Source network load storage coordination control method and system

Abstract

The invention belongs to the technical field of new energy, and discloses a source network load storage coordination control method and system, and the method comprises the following steps: S1, obtaining real-time wind power generation data, real-time photovoltaic power generation data, predicted wind power generation data, predicted photovoltaic power generation data, real-time energy storage system data, real-time hydrogen production system data and real-time hydrogen utilization system data; s2, the real-time wind power generation data, the real-time photovoltaic power generation data, the predicted wind power generation data, the predicted photovoltaic power generation data, the real-time energy storage system data, the real-time hydrogen production system data, the real-time hydrogen utilization system data and three pre-trained source network load storage coordination control models are utilized to obtain the real-time wind power generation data, the real-time photovoltaic power generation data, the predicted wind power generation data, the predicted photovoltaic power generation data, the real-time energy storage system data and the three pre-trained source network load storage coordination control models; three real-time coordination control schemes are obtained, and a final real-time coordination control scheme is obtained through screening according to the credibility of the three real-time coordination control schemes; wherein the three pre-trained source network load storage coordination control models comprise a pre-trained support vector machine model, a pre-trained random forest model and a pre-trained neural network. The efficiency is high, and the wind and light abandoning rate can be reduced.

Description

Technical Field

[0001] The present invention relates to the field of new energy technology, and more particularly to a source-grid-load-storage coordinated control method and system. Background Art

[0002] Source-grid-load-storage is a new type of power operation mode with "power source, grid, load, and energy storage" as the overall planning. The coordinated control method of the source-grid-load-storage system composed of photovoltaic power generation system, wind power generation system, energy storage system, grid, hydrogen production system and hydrogen use system mostly adopts manual methods, which is not only inefficient but also increases the rate of wind and solar power curtailment.

[0003] Therefore, how to provide a source-grid-load-storage coordinated control method and system that is highly efficient and can reduce the wind and solar power curtailment rate is an urgent problem that needs to be solved by those skilled in the art. Summary of the Invention

[0004] In view of this, an object of the present invention is to provide a source-grid-load-storage coordinated control method and system.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] In a first aspect, a source-grid-load-storage coordinated control method is provided, comprising the following steps:

[0007] S1: Acquire real-time wind power generation data, real-time photovoltaic power generation data, predicted wind power generation data, predicted photovoltaic power generation data, real-time energy storage system data, real-time hydrogen production system data, and real-time hydrogen use system data;

[0008] S2: Utilize the real-time wind power generation data, the real-time photovoltaic power generation data, the predicted wind power generation data, the predicted photovoltaic power generation data, the real-time energy storage system data, the real-time hydrogen production system data, the real-time hydrogen consumption system data and three pre-trained source-grid-load-storage coordinated control models to obtain three real-time coordinated control schemes, and obtain the final real-time coordinated control scheme based on the credibility screening of the three real-time coordinated control schemes; wherein, the three pre-trained source-grid-load-storage coordinated control models include a pre-trained support vector machine model, a pre-trained random forest model and a pre-trained neural network.

[0009] Preferably, S2 specifically includes the following steps:

[0010] S21: Calculating the difference between the predicted wind power generation data and the real-time wind power generation data to obtain wind power generation difference data;

[0011] Calculating the difference between the predicted photovoltaic power generation data and the real-time photovoltaic power generation data to obtain photovoltaic power generation difference data;

[0012] S22: inputting the wind power generation difference data, the photovoltaic power generation difference data, the real-time energy storage system data, the real-time hydrogen production system data, and the real-time hydrogen use system data into the pre-trained support vector machine model to obtain a first real-time coordinated control scheme;

[0013] Inputting the wind power generation difference data, the photovoltaic power generation difference data, the real-time energy storage system data, the real-time hydrogen production system data, and the real-time hydrogen consumption system data into the pre-trained random forest model to obtain a second real-time coordinated control scheme;

[0014] Inputting the wind power generation difference data, the photovoltaic power generation difference data, the real-time energy storage system data, the real-time hydrogen production system data, and the real-time hydrogen use system data into the pre-trained neural network to obtain a third real-time coordinated control scheme;

