Optical storage micro-grid power generation system and control method thereof

Abstract

The invention discloses an optical storage micro-grid power generation system and a control method thereof, and belongs to the technical field of intelligent power grids, and the method comprises the steps: S1, obtaining the real-time operation data of an optical storage micro-grid, and carrying out the preprocessing of the real-time operation data, and obtaining an operation data set; s2, determining photovoltaic characteristics according to the operation data set and a characteristic extraction rule, and making a photovoltaic output strategy based on the photovoltaic characteristics; synchronously, the working state of the optical storage micro-grid power generation system is judged based on the operation data set, and a security isolation strategy is made based on the working state of the optical storage micro-grid power generation system; s3, arranging a photovoltaic output strategy and a security isolation strategy to obtain a control strategy of a power distribution network corresponding to the optical storage micro-grid power generation system; s4, the corresponding power distribution network responds to the control strategy to execute a control action; according to the method, the problem of poor stability of the corresponding power distribution network caused by the fact that the volatility of the photovoltaic power generation system and the uneven space-time distribution are not comprehensively considered in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of smart grids, and in particular to a photovoltaic storage microgrid power generation system and a control method thereof. Background Art

[0002] With the development of photovoltaic power generation technology, the proportion of distributed photovoltaic power generation systems in distribution networks is increasing, and the disordered power generation output of distributed photovoltaic power generation systems has a significant impact on the stable operation of distribution networks; first, the power generation output of distributed photovoltaic power generation systems has the characteristics of uneven temporal and spatial distribution, which makes the load forecasting of distribution networks more difficult and makes the dispatching and control of distribution networks difficult; second, the power generation output of distributed photovoltaic power generation systems is volatile, which makes the power flow characteristics of distribution networks more complex, increases the reverse pressure of distribution networks, and causes reverse overload problems in corresponding transmission lines and equipment, thereby affecting the power supply quality and reliability of distribution networks.

[0003] Chinese patent, publication number: CN118971080A, publication date: November 15, 2024, discloses a photovoltaic microgrid energy management and optimization scheduling system, including: an intelligent prediction and analysis module, which is used to integrate real-time meteorological data, historical photovoltaic output records and user load data, and predict future photovoltaic power generation and load curves through deep learning prediction algorithms; a dynamic scheduling optimization module, which is used to receive the output data of the intelligent prediction and analysis module, adjust the energy distribution between the photovoltaic system, energy storage device and controllable load in real time, and send scheduling commands to the distributed energy resource control module and the energy storage management and optimization module; a distributed energy resource control module, which is used to dynamically adjust the output of each distributed energy resource according to the scheduling instructions sent by the dynamic scheduling optimization module, and report the execution results to the real-time monitoring and data feedback module; the distributed energy resource control The module is based on edge computing and microservice architecture, and realizes intelligent local control of distributed energy resources through a protocol adapter; the energy storage management and optimization module is used to dynamically adjust the charging and discharging status of the energy storage equipment based on the scheduling instructions sent by the dynamic scheduling optimization module, and feedback the execution status to the real-time monitoring and data feedback module; the energy storage management and optimization module optimizes the energy storage charging and discharging strategy through a deep health status assessment algorithm; the real-time monitoring and data feedback module is used to monitor the microgrid system status in real time, collect the execution results of each module, and feedback to the intelligent prediction and analysis module and the dynamic scheduling optimization module; the real-time monitoring and data feedback module realizes real-time monitoring and secure data transmission of the system status through the Internet of Things sensor network and blockchain; however, the invention does not comprehensively consider the volatility and uneven temporal and spatial distribution characteristics of the photovoltaic power generation system, resulting in poor stability of the corresponding distribution network. Summary of the invention

[0004] The purpose of the present invention is to address the problem that the prior art does not comprehensively consider the volatility and uneven temporal and spatial distribution characteristics of photovoltaic power generation systems, resulting in poor stability of the corresponding distribution network; a photovoltaic storage microgrid power generation system and a control method thereof are proposed, a photovoltaic output strategy is formulated by photovoltaic characteristics calculated based on real-time operation data of the photovoltaic storage microgrid, and a safety isolation strategy is formulated by judging the working state of the photovoltaic storage microgrid power generation system based on the real-time operation data of the photovoltaic storage microgrid, and then the photovoltaic output strategy and the safety isolation strategy are sorted out to obtain the control strategy of the distribution network corresponding to the photovoltaic storage microgrid power generation system, and the distribution network executes control actions in response to the control strategy to adjust the power, thereby improving the power supply quality of the distribution network and significantly improving the stability of the corresponding distribution network.

