Distributed photovoltaic management method and system based on four fusible terminals

Abstract

The invention discloses a distributed photovoltaic management method and system based on four fusible terminals, and relates to the technical field of energy management. The system comprises a data acquisition and classification module, a data analysis and feature extraction module, a real-time data analysis and strategy matching module and a control operation and feedback evaluation module. The data acquisition and classification module acquires historical data from the database and performs classification based on switching and flexible control records to form data units and extract features; the data analysis and feature extraction module identifies key features of a switching and flexible control strategy by analyzing historical data features; the real-time data analysis and strategy matching module obtains real-time data, extracts real-time features, compares the real-time features with historical data features, and matches corresponding switching and flexible control strategies; and the control operation and feedback evaluation module executes corresponding operation according to the matched control strategy, analyzes feedback data, evaluates a control effect and generates an adjustment strategy.

Description

Technical Field

[0001] The present invention relates to the field of energy management technology, and in particular to a distributed photovoltaic management method and system based on four fusion terminals. Background Art

[0002] As the global demand for renewable energy continues to increase, distributed photovoltaic power generation, as a clean and green form of energy, has become an important part of microgrids and smart energy systems. Especially in urban and rural areas, distributed photovoltaic systems have been widely used due to their flexibility and environmental protection. However, due to the intermittent and unstable nature of photovoltaic power generation, its power generation is affected by many factors such as weather, time, and season, which can easily lead to instability in power output. This instability makes distributed photovoltaic systems often face the challenge of access and disconnection control when they are connected to the grid. Especially in microgrids, the instability of photovoltaic power generation may have a negative impact on the frequency, stability, and power quality of the power grid.

[0003] Existing distributed photovoltaic management methods mostly rely on traditional single control methods. These methods are difficult to achieve accurate scheduling and flexible control of the system when faced with factors such as grid load fluctuations, unstable photovoltaic power generation, and weather changes. In addition, existing management systems often cannot fully utilize the historical data of distributed photovoltaic systems for scientific analysis, and lack intelligent and personalized control strategies, resulting in the inability to effectively improve photovoltaic power generation efficiency and reduce system operation risks. Summary of the invention

[0004] The purpose of the present invention is to provide a distributed photovoltaic management method and system based on four fusion terminals to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: A distributed photovoltaic management method based on four fusion terminals includes the following steps: Step S100. Obtain historical data and related switching and flexible control records of the distributed photovoltaic system in the low-voltage area from the database, analyze the corresponding historical data according to the switching and flexible control records, and thus obtain historical data characteristics; classify the switching and flexible control records based on the historical data characteristics; Step S200. According to the classification results of the switching and flexible control records, for the switching and flexible control records of the same category, the corresponding historical data features are obtained, and the key features related to the switching and flexible control strategies are identified by analyzing the historical data features of the switching and flexible control records of the same category and combining the corresponding switching and flexible control records; Step S300. Use the four fusion terminals to obtain real-time data of the distributed photovoltaic system in the low-voltage area, analyze the real-time data, and obtain real-time key features; compare and analyze the real-time key features with the key features corresponding to each category of switching and flexible control records, so as to match the corresponding switching and flexible control strategies; Step S400. According to the matched switching and flexible control strategies, the current distributed photovoltaic system is subjected to corresponding switching and flexible control operations, and feedback data after switching and flexible control is obtained; the feedback data is analyzed, the effects of the current switching and flexible control are evaluated, and a corresponding adjustment strategy is generated according to the evaluation results, and the generated adjustment strategy is processed accordingly by relevant personnel.

[0006] Among them, the four-in-one terminal has the characteristics of "observable, measurable, adjustable and controllable", and supports real-time data exchange and control with equipment from different manufacturers (such as photovoltaic power generation systems, energy storage equipment, load management equipment, etc.). Through unified data transmission protocols and communication interfaces, terminal devices can work together effectively and transmit device data to the cloud or edge computing nodes for processing. This compatibility makes the system more adaptable in terms of equipment diversity and technology upgrades, facilitating future expansion and upgrades.