[0015] S23: If the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are all higher than the credibility threshold, performing random voting on the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme and selecting the real-time coordinated control scheme with the highest number of votes as the final real-time coordinated control scheme;

[0016] If two of the credibility levels of the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are higher than the credibility threshold, the real-time coordinated control scheme with the highest credibility is used as the final real-time coordinated control scheme;

[0017] If the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme and the third real-time coordinated control scheme are all lower than the credibility threshold or only one credibility is higher than the credibility threshold, then the confidence of the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme and the third real-time coordinated control scheme is calculated, and the sum of the squares of the credibility and confidence of the three real-time coordinated control schemes is calculated, and the real-time coordinated control scheme with the largest sum of squares is used as the final real-time coordinated control scheme.

[0018] Preferably, the real-time wind power generation data includes real-time wind power generation efficiency, real-time wind power generation power and real-time wind power generation power change rate;

[0019] The predicted wind power generation data includes predicted wind power generation efficiency, predicted wind power generation power and predicted wind power generation power change rate;

[0020] The real-time photovoltaic power generation data includes real-time photovoltaic power generation efficiency, real-time photovoltaic power generation power and real-time photovoltaic power generation power change rate;

[0021] The predicted photovoltaic power generation data includes predicted photovoltaic power generation efficiency, predicted photovoltaic power generation power and predicted photovoltaic power generation power change rate;

[0022] The real-time energy storage system data includes real-time charging active power, real-time discharging active power, charging available power, discharging available power, energy storage SOC and energy storage SOH;

[0023] The real-time hydrogen production system data includes electrolyzer real-time power, electrolyzer real-time current, electrolyzer temperature, electrolyzer pressure, hydrogen production main pipe pressure, hydrogen production flow, hydrogen storage tank pressure and hydrogen transmission flow;

[0024] The real-time hydrogen usage system data includes real-time hydrogen usage.

[0025] Preferably, the final real-time coordinated control plan includes an energy storage system charging schedule, an energy storage system discharging schedule, a planned grid-connected power, a planned electricity purchase power, and a planned hydrogen production volume.

[0026] Preferably, the credibility threshold is 0.7.

[0027] In a second aspect, a source-grid-load-storage coordinated control system is provided, comprising a data acquisition unit and a real-time coordinated control solution output module;

[0028] The data acquisition unit is used to acquire real-time wind power generation data, real-time photovoltaic power generation data, predicted wind power generation data, predicted photovoltaic power generation data, real-time energy storage system data, real-time hydrogen production system data and real-time hydrogen use system data;

[0029] The real-time coordinated control scheme output module is used to utilize the real-time wind power generation data, the real-time photovoltaic power generation data, the predicted wind power generation data, the predicted photovoltaic power generation data, the real-time energy storage system data, the real-time hydrogen production system data, the real-time hydrogen consumption system data and three pre-trained source-grid-load-storage coordinated control models to obtain three real-time coordinated control schemes, and obtain the final real-time coordinated control scheme based on the credibility screening of the three real-time coordinated control schemes; wherein, the three pre-trained source-grid-load-storage coordinated control models include a pre-trained support vector machine model, a pre-trained random forest model and a pre-trained neural network.

[0030] Preferably, the real-time coordinated control scheme output module includes a wind power generation difference data calculation module, a photovoltaic power generation difference data calculation module, a first real-time coordinated control scheme acquisition module, a second real-time coordinated control scheme acquisition module, a third real-time coordinated control scheme acquisition module and a final real-time coordinated control scheme acquisition module;

[0031] The wind power generation difference data calculation module is used to calculate the difference between the predicted wind power generation data and the real-time wind power generation data to obtain wind power generation difference data;

[0032] The photovoltaic power generation difference data calculation module is used to calculate the difference between the predicted photovoltaic power generation data and the real-time photovoltaic power generation data to obtain photovoltaic power generation difference data;