[0005] In a first aspect, a technical solution provided in an embodiment of the present invention is a method for controlling a photovoltaic microgrid power generation system, comprising the following steps: S1. Acquire real-time operation data of the photovoltaic storage microgrid, and pre-process the real-time operation data to obtain an operation data set; S2. determining photovoltaic characteristics according to the operating data set and feature extraction rules, and formulating a photovoltaic output strategy based on the photovoltaic characteristics; Synchronously, judging the working state of the photovoltaic-storage microgrid power generation system based on the operating data set, and formulating a safety isolation strategy based on the working state of the photovoltaic-storage microgrid power generation system; S3, sorting out the photovoltaic output strategy and the safety isolation strategy to obtain the control strategy of the distribution network corresponding to the photovoltaic storage microgrid power generation system; S4, the corresponding distribution network executes the control action in response to the control strategy.

[0006] In this scheme, the acquired real-time operation data of the photovoltaic storage microgrid is preprocessed to eliminate abnormal values ​​and missing values ​​in the data, and then the photovoltaic characteristics corresponding to the uneven temporal and spatial distribution and volatility of the photovoltaic storage microgrid power generation system are extracted from the real-time operation data after the preprocessing by using the feature extraction rules, and a photovoltaic output strategy suitable for the photovoltaic characteristics is formulated. At the same time, a safety isolation strategy is formulated by judging the working state of the photovoltaic storage microgrid power generation system based on the real-time operation data after the preprocessing to prevent abnormal electrical equipment in the photovoltaic storage microgrid power generation system from affecting the output of the photovoltaic storage microgrid power generation system. Subsequently, the photovoltaic output strategy and the safety isolation strategy are sorted out to obtain a control strategy for the distribution network suitable for the uneven temporal and spatial distribution, volatility and current working state of the photovoltaic storage microgrid power generation system. Finally, the distribution network executes a control action to adjust the power in response to the control strategy, thereby improving the power supply quality of the distribution network and significantly improving the stability of the corresponding distribution network.

[0007] Preferably, in S1, the specific process of preprocessing the real-time operation data to obtain the operation data set is: S111, inputting the real-time operation data into a filter to filter and obtain noise-free operation data, and performing statistical analysis on the noise-free operation data to determine missing values ​​and abnormal values; S112: Remove the abnormal values ​​and mark them as active missing values, and use the spline interpolation method to fill the missing values ​​and active missing values ​​to obtain a running data set.

[0008] In this solution, a filter is used to filter out the noise in the real-time operation data, to eliminate the abnormal values ​​in the real-time operation data, and to fill the data at the missing positions using the spline interpolation method, so that the real-time operation data is consistent with the actual working conditions of the corresponding photovoltaic storage microgrid power generation system, and the data is more complete and smooth.

[0009] Preferably, in S2, the specific process of determining the photovoltaic characteristics according to the operating data set and the feature extraction rule is: S211, calculating the power variation according to the photovoltaic power generation power and the load power in the operation data set, and determining the time scale of the power variation according to the time scale variation of the photovoltaic power generation power and the time scale variation of the load power; S212: Perform definite integral conversion on the power variation based on the time scale of the power variation to obtain photovoltaic characteristics.

[0010] In this scheme, the power change is used to quantify the uneven temporal and spatial distribution and fluctuating characteristics of the corresponding photovoltaic storage microgrid power generation system. However, since the actual data may be very large due to different specific environments, the power change may be insufficient to reflect subtle changes. Therefore, the power change is converted into a definite integral to extract the subtle change characteristics of the corresponding data.

[0011] Preferably, in S2, the specific process of formulating the photovoltaic output strategy based on the photovoltaic characteristics is: S221, determining a photovoltaic action threshold based on a charging rate and a discharging rate of an energy storage module in a photovoltaic microgrid power generation system; S222. Analyze the power flow of the photovoltaic storage microgrid power generation system according to the photovoltaic characteristics and photovoltaic action thresholds to obtain a photovoltaic output strategy.