[0007] Furthermore, step S100 includes: S101. Obtain historical data and related switching and flexible control records of the distributed photovoltaic system in the low-voltage area from the database, wherein the historical data includes photovoltaic power generation data, environmental data and load data, wherein the historical data is composed of a plurality of historical data segments, and each historical data segment has a one-to-one correspondence with a switching and flexible control record; the switching and flexible control record refers to a control behavior record of the switching and flexible control strategy that meets the corresponding system state and requirements during the operation of the distributed photovoltaic system in the low-voltage area; according to the correspondence between the historical data segment and the switching and flexible control record, the corresponding historical data segment and the switching and flexible control record are combined into a historical data unit; S102. For each historical data unit, the corresponding historical data is analyzed to extract the corresponding historical data features, and the numerical values ​​corresponding to the extracted historical data features are normalized to form a historical data feature vector V, and V=[v1,v2,...,vn], wherein n represents the dimension of the historical data feature vector V, v1 represents the eigenvalue corresponding to the first dimension of the historical data feature vector, v2 represents the eigenvalue corresponding to the second dimension of the historical data feature vector, and so on, vn represents the eigenvalue corresponding to the nth dimension of the historical data feature vector; the historical data feature vectors V of all historical data units are summarized, and the historical data feature vectors V are classified using the support vector machine method to obtain several categories of switching and flexible control records.

[0008] Further, step S200 includes: S201. According to the classification results of the switching and flexible control records, for the switching and flexible control records of the same category, the corresponding historical data feature vector V is extracted; for each dimension of the historical data feature vector V, the mean μi and standard deviation σi of the corresponding eigenvalue vi are calculated, where i ranges from 1 to n; the degree of difference between the eigenvalue vi and the corresponding mean μi and standard deviation σi is analyzed to calculate the corresponding difference index Ci, and the specific calculation formula is: Ci=(vi-μi) / σi; the difference index Ci of all dimensional eigenvalues ​​is summarized to form a difference index set CY of the historical data feature vector V, and CY={C1,C2,...,Cn}, where C1 represents the difference index of the 1st dimension eigenvalue of the historical data feature vector V, C2 represents the difference index of the 1st dimension eigenvalue of the historical data feature vector V, C3 represents the difference index of the 2nd dimension eigenvalue of the historical data feature vector V, and so on, Cn represents the difference index of the nth dimension eigenvalue of the historical data feature vector V; S202. For the difference index set CY of the historical data feature vector V corresponding to the switching and flexible control records of the same category, perform intersection calculation in sequence, summarize all intersections, classify the same intersections into one category, count the number of each intersection category, extract the intersection category with the largest number, and obtain its corresponding historical data feature vector V; according to the dimension of the historical data feature vector corresponding to the elements in the intersection, extract the historical data features of the corresponding dimension, and mark them as key features; S203. Extract the switching and flexible control records of the historical data feature vector V corresponding to the intersection category, perform semantic analysis on the switching and flexible control records to obtain the corresponding switching and flexible control strategy, and convert the format of the switching and flexible control strategy to obtain the corresponding switching and flexible control strategy feature vector K, and K=[k1,k2,...,km], where m represents the dimension of the switching and flexible control strategy feature vector K, k1 represents the first dimension feature value of the switching and flexible control strategy feature vector, k2 represents the second dimension feature value of the switching and flexible control strategy feature vector, and so on, km represents the mth dimension feature value of the switching and flexible control strategy feature vector; perform intersection calculation on all the switching and flexible control strategy feature vectors K, summarize the dimensional features of the switching and flexible control strategy feature vectors corresponding to the intersection calculation results, and correspond the key features to the dimensional features of the corresponding switching and flexible control strategy feature vectors; traverse all categories of switching and flexible control records in turn to obtain the key features related to the switching and flexible control strategy.

[0009] Furthermore, step S300 includes: S301. Use the four fusion terminals to obtain the real-time data of the distributed photovoltaic system in the low-voltage area, analyze the real-time data with reference to the analysis method of historical data, so as to obtain the real-time data features, normalize the values ​​corresponding to the real-time data features, and thus form a real-time data feature vector V'; refer to the key features corresponding to the switching and flexible control records of each category, and extract the real-time key features of the corresponding categories from the real-time data feature vector V' in turn; S302. For the key features corresponding to the switching and flexible control records of each category, the real-time key features of the corresponding category are calculated in turn with the key features corresponding to each switching and flexible control record, and the average value is taken as the average similarity of the key features of the corresponding category, and the category with the largest average similarity is selected as the real-time matching category, and the switching and flexible control strategy corresponding to the key features of the real-time matching category is used as the current matching switching and flexible control strategy.

