection cycle and divide the collection cycle into several sub-collection time periods, marked as i, where i=1,2,3...n, and n is the last sub-collection time period; S2: Real-time acquisition of temperature data, light intensity data, energy storage data, load data and photovoltaic panel dust accumulation data within the sub-collection time period, and marked as temperature value WDi, light intensity value GDi, energy storage data CNi, load power FZi and photovoltaic panel dust accumulation thickness value HDi respectively; S3: According to the temperature data, light intensity data, energy storage data, load power data, and photovoltaic panel dust accumulation data in the sub-collection time period, the temperature difference value WC, light difference value GC, average energy storage value JCN, average load value JFZ, and photovoltaic panel dust accumulation value JH are obtained through analysis; S4: Process the temperature difference value WC, the light difference value GC, the average energy storage value JCN, the average load value JFZ and the photovoltaic panel dust accumulation value JH to obtain the power generation coefficient FD within the collection period, compare the power generation coefficient FD with the preset power generation coefficient threshold value YF, and generate a control signal; S5: Take corresponding control measures based on the type of control signal.

2. A method for predicting power on the renewable energy generation side considering energy storage systems according to claim 1, characterized in that: The specific method for obtaining the temperature difference value WC is: The highest temperature value WDg and the lowest temperature value WDd among all the temperature values ​​WDi in the acquisition period are obtained, the difference between the highest temperature value WDg and the lowest temperature value WDd is calculated, and the obtained difference is marked as the temperature difference value WC.

3. A method for predicting power on the renewable energy generation side considering energy storage systems according to claim 1, characterized in that: The method for obtaining the light difference value GC is: The maximum light intensity value GDg and the minimum light intensity value GDd of all the light intensity values ​​GDi in the acquisition period are obtained, the difference between the maximum light intensity value GDg and the minimum light intensity value GDd is calculated, and the obtained difference is marked as the light difference value GC.

4. A method for predicting power on the renewable energy generation side considering energy storage system according to claim 1, characterized in that: The method for obtaining the energy storage capacity CNi is specifically as follows: All energy storage capacities CNi within the acquisition period are obtained, summed and averaged, and marked as the average energy storage value JCN.

5. The method for predicting power of renewable energy generation side considering energy storage system according to claim 1, characterized in that: The method for obtaining the average load value JFZ is specifically as follows: All load powers FZi within the collection period are obtained, summed and averaged, and marked as the average load value JFZ.

6. A method for predicting power on the renewable energy generation side considering energy storage system according to claim 1, characterized in that: The photovoltaic panel dust accumulation value JH is obtained as follows: Obtain the dust accumulation thickness value HDi of the photovoltaic panel in each sub-collection time period within the collection cycle, obtain the dust accumulation thickness value HD1 of the photovoltaic panel collected in the first collection time period t1, and the dust accumulation thickness value HDn of the photovoltaic panel collected in the last sub-collection time period tn, through the formula The photovoltaic panel dust accumulation growth value HX is obtained, the time difference YDC between the current time and the predicted time is obtained, and the time difference YDC is multiplied by the photovoltaic panel dust accumulation growth value HX to obtain the photovoltaic panel dust accumulation value JH.

7. A method for predicting power on the renewable energy generation side considering energy storage systems according to claim 1, characterized in that: The specific method of obtaining the power generation coefficient FD is: Substitute the temperature difference value WC, light difference value GC, average energy storage value JCN, average load value JFZ and photovoltaic panel dust accumulation value JH into the formula The power generation coefficient FD within the collection period is obtained, where a1, a2, a3, a4, and a5 are all preset proportional coefficients, and a1+a2+a3+a4+a5=1.

8. The method for predicting power of renewable energy generation side considering energy storage system according to claim 1, characterized in that: The preset power generation coefficient threshold value YF includes a first preset power generation coefficient threshold value YF1 and a second preset power generation coefficient threshold value YF2; If the power generation coefficient FD> the first preset power generation coefficient threshold value YF1, it means that the power supply cannot be normal, and a first-level alarm signal is generated; If the second preset power generation coefficient threshold value YF2 ≤ power generation coefficient FD ≤ first preset power generation coefficient threshold value YF1, it indicates that power supply is barely sufficient and a level 2 alarm signal is generated; If the power generation coefficient FD is less than the second preset power generation coefficient threshold value YF2, it means that the power supply can be normal, a normal signal is generated, and no operation is required.

9. A method for predicting power on the renewable energy generation side considering energy storage systems according to claim 8, characterized in that: After receiving the first-level alarm signal, the load power on the renewable energy power generation side is reduced and regulated.

10. A method for predicting power on the renewable energy generation side considering energy storage systems according to claim 8, characterized in that: After receiving the secondary alarm signal, the photovoltaic panel is cleaned to reduce the dust accumulation value JH of the photovoltaic panel, and the power generation coefficient FD is obtained again after cleaning, and compared with the preset power generation coefficient threshold value YF again; If the power generation coefficient FD ≥ the second preset power generation coefficient threshold value YF2, the secondary alarm signal is converted into a primary alarm signal output; If the power generation coefficient FD is less than the second preset power generation coefficient threshold value YF2, the secondary alarm signal is converted into a normal signal output.

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