[0012] In this scheme, a reasonable photovoltaic action threshold is determined based on the charge and discharge rate of the energy storage module, and the power flow regulation process of the photovoltaic storage microgrid power generation system can be divided into different stages. At the same time, according to the photovoltaic action threshold and photovoltaic characteristics, the photovoltaic output action corresponding to the uneven temporal and spatial distribution and volatility can be obtained, making the output of the entire photovoltaic storage microgrid power generation system more stable.

[0013] Preferably, in S221, the charging rate and the discharging rate of the energy storage module are determined by a rate adjustment formula, and the rate adjustment formula is specifically: Where u[k] is the energy conversion rate of the energy storage module in the kth cycle, y[k] is the state of the photovoltaic microgrid power generation system, and y ref [k] is the reference trajectory of energy storage module charging and discharging, ρ is the penalty factor of control action, N p is the predicted number of steps of the photovoltaic output action, J[k] is the energy loss in the kth cycle, and t is the starting time of charging and discharging of the energy storage module.

[0014] Preferably, in S2, the specific process of determining the working state of the photovoltaic storage microgrid power generation system based on the operating data set is: S231, extracting topological features based on the topological structure of the photovoltaic storage microgrid power generation system, and dividing the operating data set into a multi-object data set and a single-object data set based on the topological features; S232, performing a horizontal comparison analysis based on the corresponding topological features of the multi-object data set and the multi-object data set, and performing a vertical comparison analysis based on the single-object data set, the single-object threshold and the vertical time threshold; S233. Arrange the results of the horizontal comparison analysis and the vertical comparison analysis to obtain the working status of the photovoltaic storage microgrid power generation system.

[0015] In this solution, based on the fact that the photovoltaic microgrid power generation system has multiple identical electrical devices and multiple different electrical devices, the operating data set is divided into a multi-object data set and a single-object data set. In the multi-object data set, a horizontal comparison and analysis is performed based on the operating data of the same equipment to find abnormal electrical equipment that does not fit in. In the single-object data set, a vertical comparison and analysis is performed based on the operating data of different devices to find abnormal electrical equipment that does not meet the requirements of the photovoltaic microgrid power generation system or has strange operating changes. The working status of the photovoltaic microgrid power generation system from local to overall is obtained based on the analysis of the abnormal electrical equipment.

[0016] Preferably, in S2, the specific process of formulating a safety isolation strategy based on the working state of the photovoltaic storage microgrid power generation system is: S241, determining abnormal nodes and normal nodes based on the working state of the photovoltaic storage microgrid power generation system and the topological structure of the photovoltaic storage microgrid power generation system; S242, planning an energy flow path in the topology of the photovoltaic storage microgrid power generation system according to the abnormal nodes and normal nodes; S243, formulating a fault isolation action based on the energy flow path to obtain a safety isolation strategy.

[0017] In this scheme, abnormal nodes and normal nodes are determined according to the working status of the photovoltaic microgrid power generation system and the topological structure of the photovoltaic microgrid power generation system. Abnormal electrical equipment in the photovoltaic microgrid power generation system can be excluded from the power supply, and the shortest energy flow path of the current state of the photovoltaic microgrid power generation system can be obtained. At the same time, an electrical isolation interval is established between normal electrical equipment and abnormal electrical equipment to protect normal electrical equipment.

[0018] Preferably, in S3, the specific process of sorting out the photovoltaic output strategy and the safety isolation strategy to obtain the control strategy of the photovoltaic storage microgrid power generation system corresponding to the distribution network is: The topology of the photovoltaic microgrid power generation system is adjusted based on the safety isolation strategy, and the power regulation action of the distribution network is formulated according to the adjusted topology of the photovoltaic microgrid power generation system, the photovoltaic output strategy and the real-time operation data of the corresponding distribution network to obtain the control strategy of the corresponding distribution network.

[0019] On the other hand, a technical solution also provided in an embodiment of the present invention is a photovoltaic storage microgrid power generation system, comprising: a photovoltaic power generation module, an energy storage module, a safety monitoring module, and an intelligent control module; The output end of the photovoltaic power generation module is electrically connected to the first input end of the intelligent control module, the data collection end of the photovoltaic power generation module is electrically connected to the data collection end of the safety monitoring module, the controlled end of the photovoltaic power generation module is electrically connected to the first control end of the intelligent control module, the output end of the energy storage module is electrically connected to the second input end of the intelligent control module, the data collection end of the energy storage module is electrically connected to the data collection end of the safety monitoring module, the controlled end of the energy storage module is electrically connected to the second control end of the intelligent control module, and the data collection end of the safety monitoring module is electrically connected to the data collection end of the intelligent control module.