[0010] Furthermore, step S400 includes: S401. According to the matched switching and flexible control strategy, the current distributed photovoltaic system is subjected to corresponding switching and flexible control operations, and feedback data after switching and flexible control is obtained; the switching and flexible control operations include switching operations and flexible control, wherein the switching operations are executed to turn on or off certain photovoltaic components or adjust their output power according to the control strategy, and the flexible control is performed to adjust the photovoltaic power generation power or the charging and discharging operation of the energy storage device according to the load demand or system status; the feedback data includes photovoltaic power generation data, load data and environmental data; S402. According to the feedback data, analyze the change of photovoltaic power generation, compare the photovoltaic power generation data before and after control, calculate the power change rate ΔP, and ΔP=(P_after-P_before) / P_before, where P_after represents the power generation after control, and P_before represents the power generation before control; compare the load change, calculate the load change ratio ΔL, and ΔL=(L_after-L_before) / L_before, where L_after and L_before represent the load after control and the load before control respectively; calculate the environmental adjustment coefficient E, and E=P_actual / P_theoretical, where P_actual represents the actual power generation of the photovoltaic module under the current actual environmental conditions, and P_theoretical represents the expected power generation of the photovoltaic module under ideal environmental conditions; S403. Comprehensively evaluate the effects of the current switching and flexible control according to the power change rate ΔP, the load change ratio ΔL and the environmental adjustment coefficient E, and calculate the corresponding comprehensive evaluation index R, and R=w1×ΔP+w2×ΔL+w3×E, and w1, w2 and w3 represent different weight coefficients, and w1+w2+w3=1; compare the calculated comprehensive evaluation index R with the corresponding threshold R0, if R≥R0, it means that the current matching switching and flexible control strategy is reasonable, and no operation is performed; if R<R0, it means that the current matching switching and flexible control strategy is unreasonable, then generate a corresponding adjustment strategy according to the power change rate ΔP, the load change ratio ΔL and the environmental adjustment coefficient E, and output the adjustment strategy to relevant personnel, who will perform corresponding processing on the generated adjustment strategy.

[0011] A distributed photovoltaic management system based on four fusion terminals, including: a data collection and classification module, a data analysis and feature extraction module, a real-time data analysis and strategy matching module, and a control operation and feedback evaluation module; The data acquisition and classification module acquires the historical data of the distributed photovoltaic system in the low-voltage area and the related switching and flexible control records, analyzes the corresponding historical data according to the switching and flexible control records, and obtains the historical data characteristics; based on the historical data characteristics, the switching and flexible control records are classified; The data analysis and feature extraction module obtains the corresponding historical data features for the switching and flexible control records of the same category according to the classification results of the switching and flexible control records, and identifies the key features related to the switching and flexible control strategies by analyzing the historical data features of the switching and flexible control records of the same category and combining the corresponding switching and flexible control records; The real-time data analysis and strategy matching module obtains the real-time data of the distributed photovoltaic system in the low-voltage area, analyzes the real-time data, and obtains the real-time key features; compares and analyzes the real-time key features with the key features corresponding to each category of switching and flexible control records, and matches the corresponding switching and flexible control strategies; The control operation and feedback evaluation module performs corresponding switching and flexible control operations on the current distributed photovoltaic system according to the matched switching and flexible control strategies, and obtains feedback data after switching and flexible control; analyzes the feedback data, evaluates the effects of the current switching and flexible control, and generates corresponding adjustment strategies based on the evaluation results, and relevant personnel perform corresponding processing on the generated adjustment strategies.