[0033] The first real-time coordinated control scheme acquisition module is used to input the wind power generation difference data, the photovoltaic power generation difference data, the real-time energy storage system data, the real-time hydrogen production system data and the real-time hydrogen use system data into the pre-trained support vector machine model to obtain a first real-time coordinated control scheme;

[0034] The second real-time coordinated control scheme acquisition module is used to input the wind power generation difference data, the photovoltaic power generation difference data, the real-time energy storage system data, the real-time hydrogen production system data, and the real-time hydrogen consumption system data into the pre-trained random forest model to obtain a second real-time coordinated control scheme;

[0035] The third real-time coordinated control scheme acquisition module is used to input the wind power generation difference data, the photovoltaic power generation difference data, the real-time energy storage system data, the real-time hydrogen production system data, and the real-time hydrogen use system data into the pre-trained neural network to obtain a third real-time coordinated control scheme;

[0036] The final real-time coordinated control scheme acquisition module is used to obtain the final real-time coordinated control scheme. Specifically, if the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are all higher than the credibility threshold, the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are randomly voted and the real-time coordinated control scheme with the highest number of votes is used as the final real-time coordinated control scheme.

[0037] If two of the credibility levels of the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are higher than the credibility threshold, the real-time coordinated control scheme with the highest credibility is used as the final real-time coordinated control scheme;

[0038] If the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme and the third real-time coordinated control scheme are all lower than the credibility threshold or only one credibility is higher than the credibility threshold, then the confidence of the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme and the third real-time coordinated control scheme is calculated, and the sum of the squares of the credibility and confidence of the three real-time coordinated control schemes is calculated, and the real-time coordinated control scheme with the largest sum of squares is used as the final real-time coordinated control scheme.

[0039] Preferably, the real-time wind power generation data includes real-time wind power generation efficiency, real-time wind power generation power and real-time wind power generation power change rate;

[0040] The predicted wind power generation data includes predicted wind power generation efficiency, predicted wind power generation power and predicted wind power generation power change rate;

[0041] The real-time photovoltaic power generation data includes real-time photovoltaic power generation efficiency, real-time photovoltaic power generation power and real-time photovoltaic power generation power change rate;

[0042] The predicted photovoltaic power generation data includes predicted photovoltaic power generation efficiency, predicted photovoltaic power generation power and predicted photovoltaic power generation power change rate;

[0043] The real-time energy storage system data includes real-time charging active power, real-time discharging active power, charging available power, discharging available power, energy storage SOC and energy storage SOH;

[0044] The real-time hydrogen production system data includes electrolyzer real-time power, electrolyzer real-time current, electrolyzer temperature, electrolyzer pressure, hydrogen production main pipe pressure, hydrogen production flow, hydrogen storage tank pressure and hydrogen transmission flow;

[0045] The real-time hydrogen usage system data includes real-time hydrogen usage.

[0046] Preferably, the final real-time coordinated control plan includes an energy storage system charging schedule, an energy storage system discharging schedule, a planned grid-connected power, a planned electricity purchase power, and a planned hydrogen production volume.

[0047] Preferably, the credibility threshold is 0.7.

[0048] In a third aspect, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, a source-grid-load-storage coordinated control method as described above is implemented.

[0049] In a fourth aspect, a non-transitory computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, a source-grid-load-storage coordinated control method as described in any one of the above is implemented.

[0050] In a fifth aspect, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements a source-grid-load-storage coordinated control method as described in any one of the above.

[0051] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses a source-grid-load-storage coordinated control method and system, which is highly efficient and can reduce the wind and solar power curtailment rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0053] Figure 1 A flow chart of a source-grid-load-storage coordinated control method provided by the present invention;

[0054] Figure 2 A schematic diagram of an electronic device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0056] On the one hand, if Figure 1 As shown, the embodiment of the present invention discloses a source-grid-load-storage coordinated control method, comprising the following steps:

[0057] S1: Acquire real-time wind power generation data, real-time photovoltaic power generation data, predicted wind power generation data, predicted photovoltaic power generation data, real-time energy storage system data, real-time hydrogen production system data, and real-time hydrogen use system data;

[0058] It can be understood that: the hydrogen production system uses alkaline electrolysis hydrogen production equipment to produce hydrogen; the hydrogen use system can be a chemical plant that uses hydrogen as energy.