[0020] Preferably, the energy storage module comprises: a lithium-ion battery pack and a supercapacitor; The lithium-ion battery pack is connected in parallel with the supercapacitor, and a first common point, a second common point and a third common point are provided in the parallel circuit of the lithium-ion battery pack and the supercapacitor, wherein the first common point serves as an output end of the energy storage module, the second common point serves as a data collection end of the energy storage module, and the third common point serves as a controlled end of the energy storage module.

[0021] The present invention has at least the following substantial effects: The present application preprocesses the acquired real-time operation data of the photovoltaic storage microgrid to eliminate abnormal values ​​and missing values ​​in the data, and then uses feature extraction rules to extract photovoltaic characteristics corresponding to the uneven temporal and spatial distribution and volatility of the photovoltaic storage microgrid power generation system from the real-time operation data after the preprocessing, and formulates a photovoltaic output strategy suitable for the photovoltaic characteristics. At the same time, a safety isolation strategy is formulated by judging the working state of the photovoltaic storage microgrid power generation system based on the real-time operation data after the preprocessing to prevent abnormal electrical equipment in the photovoltaic storage microgrid power generation system from affecting the output of the photovoltaic storage microgrid power generation system. Subsequently, the photovoltaic output strategy and the safety isolation strategy are sorted out to obtain a control strategy for the distribution network suitable for the uneven temporal and spatial distribution, volatility and current working state of the photovoltaic storage microgrid power generation system. Finally, the distribution network executes a control action in response to the control strategy to adjust the power, improve the power supply quality of the distribution network, and significantly improve the stability of the corresponding distribution network. At the same time, the present application can also use the formulation process of the safety isolation strategy to detect abnormal electrical equipment in advance and isolate it to protect the normal electrical equipment in the photovoltaic storage microgrid power generation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Other features, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for the purpose of illustrating preferred embodiments and are not to be considered as limiting the present invention. Also, the same reference symbols are used throughout the drawings to represent the same parts.

[0023] Figure 1 It is a flow chart of a control method of a photovoltaic storage microgrid power generation system; Figure 2 This is a structural schematic diagram of a photovoltaic storage microgrid power generation system. DETAILED DESCRIPTION

[0024] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific implementation method described herein is only an optimal embodiment of the present invention, which is only used to explain the present invention and does not limit the scope of protection of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0025] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations (or steps) therein can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the drawings; the process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0026] Embodiment 1: like Figure 1 As shown, this embodiment provides a control method for a photovoltaic storage microgrid power generation system, comprising the following steps: S1. Acquire real-time operation data of the photovoltaic and energy storage microgrid, and pre-process the real-time operation data to obtain an operation data set.

[0027] S111, inputting the real-time operation data into a filter to filter and obtain noise-free operation data, and performing statistical analysis on the noise-free operation data to determine missing values ​​and abnormal values; S112: Remove the abnormal values ​​and mark them as active missing values, and use the spline interpolation method to fill the missing values ​​and active missing values ​​to obtain a running data set.

[0028] In this embodiment, a passive filter is specifically used to filter the noise in the real-time operation data, and a corresponding scatter plot is drawn to identify outliers in the real-time operation data. After the outliers are eliminated, all missing values ​​in the real-time operation data are searched in the scatter plot, and all missing values ​​are filled using the spline interpolation method.

[0029] S2. determining photovoltaic characteristics according to the operating data set and feature extraction rules, and formulating a photovoltaic output strategy based on the photovoltaic characteristics; Synchronously, the working state of the photovoltaic and energy storage microgrid power generation system is determined based on the operating data set, and a safety isolation strategy is formulated based on the working state of the photovoltaic and energy storage microgrid power generation system.

[0030] In one embodiment, the specific process of determining photovoltaic features according to the operating data set and feature extraction rules is as follows: S211, calculating the power variation according to the photovoltaic power generation power and the load power in the operation data set, and determining the time scale of the power variation according to the time scale variation of the photovoltaic power generation power and the time scale variation of the load power; S212: Performing derivative conversion on the power variation based on the time scale of the power variation to obtain photovoltaic characteristics.