[0012] Further, the data acquisition and classification module includes a data acquisition unit and a data classification unit; The data acquisition unit obtains the historical data of the distributed photovoltaic system in the low-voltage area and the corresponding switching and flexible control records from the database; the data classification unit analyzes the corresponding historical data according to the switching and flexible control records to obtain the historical data characteristics; based on the historical data characteristics, the switching and flexible control records are classified.

[0013] Further, the data analysis and feature extraction module includes a data analysis unit and a key feature extraction unit; The data analysis unit extracts the corresponding historical data feature vectors for the same category of switching and flexible control records based on the classification results of the switching and flexible control records; and calculates the difference index of each dimension of the historical data feature vector based on the historical data feature vector; the key feature extraction unit establishes a difference index set based on the difference index of each dimension of the historical data feature vector, and identifies the key features related to the switching and flexible control strategies by analyzing the difference index set and intersection calculation.

[0014] Further, the real-time data analysis and strategy matching module includes a real-time data analysis unit and a strategy matching unit; The real-time data analysis unit collects the real-time data of the photovoltaic system through the four fusion terminals, analyzes and processes the real-time data, extracts the real-time data features, and generates a real-time data feature vector; refers to the key features corresponding to each category of switching and flexible control records, and extracts the real-time key features of the corresponding categories from the real-time data feature vector in turn; The strategy matching unit calculates the similarity between the real-time key features of the corresponding category and the key features corresponding to each switching and flexible control record for the key features corresponding to each category of switching and flexible control records, and calculates the average value as the average similarity of the key features of the corresponding category, selects the category with the largest average similarity as the real-time matching category, and uses the switching and flexible control strategy corresponding to the key features of the real-time matching category as the currently matched switching and flexible control strategy.

[0015] Further, the control operation and feedback evaluation module includes a control operation unit and a feedback evaluation unit; The control operation unit performs corresponding operations according to the real-time matching switching and flexible control strategies, and collects feedback data after control; the feedback evaluation unit analyzes the changes in photovoltaic power generation, load changes and environmental adjustment coefficients based on the feedback data, calculates comprehensive evaluation indicators, conducts a comprehensive evaluation of the switching and flexible control effects, and generates an adjustment strategy based on the comprehensive evaluation results, and feeds back the adjustment strategy to relevant personnel, who will then handle it accordingly.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention can accurately identify and match the switching and flexible control strategies that are most suitable for the current system status by utilizing historical data features, real-time data analysis and matching, thereby realizing intelligent scheduling and flexible control of distributed photovoltaic systems; this method avoids the problem of relying only on simple rules or manual intervention in traditional methods, and improves the automation level and response speed of the system. By deeply analyzing the historical data features and real-time data features, it is possible to accurately grasp the operating status of the photovoltaic system, select the best switching and flexible control strategies, thereby effectively improving the efficiency of photovoltaic power generation, and minimizing the instability of power generation caused by factors such as weather changes and load fluctuations. The management method of the present invention integrates the historical records and real-time feedback of switching and flexible control, and performs continuous monitoring and optimization adjustment based on real-time data, effectively avoiding the risks of grid frequency fluctuations and power quality degradation caused by the instability of photovoltaic power generation in traditional methods, and ensuring the stability and safe operation of the power grid. Through the comprehensive evaluation of real-time feedback data, including power change rate, load change ratio and environmental adjustment coefficient, the effect of the control strategy can be quantitatively evaluated, thus providing a scientific basis for subsequent decision-making; through the intelligent generation of adjustment strategies, it can effectively respond to changes in grid demand and environmental conditions, avoiding the lag and inefficiency of traditional control strategies. The present invention combines feedback data for dynamic evaluation, and effectively improves the adaptability and stability of distributed photovoltaic systems by adjusting the working status of photovoltaic power generation systems and energy storage devices in real time; compared with the prior art, the present invention can adjust the control strategy in time when the system load fluctuates or the weather changes, ensuring the efficient operation of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 It is a module schematic diagram of a distributed photovoltaic management system based on four fusion terminals of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0019] See also Figure 1 , the present invention provides a technical solution: A distributed photovoltaic management system based on four fusion terminals, including: a data collection and classification module, a data analysis and feature extraction module, a real-time data analysis and strategy matching module, and a control operation and feedback evaluation module; The data acquisition and classification module acquires the historical data of the distributed photovoltaic system in the low-voltage area and the related switching and flexible control records, analyzes the corresponding historical data according to the switching and flexible control records, and obtains the historical data characteristics; based on the historical data characteristics, the switching and flexible control records are classified; The data analysis and feature extraction module obtains the corresponding historical data features for the switching and flexible control records of the same category according to the classification results of the switching and flexible control records, and identifies the key features related to the switching and flexible control strategies by analyzing the historical data features of the switching and flexible control records of the same category and combining the corresponding switching and flexible control records; The real-time data analysis and strategy matching module obtains the real-time data of the distributed photovoltaic system in the low-voltage area, analyzes the real-time data, and obtains the real-time key features; compares and analyzes the real-time key features with the key features corresponding to each category of switching and flexible control records, and matches the corresponding switching and flexible control strategies; The control operation and feedback evaluation module performs corresponding switching and flexible control operations on the current distributed photovoltaic system according to the matched switching and flexible control strategies, and obtains feedback data after switching and flexible control; analyzes the feedback data, evaluates the effects of the current switching and flexible control, and generates corresponding adjustment strategies based on the evaluation results, and relevant personnel perform corresponding processing on the generated adjustment strategies.