[0059] S2: Using real-time wind power generation data, real-time photovoltaic power generation data, predicted wind power generation data, predicted photovoltaic power generation data, real-time energy storage system data, real-time hydrogen production system data, real-time hydrogen consumption system data and three pre-trained source-grid-load-storage coordinated control models, three real-time coordinated control schemes are obtained, and the final real-time coordinated control scheme is obtained based on the credibility screening of the three real-time coordinated control schemes; among them, the three pre-trained source-grid-load-storage coordinated control models include a pre-trained support vector machine model, a pre-trained random forest model and a pre-trained neural network.

[0060] In one embodiment, S2 specifically includes the following steps:

[0061] S21: Calculate the difference between the predicted wind power generation data and the real-time wind power generation data to obtain wind power generation difference data;

[0062] That is: wind power generation difference data = predicted wind power generation data - real-time wind power generation data;

[0063] Calculate the difference between the predicted photovoltaic power generation data and the real-time photovoltaic power generation data to obtain photovoltaic power generation difference data;

[0064] That is: photovoltaic power generation difference data = predicted photovoltaic power generation data - real-time photovoltaic power generation data;

[0065] S22: Inputting the wind power generation difference data, the photovoltaic power generation difference data, the real-time energy storage system data, the real-time hydrogen production system data, and the real-time hydrogen use system data into a pre-trained support vector machine model to obtain a first real-time coordinated control scheme;

[0066] Inputting wind power generation difference data, photovoltaic power generation difference data, real-time energy storage system data, real-time hydrogen production system data, and real-time hydrogen consumption system data into a pre-trained random forest model to obtain a second real-time coordinated control scheme;

[0067] Inputting wind power generation difference data, photovoltaic power generation difference data, real-time energy storage system data, real-time hydrogen production system data, and real-time hydrogen use system data into a pre-trained neural network to obtain a third real-time coordinated control scheme;

[0068] S23: If the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are all higher than the credibility threshold, the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are randomly voted and the real-time coordinated control scheme with the highest number of votes is selected as the final real-time coordinated control scheme;

[0069] If two of the credibility levels of the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are higher than the credibility threshold, the real-time coordinated control scheme with the highest credibility is used as the final real-time coordinated control scheme;

[0070] If the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme and the third real-time coordinated control scheme are all lower than the credibility threshold or only one credibility is higher than the credibility threshold, then the confidence of the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme and the third real-time coordinated control scheme is calculated, and the sum of the squares of the credibility and confidence of the three real-time coordinated control schemes is calculated, and the real-time coordinated control scheme with the largest sum of squares is taken as the final real-time coordinated control scheme.

[0071] In one embodiment, the real-time wind power generation data includes real-time wind power generation efficiency, real-time wind power generation power, and real-time wind power generation power change rate;

[0072] The predicted wind power generation data includes the predicted wind power generation efficiency, the predicted wind power generation power and the predicted wind power generation power change rate;

[0073] It can be understood that: the wind power generation difference data includes wind power generation efficiency difference data, wind power generation power difference data and wind power generation power change rate difference data;

[0074] Wind power generation efficiency difference data = predicted wind power generation efficiency - real-time wind power generation efficiency;

[0075] Wind power generation difference data = predicted wind power generation - real-time wind power generation;

[0076] Wind power generation power change rate difference data = predicted wind power generation power change rate - real-time wind power generation power change rate;

[0077] Real-time photovoltaic power generation data includes real-time photovoltaic power generation efficiency, real-time photovoltaic power generation and real-time photovoltaic power generation rate of change;

[0078] The predicted photovoltaic power generation data includes the predicted photovoltaic power generation efficiency, the predicted photovoltaic power generation power and the predicted photovoltaic power generation power change rate;

[0079] It can be understood that: the photovoltaic power generation difference data includes photovoltaic power generation efficiency difference data, photovoltaic power generation power difference data and photovoltaic power generation power change rate difference data;