[0031] In this embodiment, the calculation formula of the power change is specifically: Δp=p 光 -p 荷 ; Where Δp is the power change, p 光 is the power generation power of the photovoltaic power generation module in the photovoltaic storage microgrid power generation system, p 荷 is the power of the photovoltaic and storage microgrid power generation system corresponding to the external load; By subtracting the power generated by the photovoltaic power generation module and the external load power, the difference between the power generated and the power consumed at the same time can be obtained, that is, the power change. The power change is differentiated corresponding to its time scale to obtain the rate of change of power within the corresponding time scale. The volatility and spatiotemporal distribution uniformity of the photovoltaic microgrid power generation system within the time scale are digitized and displayed, that is, the photovoltaic characteristics.

[0032] In one embodiment, the specific process of formulating a photovoltaic output strategy based on photovoltaic characteristics is as follows: S221, determining a photovoltaic action threshold based on a charging rate and a discharging rate of an energy storage module in a photovoltaic microgrid power generation system; The energy storage module charging rate and the energy storage module discharging rate are determined by a rate adjustment formula, which is specifically: Where u[k] is the energy conversion rate of the energy storage module in the kth cycle, y[k] is the state of the photovoltaic microgrid power generation system, and y ref [k] is the reference trajectory of energy storage module charging and discharging, ρ is the penalty factor of control action, N p is the predicted number of steps of the photovoltaic output action, J[k] is the energy loss in the kth cycle, and t is the starting time of charging and discharging of the energy storage module; S222. Analyze the power flow of the photovoltaic storage microgrid power generation system according to the photovoltaic characteristics and photovoltaic action thresholds to obtain a photovoltaic output strategy.

[0033] In this embodiment, when the photovoltaic characteristic is greater than zero, it proves that the power of the photovoltaic power generation module in the photovoltaic storage microgrid power generation system can not only support the normal operation of the external load, but also has surplus electric energy. At this time, the lithium-ion battery pack in the energy storage module is adjusted to absorb the surplus electric energy according to the charging rate of the energy storage module. When the photovoltaic characteristic is equal to zero, it proves that the power of the photovoltaic power generation module in the photovoltaic storage microgrid power generation system just supports the normal operation of the external load, and the photovoltaic power generation module only supplies power to the external load. When the photovoltaic characteristic is less than zero, it proves that the power of the photovoltaic power generation module in the photovoltaic storage microgrid power generation system is insufficient to support the normal operation of the external load, and the output power of the photovoltaic storage microgrid power generation system needs to be increased. At this time, the photovoltaic characteristic and the photovoltaic dynamic as a threshold, if the photovoltaic characteristic is less than the photovoltaic action threshold, the lithium-ion battery pack in the energy storage module cooperates with the photovoltaic power generation module to power the external load; if the photovoltaic characteristic is greater than or equal to the photovoltaic action threshold, the lithium-ion battery pack and supercapacitor in the energy storage module cooperate with the photovoltaic power generation module to power the external load; the photovoltaic output strategy of the photovoltaic storage microgrid power generation system is adjusted according to the power supply action. In addition to eliminating the impact of the volatility and uneven temporal and spatial distribution of the photovoltaic storage microgrid power generation system, it can also ensure that the lithium-ion battery pack in the energy storage module is in the optimal working range, maximize energy utilization and optimize the charging and discharging process of the lithium-ion battery pack under the charging and discharging restriction conditions of the lithium-ion battery pack, and extend the service life of the lithium-ion battery pack.

[0034] In one embodiment, the specific process of determining the working state of the photovoltaic storage microgrid power generation system based on the operating data set is as follows: S231, extracting topological features based on the topological structure of the photovoltaic storage microgrid power generation system, and dividing the operating data set into a multi-object data set and a single-object data set based on the topological features; S232, performing a horizontal comparison analysis based on the corresponding topological features of the multi-object data set and the multi-object data set, and performing a vertical comparison analysis based on the single-object data set, the single-object threshold and the vertical time threshold; S233. Arrange the results of the horizontal comparison analysis and the vertical comparison analysis to obtain the working status of the photovoltaic storage microgrid power generation system.