[0020] The data acquisition and classification module includes a data acquisition unit and a data classification unit; The data acquisition unit obtains the historical data of the distributed photovoltaic system in the low-voltage area and the corresponding switching and flexible control records from the database; the data classification unit analyzes the corresponding historical data according to the switching and flexible control records to obtain the historical data characteristics; based on the historical data characteristics, the switching and flexible control records are classified.

[0021] The data analysis and feature extraction module includes a data analysis unit and a key feature extraction unit; The data analysis unit extracts the corresponding historical data feature vectors for the same category of switching and flexible control records based on the classification results of the switching and flexible control records; and calculates the difference index of each dimension of the historical data feature vector based on the historical data feature vector; the key feature extraction unit establishes a difference index set based on the difference index of each dimension of the historical data feature vector, and identifies the key features related to the switching and flexible control strategies by analyzing the difference index set and intersection calculation.

[0022] The real-time data analysis and strategy matching module includes a real-time data analysis unit and a strategy matching unit; The real-time data analysis unit collects the real-time data of the photovoltaic system through the four fusion terminals, analyzes and processes the real-time data, extracts the real-time data features, and generates a real-time data feature vector; refers to the key features corresponding to each category of switching and flexible control records, and extracts the real-time key features of the corresponding categories from the real-time data feature vector in turn; The strategy matching unit calculates the similarity between the real-time key features of the corresponding category and the key features corresponding to each switching and flexible control record for the key features corresponding to each category of switching and flexible control records, and calculates the average value as the average similarity of the key features of the corresponding category, selects the category with the largest average similarity as the real-time matching category, and uses the switching and flexible control strategy corresponding to the key features of the real-time matching category as the currently matched switching and flexible control strategy.

[0023] The control operation and feedback evaluation module includes a control operation unit and a feedback evaluation unit; The control operation unit performs corresponding operations according to the real-time matching switching and flexible control strategies, and collects feedback data after control; the feedback evaluation unit analyzes the changes in photovoltaic power generation, load changes and environmental adjustment coefficients based on the feedback data, calculates comprehensive evaluation indicators, conducts a comprehensive evaluation of the switching and flexible control effects, and generates an adjustment strategy based on the comprehensive evaluation results, and feeds back the adjustment strategy to relevant personnel, who will then handle it accordingly.