[0080] Photovoltaic power generation efficiency difference data = predicted photovoltaic power generation efficiency - real-time photovoltaic power generation efficiency;

[0081] Photovoltaic power generation difference data = predicted photovoltaic power generation - real-time photovoltaic power generation;

[0082] Photovoltaic power generation power change rate difference data = predicted photovoltaic power generation power change rate - real-time photovoltaic power generation power change rate;

[0083] Real-time energy storage system data includes real-time charging active power, real-time discharging active power, charging available power, discharging available power, energy storage SOC and energy storage SOH;

[0084] Real-time hydrogen production system data includes electrolyzer real-time power, electrolyzer real-time current, electrolyzer temperature, electrolyzer pressure, hydrogen production main pipe pressure, hydrogen production flow, hydrogen storage tank pressure and hydrogen transmission flow;

[0085] Real-time hydrogen usage system data includes real-time hydrogen usage.

[0086] In one embodiment, the final real-time coordinated control plan includes an energy storage system charging schedule, an energy storage system discharging schedule, a planned grid-connected power, a planned electricity purchase power, and a planned hydrogen production volume.

[0087] It can be understood that the planned grid-connected power is the power planned to be input to the grid.

[0088] In one embodiment, the confidence threshold is 0.7.

[0089] On the other hand, an embodiment of the present invention discloses a source-grid-load-storage coordinated control system, including a data acquisition unit and a real-time coordinated control solution output module;

[0090] The data acquisition unit is used to acquire real-time wind power generation data, real-time photovoltaic power generation data, predicted wind power generation data, predicted photovoltaic power generation data, real-time energy storage system data, real-time hydrogen production system data and real-time hydrogen use system data;

[0091] The real-time coordinated control scheme output module is used to obtain three real-time coordinated control schemes using real-time wind power generation data, real-time photovoltaic power generation data, predicted wind power generation data, predicted photovoltaic power generation data, real-time energy storage system data, real-time hydrogen production system data, real-time hydrogen consumption system data and three pre-trained source-grid-load-storage coordinated control models, and obtain the final real-time coordinated control scheme based on the credibility screening of the three real-time coordinated control schemes; among them, the three pre-trained source-grid-load-storage coordinated control models include a pre-trained support vector machine model, a pre-trained random forest model and a pre-trained neural network.

[0092] In one embodiment, the real-time coordinated control scheme output module includes a wind power generation difference data calculation module, a photovoltaic power generation difference data calculation module, a first real-time coordinated control scheme acquisition module, a second real-time coordinated control scheme acquisition module, a third real-time coordinated control scheme acquisition module, and a final real-time coordinated control scheme acquisition module;

[0093] The wind power generation difference data calculation module is used to calculate the difference between the predicted wind power generation data and the real-time wind power generation data to obtain the wind power generation difference data;

[0094] That is: wind power generation difference data = predicted wind power generation data - real-time wind power generation data;

[0095] The photovoltaic power generation difference data calculation module is used to calculate the difference between the predicted photovoltaic power generation data and the real-time photovoltaic power generation data to obtain the photovoltaic power generation difference data;

[0096] That is: photovoltaic power generation difference data = predicted photovoltaic power generation data - real-time photovoltaic power generation data;

[0097] The first real-time coordinated control scheme acquisition module is used to input wind power generation difference data, photovoltaic power generation difference data, real-time energy storage system data, real-time hydrogen production system data and real-time hydrogen use system data into a pre-trained support vector machine model to obtain a first real-time coordinated control scheme;

[0098] The second real-time coordinated control scheme acquisition module is used to input wind power generation difference data, photovoltaic power generation difference data, real-time energy storage system data, real-time hydrogen production system data, and real-time hydrogen consumption system data into a pre-trained random forest model to obtain a second real-time coordinated control scheme;

[0099] The third real-time coordinated control scheme acquisition module is used to input wind power generation difference data, photovoltaic power generation difference data, real-time energy storage system data, real-time hydrogen production system data, and real-time hydrogen use system data into the pre-trained neural network to obtain a third real-time coordinated control scheme;