[0035] In this embodiment, the horizontal comparison analysis specifically compares the operating data of the same electrical equipment in the photovoltaic microgrid power generation system, finds a small amount of data that has a different change trend from the majority of the data, and determines the electrical equipment corresponding to the small amount of data as abnormal electrical equipment, that is, faulty electrical equipment; the vertical comparison analysis is to draw a corresponding waveform graph based on the operating data of electrical equipment in the photovoltaic microgrid power generation system that does not have the same electrical equipment or has a small number of the same electrical equipment, and observe whether there are continuous points in the waveform graph that continuously exceed the single object threshold within a period of time exceeding the vertical time threshold. If so, the corresponding electrical equipment is determined to be abnormal electrical equipment, that is, faulty electrical equipment; if not, the corresponding electrical equipment is determined to be normal electrical equipment.

[0036] In one embodiment, the specific process of formulating a safety isolation strategy based on the working status of the photovoltaic storage microgrid power generation system is as follows: S241, determining abnormal nodes and normal nodes based on the working state of the photovoltaic storage microgrid power generation system and the topological structure of the photovoltaic storage microgrid power generation system; S242, planning an energy flow path in the topology of the photovoltaic storage microgrid power generation system according to the abnormal nodes and normal nodes; S243, formulating a fault isolation action based on the energy flow path to obtain a safety isolation strategy.

[0037] In this embodiment, nodes in which abnormal electrical equipment is incorporated into the photovoltaic microgrid power generation system are marked as abnormal nodes, and nodes in which no abnormal electrical equipment is incorporated into the photovoltaic microgrid power generation system are marked as normal nodes, and the abnormal nodes are excluded from the energy flow path, that is, the electric energy in the photovoltaic microgrid power generation system is only transmitted through normal nodes, and the nodes through which the electric energy does not flow can be disconnected according to the topology of the photovoltaic microgrid power generation system, that is, fault isolation action.

[0038] S3. Arrange the photovoltaic output strategy and the safety isolation strategy to obtain the control strategy of the distribution network corresponding to the photovoltaic storage microgrid power generation system.

[0039] In one embodiment, the specific process of arranging the photovoltaic output strategy and the safety isolation strategy is as follows: The topology of the photovoltaic microgrid power generation system is adjusted based on the safety isolation strategy, and the power regulation action of the distribution network is formulated according to the adjusted topology of the photovoltaic microgrid power generation system, the photovoltaic output strategy and the real-time operation data of the corresponding distribution network to obtain the control strategy of the corresponding distribution network.

[0040] S4. The corresponding distribution network executes a control action in response to the control strategy.

[0041] On the other hand, Figure 2As shown, a technical solution also provided in the embodiment of the present invention is a photovoltaic storage microgrid power generation system, comprising: a photovoltaic power generation module, an energy storage module, a safety monitoring module, and an intelligent control module; The output end of the photovoltaic power generation module is electrically connected to the first input end of the intelligent control module, the data collection end of the photovoltaic power generation module is electrically connected to the data collection end of the safety monitoring module, the controlled end of the photovoltaic power generation module is electrically connected to the first control end of the intelligent control module, the output end of the energy storage module is electrically connected to the second input end of the intelligent control module, the data collection end of the energy storage module is electrically connected to the data collection end of the safety monitoring module, the controlled end of the energy storage module is electrically connected to the second control end of the intelligent control module, and the data collection end of the safety monitoring module is electrically connected to the data collection end of the intelligent control module.

[0042] Furthermore, the energy storage module includes: a lithium-ion battery pack and a supercapacitor; The lithium-ion battery pack is connected in parallel with the supercapacitor, and a first common point, a second common point and a third common point are provided in the parallel circuit of the lithium-ion battery pack and the supercapacitor, wherein the first common point serves as an output end of the energy storage module, the second common point serves as a data collection end of the energy storage module, and the third common point serves as a controlled end of the energy storage module.