[0024] A distributed photovoltaic management method based on four fusion terminals includes the following steps: Step S100. Obtain historical data and related switching and flexible control records of the distributed photovoltaic system in the low-voltage area from the database, analyze the corresponding historical data according to the switching and flexible control records, and thus obtain historical data characteristics; classify the switching and flexible control records based on the historical data characteristics; Step S200. According to the classification results of the switching and flexible control records, for the switching and flexible control records of the same category, the corresponding historical data features are obtained, and the key features related to the switching and flexible control strategies are identified by analyzing the historical data features of the switching and flexible control records of the same category and combining the corresponding switching and flexible control records; Step S300. Use the four fusion terminals to obtain real-time data of the distributed photovoltaic system in the low-voltage area, analyze the real-time data, and obtain real-time key features; compare and analyze the real-time key features with the key features corresponding to each category of switching and flexible control records, so as to match the corresponding switching and flexible control strategies; Step S400. According to the matched switching and flexible control strategies, the current distributed photovoltaic system is subjected to corresponding switching and flexible control operations, and feedback data after switching and flexible control is obtained; the feedback data is analyzed, the effects of the current switching and flexible control are evaluated, and a corresponding adjustment strategy is generated according to the evaluation results, and the generated adjustment strategy is processed accordingly by relevant personnel.

[0025] Among them, the four-in-one terminal has the characteristics of "observable, measurable, adjustable and controllable", and supports real-time data exchange and control with equipment from different manufacturers (such as photovoltaic power generation systems, energy storage equipment, load management equipment, etc.). Through unified data transmission protocols and communication interfaces, terminal devices can work together effectively and transmit device data to the cloud or edge computing nodes for processing. This compatibility makes the system more adaptable in terms of equipment diversity and technology upgrades, facilitating future expansion and upgrades.

[0026] Step S100 includes: S101. Obtain historical data and related switching and flexible control records of the distributed photovoltaic system in the low-voltage area from the database, wherein the historical data includes photovoltaic power generation data, environmental data and load data, wherein the historical data is composed of a plurality of historical data segments, and each historical data segment has a one-to-one correspondence with a switching and flexible control record; the switching and flexible control record refers to a control behavior record of the switching and flexible control strategy that meets the corresponding system state and requirements during the operation of the distributed photovoltaic system in the low-voltage area; according to the correspondence between the historical data segment and the switching and flexible control record, the corresponding historical data segment and the switching and flexible control record are combined into a historical data unit; S102. For each historical data unit, the corresponding historical data is analyzed to extract the corresponding historical data features, and the numerical values ​​corresponding to the extracted historical data features are normalized to form a historical data feature vector V, and V=[v1,v2,...,vn], wherein n represents the dimension of the historical data feature vector V, v1 represents the eigenvalue corresponding to the first dimension of the historical data feature vector, v2 represents the eigenvalue corresponding to the second dimension of the historical data feature vector, and so on, vn represents the eigenvalue corresponding to the nth dimension of the historical data feature vector; the historical data feature vectors V of all historical data units are summarized, and the historical data feature vectors V are classified using the support vector machine method to obtain several categories of switching and flexible control records.

[0027] In this embodiment, the historical data characteristics include data characteristics corresponding to photovoltaic power generation data, environmental data and load data respectively. It is assumed that the historical data characteristics of photovoltaic power generation data include average power generation power, power fluctuation characteristics and power generation efficiency, etc., the historical data characteristics of environmental data include the correlation between temperature and power generation power, the average value and the standard deviation, etc., the historical data characteristics of load data include the volatility characteristics, the average value and the standard deviation, etc. of the load, and the selection of specific historical data characteristics is determined by relevant personnel.