[0100] The final real-time coordinated control scheme acquisition module is used to obtain the final real-time coordinated control scheme. Specifically: if the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are all higher than the credibility threshold, the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are randomly voted and the real-time coordinated control scheme with the highest number of votes is used as the final real-time coordinated control scheme;

[0101] If two of the credibility levels of the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are higher than the credibility threshold, the real-time coordinated control scheme with the highest credibility is used as the final real-time coordinated control scheme;

[0102] If the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme and the third real-time coordinated control scheme are all lower than the credibility threshold or only one credibility is higher than the credibility threshold, then the confidence of the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme and the third real-time coordinated control scheme is calculated, and the sum of the squares of the credibility and confidence of the three real-time coordinated control schemes is calculated, and the real-time coordinated control scheme with the largest sum of squares is taken as the final real-time coordinated control scheme.

[0103] In one embodiment, the real-time wind power generation data includes real-time wind power generation efficiency, real-time wind power generation power, and real-time wind power generation power change rate;

[0104] The predicted wind power generation data includes the predicted wind power generation efficiency, the predicted wind power generation power and the predicted wind power generation power change rate;

[0105] It can be understood that: the wind power generation difference data includes wind power generation efficiency difference data, wind power generation power difference data and wind power generation power change rate difference data;

[0106] Wind power generation efficiency difference data = predicted wind power generation efficiency - real-time wind power generation efficiency;

[0107] Wind power generation difference data = predicted wind power generation - real-time wind power generation;

[0108] Wind power generation power change rate difference data = predicted wind power generation power change rate - real-time wind power generation power change rate;

[0109] Real-time photovoltaic power generation data includes real-time photovoltaic power generation efficiency, real-time photovoltaic power generation and real-time photovoltaic power generation rate of change;

[0110] The predicted photovoltaic power generation data includes the predicted photovoltaic power generation efficiency, the predicted photovoltaic power generation power and the predicted photovoltaic power generation power change rate;

[0111] It can be understood that: the photovoltaic power generation difference data includes photovoltaic power generation efficiency difference data, photovoltaic power generation power difference data and photovoltaic power generation power change rate difference data;

[0112] Photovoltaic power generation efficiency difference data = predicted photovoltaic power generation efficiency - real-time photovoltaic power generation efficiency;

[0113] Photovoltaic power generation difference data = predicted photovoltaic power generation - real-time photovoltaic power generation;

[0114] Photovoltaic power generation power change rate difference data = predicted photovoltaic power generation power change rate - real-time photovoltaic power generation power change rate;

[0115] Real-time energy storage system data includes real-time charging active power, real-time discharging active power, charging available power, discharging available power, energy storage SOC and energy storage SOH;

[0116] Real-time hydrogen production system data includes electrolyzer real-time power, electrolyzer real-time current, electrolyzer temperature, electrolyzer pressure, hydrogen production main pipe pressure, hydrogen production flow, hydrogen storage tank pressure and hydrogen transmission flow;

[0117] Real-time hydrogen usage system data includes real-time hydrogen usage.

[0118] In one embodiment, the final real-time coordinated control plan includes an energy storage system charging schedule, an energy storage system discharging schedule, a planned grid-connected power, a planned electricity purchase power, and a planned hydrogen production volume.

[0119] It can be understood that the planned grid-connected power is the power planned to be input to the grid.

[0120] In one embodiment, the confidence threshold is 0.7.

[0121] On the other hand, the present invention also provides an electronic device, such as Figure 2 As shown, the electronic device may include: a processor 201, a communication interface 202, a memory 203, and a communication bus 204, wherein the processor 201, the communication interface 202, and the memory 203 communicate with each other via the communication bus 204. The processor 201 may call logic instructions in the memory 203 to execute a source-grid-load-storage coordinated control method.

[0122] In addition, the logic instructions in the above-mentioned memory 203 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0123] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute a source-grid-load-storage coordinated control method provided by the above methods.