[0043] In this embodiment, the photovoltaic power generation module includes at least one integrated photovoltaic power generation unit, and the integrated photovoltaic power generation unit has sunflower tracking technology, which can automatically adjust the direction according to the real-time position of the sun to ensure that the panel collecting sunlight is always facing the sun; after identifying the abnormal electrical equipment, the safety monitoring module transmits the relevant data to the intelligent control module, and the intelligent control module first isolates the abnormal electrical equipment according to the safety isolation strategy, and starts the corresponding backup power supply in the photovoltaic microgrid power generation system after the isolation is completed to prevent the photovoltaic microgrid power generation system from fluctuating. The safety monitoring module also includes an early warning unit, which issues an alarm after detecting abnormal electrical equipment; the intelligent control module also includes a friendly user interaction interface, so that the end user can intuitively understand the system operation status, energy consumption and predictive analysis report, and integrates energy efficiency management functions to provide users with energy-saving and emission reduction suggestions, promote users to participate in energy management, and jointly improve the energy utilization efficiency of the entire system.

[0044] This embodiment has at least the following substantial effects: In this embodiment, the acquired real-time operation data of the photovoltaic storage microgrid is preprocessed to eliminate abnormal values ​​and missing values ​​in the data. Then, the photovoltaic characteristics corresponding to the uneven temporal and spatial distribution and volatility of the photovoltaic storage microgrid power generation system are extracted from the real-time operation data after the preprocessing by using the feature extraction rule, and a photovoltaic output strategy suitable for the photovoltaic characteristics is formulated. At the same time, a safety isolation strategy is formulated by judging the working state of the photovoltaic storage microgrid power generation system based on the real-time operation data after the preprocessing to prevent abnormal electrical equipment in the photovoltaic storage microgrid power generation system from affecting the output of the photovoltaic storage microgrid power generation system. Then, the photovoltaic output strategy and the safety isolation strategy are sorted out to obtain a control strategy for the distribution network suitable for the uneven temporal and spatial distribution, volatility and current working state of the photovoltaic storage microgrid power generation system. Finally, the distribution network responds to the control strategy to execute the control action to adjust the power, improve the power supply quality of the distribution network, and significantly improve the stability of the corresponding distribution network. At the same time, the present application can also use the formulation process of the safety isolation strategy to discover abnormal electrical equipment in advance and isolate it, protect the normal electrical equipment in the photovoltaic storage microgrid power generation system, and issue an alarm after the isolation is completed to remind the operation and maintenance personnel to perform maintenance.

[0045] The above specific embodiments are preferred embodiments of the present invention, and are not intended to limit the specific implementation scope of the present invention. The scope of the present invention includes but is not limited to the present specific embodiments. All equivalent changes made in accordance with the shape, structure, and method of the present invention are within the protection scope of the present invention.

Claims

1. A control method for a photovoltaic storage microgrid power generation system, characterized in that: The method comprises the following steps: S1. Acquire real-time operation data of the photovoltaic storage microgrid, and pre-process the real-time operation data to obtain an operation data set; S2. determining photovoltaic characteristics according to the operating data set and feature extraction rules, and formulating a photovoltaic output strategy based on the photovoltaic characteristics; Synchronously, judging the working state of the photovoltaic-storage microgrid power generation system based on the operating data set, and formulating a safety isolation strategy based on the working state of the photovoltaic-storage microgrid power generation system; S3, sorting out the photovoltaic output strategy and the safety isolation strategy to obtain the control strategy of the photovoltaic storage microgrid power generation system corresponding to the distribution network; S4. The corresponding distribution network executes a control action in response to the control strategy.

2. A control method for a photovoltaic microgrid power generation system according to claim 1, characterized in that: In S1, the specific process of preprocessing the real-time operation data to obtain the operation data set is: S111, inputting the real-time operation data into a filter to filter and obtain noise-free operation data, and performing statistical analysis on the noise-free operation data to determine missing values ​​and abnormal values; S112: Remove the abnormal values ​​and mark them as active missing values, and use the spline interpolation method to fill the missing values ​​and active missing values ​​to obtain a running data set.

3. A control method for a photovoltaic microgrid power generation system according to claim 1, characterized in that: In S2, the specific process of determining the photovoltaic characteristics according to the operating data set and the feature extraction rule is: S211, calculating the power variation according to the photovoltaic power generation power and the load power in the operation data set, and determining the time scale of the power variation according to the time scale variation of the photovoltaic power generation power and the time scale variation of the load power; S212: Performing derivative conversion on the power variation based on the time scale of the power variation to obtain photovoltaic characteristics.