[0028] Step S200 includes: S201. According to the classification results of the switching and flexible control records, for the switching and flexible control records of the same category, the corresponding historical data feature vector V is extracted; for each dimension of the historical data feature vector V, the mean μi and standard deviation σi of the corresponding eigenvalue vi are calculated, where i ranges from 1 to n; the degree of difference between the eigenvalue vi and the corresponding mean μi and standard deviation σi is analyzed to calculate the corresponding difference index Ci, and the specific calculation formula is: Ci=(vi-μi) / σi; the difference index Ci of all dimensional eigenvalues ​​is summarized to form a difference index set CY of the historical data feature vector V, and CY={C1,C2,...,Cn}, where C1 represents the difference index of the 1st dimension eigenvalue of the historical data feature vector V, C2 represents the difference index of the 1st dimension eigenvalue of the historical data feature vector V, C3 represents the difference index of the 2nd dimension eigenvalue of the historical data feature vector V, and so on, Cn represents the difference index of the nth dimension eigenvalue of the historical data feature vector V; S202. For the difference index set CY of the historical data feature vector V corresponding to the switching and flexible control records of the same category, perform intersection calculation in sequence, summarize all intersections, classify the same intersections into one category, count the number of each intersection category, extract the intersection category with the largest number, and obtain its corresponding historical data feature vector V; according to the dimension of the historical data feature vector corresponding to the elements in the intersection, extract the historical data features of the corresponding dimension, and mark them as key features; S203. Extract the switching and flexible control records of the historical data feature vector V corresponding to the intersection category, perform semantic analysis on the switching and flexible control records to obtain the corresponding switching and flexible control strategy, and convert the format of the switching and flexible control strategy to obtain the corresponding switching and flexible control strategy feature vector K, and K=[k1,k2,...,km], where m represents the dimension of the switching and flexible control strategy feature vector K, k1 represents the first dimension feature value of the switching and flexible control strategy feature vector, k2 represents the second dimension feature value of the switching and flexible control strategy feature vector, and so on, km represents the mth dimension feature value of the switching and flexible control strategy feature vector; perform intersection calculation on all the switching and flexible control strategy feature vectors K, summarize the dimensional features of the switching and flexible control strategy feature vectors corresponding to the intersection calculation results, and correspond the key features to the dimensional features of the corresponding switching and flexible control strategy feature vectors; traverse all categories of switching and flexible control records in turn to obtain the key features related to the switching and flexible control strategy.

[0029] In this embodiment, it is assumed that for a certain category of switching and flexible control records, the corresponding historical data feature vector V is extracted. It is assumed that there are 3 switching and flexible control records of this category, namely T1, T2 and T3, and the historical data feature vectors corresponding to the switching and flexible control records are V1, V2 and V3 respectively; for the eigenvalues ​​of each dimension of the historical data feature vectors V1, V2 and V3, the corresponding mean μ and standard deviation σ are calculated. Taking the eigenvalue v1 of the first dimension as an example, the corresponding mean μ1 and standard deviation σ1 are obtained; the degree of difference between the eigenvalue v1 and the corresponding mean μ1 and standard deviation σ1 is analyzed, so as to calculate the corresponding difference index C11, and the specific calculation formula is: C11=(v1-μ1) / σ1; for the eigenvalues ​​of the first dimension of the historical data feature vectors V1, V2 and V3, the corresponding difference index Ci is calculated, so as to obtain C11, C12 and so on. and C13; summarize the difference indicators Ci of all dimensions of the historical data feature vectors V1, V2 and V3, and form the corresponding difference indicator sets CY1, CY2 and CY3; for the difference indicator sets CY1, CY2 and CY3, perform intersection calculations in turn, i.e., CY1∩CY2, CY1∩CY3, and CY2∩CY3. Assuming that CY1∩CY2=CY1∩CY3≠CY2∩CY3, then classify the same intersections into one category, assuming that CY1∩CY2=CY1∩CY3, recorded as set A, and CY2∩CY3 as set B. Since the number of sets A is 2 and the number of sets B is 1, extract the largest number of intersection categories, and the intersection result is set A; Assuming that the dimensions of the historical data feature vectors corresponding to the elements in set A are 2, 3 and 5, extract the historical data features v2, v3 and v5 with dimensions 2, 3 and 5, and mark them as key features; Extract the switching and flexible control records T1, T2 and T3 of the historical data feature vector V corresponding to the set A respectively, perform semantic analysis on the switching and flexible control records, and convert the format of the switching and flexible control strategy to obtain the corresponding switching and flexible control strategy feature vector K, which are recorded as K1, K2 and K3 respectively; obtain the dimensional features of the switching and flexible control strategy feature vector corresponding to K1∩K2∩K3, assuming them to be k1, k2 and k4, then correspond the key features v2, v3 and v5 to k1, k2 and k4, so as to obtain the key features v2, v3 and v5 of the switching and flexible control strategy corresponding to k1, k2 and k4.