[0124] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute a source-grid-load-storage coordinated control method provided by the above methods.

[0125] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0126] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0127] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0128] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A source-grid-load-storage coordinated control method, characterized in that: The following steps are involved: S1: Acquire real-time wind power generation data, real-time photovoltaic power generation data, predicted wind power generation data, predicted photovoltaic power generation data, real-time energy storage system data, real-time hydrogen production system data, and real-time hydrogen use system data; S2: Utilize the real-time wind power generation data, the real-time photovoltaic power generation data, the predicted wind power generation data, the predicted photovoltaic power generation data, the real-time energy storage system data, the real-time hydrogen production system data, the real-time hydrogen consumption system data and three pre-trained source-grid-load-storage coordinated control models to obtain three real-time coordinated control schemes, and obtain the final real-time coordinated control scheme based on the credibility screening of the three real-time coordinated control schemes; wherein, the three pre-trained source-grid-load-storage coordinated control models include a pre-trained support vector machine model, a pre-trained random forest model and a pre-trained neural network.

2. A source-grid-load-storage coordinated control method according to claim 1, characterized in that: S2 specifically includes the following steps: S21: Calculating the difference between the predicted wind power generation data and the real-time wind power generation data to obtain wind power generation difference data; Calculating the difference between the predicted photovoltaic power generation data and the real-time photovoltaic power generation data to obtain photovoltaic power generation difference data; S22: inputting the wind power generation difference data, the photovoltaic power generation difference data, the real-time energy storage system data, the real-time hydrogen production system data, and the real-time hydrogen use system data into the pre-trained support vector machine model to obtain a first real-time coordinated control scheme; Inputting the wind power generation difference data, the photovoltaic power generation difference data, the real-time energy storage system data, the real-time hydrogen production system data, and the real-time hydrogen consumption system data into the pre-trained random forest model to obtain a second real-time coordinated control scheme; Inputting the wind power generation difference data, the photovoltaic power generation difference data, the real-time energy storage system data, the real-time hydrogen production system data, and the real-time hydrogen use system data into the pre-trained neural network to obtain a third real-time coordinated control scheme; S23: If the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are all higher than the credibility threshold, performing random voting on the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme and selecting the real-time coordinated control scheme with the highest number of votes as the final real-time coordinated control scheme; If two of the credibility levels of the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are higher than the credibility threshold, the real-time coordinated control scheme with the highest credibility is used as the final real-time coordinated control scheme; If the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme and the third real-time coordinated control scheme are all lower than the credibility threshold or only one credibility is higher than the credibility threshold, then the confidence of the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme and the third real-time coordinated control scheme is calculated, and the sum of the squares of the credibility and confidence of the three real-time coordinated control schemes is calculated, and the real-time coordinated control scheme with the largest sum of squares is used as the final real-time coordinated control scheme.

3. The source-grid-load-storage coordinated control method according to claim 1, characterized in that: The real-time wind power generation data includes real-time wind power generation efficiency, real-time wind power generation power and real-time wind power generation power change rate; The predicted wind power generation data includes predicted wind power generation efficiency, predicted wind power generation power and predicted wind power generation power change rate; The real-time photovoltaic power generation data includes real-time photovoltaic power generation efficiency, real-time photovoltaic power generation power and real-time photovoltaic power generation power change rate; The predicted photovoltaic power generation data includes predicted photovoltaic power generation efficiency, predicted photovoltaic power generation power and predicted photovoltaic power generation power change rate; The real-time energy storage system data includes real-time charging active power, real-time discharging active power, charging available power, discharging available power, energy storage SOC and energy storage SOH; The real-time hydrogen production system data includes electrolyzer real-time power, electrolyzer real-time current, electrolyzer temperature, electrolyzer pressure, hydrogen production main pipe pressure, hydrogen production flow, hydrogen storage tank pressure and hydrogen transmission flow; The real-time hydrogen usage system data includes real-time hydrogen usage.

4. The source-grid-load-storage coordinated control method according to claim 1, characterized in that: The final real-time coordinated control plan includes an energy storage system charging schedule, an energy storage system discharging schedule, a planned grid-connected power, a planned electricity purchase power, and a planned hydrogen production volume.