4. A control method for a photovoltaic microgrid power generation system according to claim 3, characterized in that: In S2, the specific process of formulating the photovoltaic output strategy based on photovoltaic characteristics is as follows: S221, determining a photovoltaic action threshold based on a charging rate and a discharging rate of an energy storage module in a photovoltaic microgrid power generation system; S222. Analyze the power flow of the photovoltaic storage microgrid power generation system according to the photovoltaic characteristics and photovoltaic action thresholds to obtain a photovoltaic output strategy.

5. A control method for a photovoltaic energy storage microgrid power generation system according to claim 4, characterized in that: In S221, the energy storage module charging rate and the energy storage module discharging rate are determined by a rate adjustment formula, and the rate adjustment formula is specifically: Where u[k] is the energy conversion rate of the energy storage module in the kth cycle, y[k] is the state of the photovoltaic microgrid power generation system, and y ref [k] is the reference trajectory of energy storage module charging and discharging, ρ is the penalty factor of control action, N p is the predicted number of steps of the photovoltaic output action, J[k] is the energy loss in the kth cycle, and t is the starting time of charging and discharging of the energy storage module.

6. A control method for a photovoltaic energy storage microgrid power generation system according to claim 1, characterized in that: In S2, the specific process of determining the working state of the photovoltaic storage microgrid power generation system based on the operating data set is as follows: S231, extracting topological features based on the topological structure of the photovoltaic storage microgrid power generation system, and dividing the operating data set into a multi-object data set and a single-object data set based on the topological features; S232, performing a horizontal comparison analysis based on the corresponding topological features of the multi-object data set and the multi-object data set, and performing a vertical comparison analysis based on the single-object data set, the single-object threshold and the vertical time threshold; S233. Arrange the results of the horizontal comparison analysis and the vertical comparison analysis to obtain the working status of the photovoltaic storage microgrid power generation system.

7. A control method for a photovoltaic energy storage microgrid power generation system according to claim 6, characterized in that: In S2, the specific process of formulating a safety isolation strategy based on the working state of the photovoltaic storage microgrid power generation system is as follows: S241, determining abnormal nodes and normal nodes based on the working state of the photovoltaic storage microgrid power generation system and the topological structure of the photovoltaic storage microgrid power generation system; S242, planning an energy flow path in the topology structure of the photovoltaic storage microgrid power generation system according to the abnormal nodes and the normal nodes; S243. Formulate a fault isolation action based on the energy flow path to obtain a safety isolation strategy.

8. A control method for a photovoltaic microgrid power generation system according to claim 1, characterized in that: In S3, the specific process of sorting out the photovoltaic output strategy and the safety isolation strategy to obtain the control strategy of the photovoltaic storage microgrid power generation system corresponding to the distribution network is: The topology of the photovoltaic microgrid power generation system is adjusted based on the safety isolation strategy, and the power regulation action of the distribution network is formulated according to the adjusted topology of the photovoltaic microgrid power generation system, the photovoltaic output strategy and the real-time operation data of the corresponding distribution network to obtain the control strategy of the corresponding distribution network.

9. A photovoltaic storage microgrid power generation system, characterized in that: Including: photovoltaic power generation module, energy storage module, safety monitoring module, intelligent control module; The output end of the photovoltaic power generation module is electrically connected to the first input end of the intelligent control module, the data collection end of the photovoltaic power generation module is electrically connected to the data collection end of the safety monitoring module, the controlled end of the photovoltaic power generation module is electrically connected to the first control end of the intelligent control module, the output end of the energy storage module is electrically connected to the second input end of the intelligent control module, the data collection end of the energy storage module is electrically connected to the data collection end of the safety monitoring module, the controlled end of the energy storage module is electrically connected to the second control end of the intelligent control module, and the data collection end of the safety monitoring module is electrically connected to the data collection end of the intelligent control module.

10. A photovoltaic energy storage microgrid power generation system according to claim 9, characterized in that: The energy storage module includes: Lithium-ion battery packs, supercapacitors; The lithium-ion battery pack is connected in parallel with the supercapacitor, and a first common point, a second common point and a third common point are provided in the parallel circuit of the lithium-ion battery pack and the supercapacitor, wherein the first common point serves as an output end of the energy storage module, the second common point serves as a data collection end of the energy storage module, and the third common point serves as a controlled end of the energy storage module.

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