5. The source-grid-load-storage coordinated control method according to claim 2, characterized in that: The credibility threshold is 0.

7.

6. A source-grid-load-storage coordinated control system, characterized in that: It includes a data acquisition unit and a real-time coordinated control scheme output module; The data acquisition unit is used to acquire real-time wind power generation data, real-time photovoltaic power generation data, predicted wind power generation data, predicted photovoltaic power generation data, real-time energy storage system data, real-time hydrogen production system data and real-time hydrogen use system data; The real-time coordinated control scheme output module is used to utilize the real-time wind power generation data, the real-time photovoltaic power generation data, the predicted wind power generation data, the predicted photovoltaic power generation data, the real-time energy storage system data, the real-time hydrogen production system data, the real-time hydrogen consumption system data and three pre-trained source-grid-load-storage coordinated control models to obtain three real-time coordinated control schemes, and obtain the final real-time coordinated control scheme based on the credibility screening of the three real-time coordinated control schemes; wherein, the three pre-trained source-grid-load-storage coordinated control models include a pre-trained support vector machine model, a pre-trained random forest model and a pre-trained neural network.

7. A source-grid-load-storage coordinated control system according to claim 6, characterized in that: The real-time coordinated control scheme output module includes a wind power generation difference data calculation module, a photovoltaic power generation difference data calculation module, a first real-time coordinated control scheme acquisition module, a second real-time coordinated control scheme acquisition module, a third real-time coordinated control scheme acquisition module and a final real-time coordinated control scheme acquisition module; The wind power generation difference data calculation module is used to calculate the difference between the predicted wind power generation data and the real-time wind power generation data to obtain wind power generation difference data; The photovoltaic power generation difference data calculation module is used to calculate the difference between the predicted photovoltaic power generation data and the real-time photovoltaic power generation data to obtain photovoltaic power generation difference data; The first real-time coordinated control scheme acquisition module is used to input the wind power generation difference data, the photovoltaic power generation difference data, the real-time energy storage system data, the real-time hydrogen production system data and the real-time hydrogen use system data into the pre-trained support vector machine model to obtain a first real-time coordinated control scheme; The second real-time coordinated control scheme acquisition module is used to input the wind power generation difference data, the photovoltaic power generation difference data, the real-time energy storage system data, the real-time hydrogen production system data, and the real-time hydrogen consumption system data into the pre-trained random forest model to obtain a second real-time coordinated control scheme; The third real-time coordinated control scheme acquisition module is used to input the wind power generation difference data, the photovoltaic power generation difference data, the real-time energy storage system data, the real-time hydrogen production system data, and the real-time hydrogen use system data into the pre-trained neural network to obtain a third real-time coordinated control scheme; The final real-time coordinated control scheme acquisition module is used to obtain the final real-time coordinated control scheme. Specifically, if the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are all higher than the credibility threshold, the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are randomly voted and the real-time coordinated control scheme with the highest number of votes is used as the final real-time coordinated control scheme. If two of the credibility levels of the first real-time coordinated control scheme, the second real-time coordinated control scheme, and the third real-time coordinated control scheme are higher than the credibility threshold, the real-time coordinated control scheme with the highest credibility is used as the final real-time coordinated control scheme; If the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme and the third real-time coordinated control scheme are all lower than the credibility threshold or only one credibility is higher than the credibility threshold, then the confidence of the credibility of the first real-time coordinated control scheme, the second real-time coordinated control scheme and the third real-time coordinated control scheme is calculated, and the sum of the squares of the credibility and confidence of the three real-time coordinated control schemes is calculated, and the real-time coordinated control scheme with the largest sum of squares is used as the final real-time coordinated control scheme.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, a source-grid-load-storage coordinated control method according to any one of claims 1 to 5 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, a source-grid-load-storage coordinated control method according to any one of claims 1 to 5 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, a source-grid-load-storage coordinated control method according to any one of claims 1 to 5 is implemented.

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