[0030] Step S300 includes: S301. Use the four fusion terminals to obtain the real-time data of the distributed photovoltaic system in the low-voltage area, analyze the real-time data with reference to the analysis method of historical data, so as to obtain the real-time data features, normalize the values ​​corresponding to the real-time data features, and thus form a real-time data feature vector V'; refer to the key features corresponding to the switching and flexible control records of each category, and extract the real-time key features of the corresponding categories from the real-time data feature vector V' in turn; S302. For the key features corresponding to the switching and flexible control records of each category, the real-time key features of the corresponding category are calculated in turn with the key features corresponding to each switching and flexible control record, and the average value is taken as the average similarity of the key features of the corresponding category, and the category with the largest average similarity is selected as the real-time matching category, and the switching and flexible control strategy corresponding to the key features of the real-time matching category is used as the current matching switching and flexible control strategy.

[0031] In this embodiment, it is assumed that the real-time data feature vector is V', and it is assumed that the switching and flexible control records are divided into two categories, namely category 1 and category 2. Taking category 1 as an example, it is assumed that the key features corresponding to category 1 are: "photovoltaic power generation" and "ambient temperature"; according to the key features corresponding to category 1, the features corresponding to "photovoltaic power generation" and "ambient temperature" are extracted from the real-time data feature vector V' as real-time key features; it is assumed that the historical data features corresponding to "photovoltaic power generation" and "ambient temperature" are calculated similarly to the real-time key features, and the similarity calculation method includes Euclidean distance, cosine distance, and the like. Similarity, etc., the historical data features corresponding to "photovoltaic power generation" and the real-time key features are calculated to obtain the similarity value S1, the historical data features corresponding to "ambient temperature" and the real-time key features are calculated to obtain the similarity value S2, and the average value is calculated, that is, (S1+S2) / 2 is the average similarity of category 1; the same operation is performed for category 2, and the average similarity of category 1 is compared with the average similarity of category 2. Assuming that the average similarity of category 1 is large, the switching and flexible control strategies corresponding to the key features of category 1 are used as the currently matched switching and flexible control strategies.

[0032] Step S400 includes: S401. According to the matched switching and flexible control strategy, the current distributed photovoltaic system is subjected to corresponding switching and flexible control operations, and feedback data after switching and flexible control is obtained; the switching and flexible control operations include switching operations and flexible control, wherein the switching operations are executed to turn on or off certain photovoltaic components or adjust their output power according to the control strategy, and the flexible control is performed to adjust the photovoltaic power generation power or the charging and discharging operation of the energy storage device according to the load demand or system status; the feedback data includes photovoltaic power generation data, load data and environmental data; S402. According to the feedback data, analyze the change of photovoltaic power generation, compare the photovoltaic power generation data before and after control, calculate the power change rate ΔP, and ΔP=(P_after-P_before) / P_before, where P_after represents the power generation after control, and P_before represents the power generation before control; compare the load change, calculate the load change ratio ΔL, and ΔL=(L_after-L_before) / L_before, where L_after and L_before represent the load after control and the load before control respectively; calculate the environmental adjustment coefficient E, and E=P_actual / P_theoretical, where P_actual represents the actual power generation of the photovoltaic module under the current actual environmental conditions, and P_theoretical represents the expected power generation of the photovoltaic module under ideal environmental conditions; S403. Comprehensively evaluate the effects of the current switching and flexible control according to the power change rate ΔP, the load change ratio ΔL and the environmental adjustment coefficient E, and calculate the corresponding comprehensive evaluation index R, and R=w1×ΔP+w2×ΔL+w3×E, and w1, w2 and w3 represent different weight coefficients, and w1+w2+w3=1; compare the calculated comprehensive evaluation index R with the corresponding threshold R0, if R≥R0, it means that the current matching switching and flexible control strategy is reasonable, and no operation is performed; if R<R0, it means that the current matching switching and flexible control strategy is unreasonable, then generate a corresponding adjustment strategy according to the power change rate ΔP, the load change ratio ΔL and the environmental adjustment coefficient E, and output the adjustment strategy to relevant personnel, who will perform corresponding processing on the generated adjustment strategy.

[0033] In this embodiment, assuming that the calculated comprehensive evaluation index R is compared with the corresponding threshold R0, the corresponding magnitude relationship is: R<R0, then the corresponding power change rate ΔP, load change ratio ΔL and environmental adjustment coefficient E are obtained, assuming the following situation: For power change rate (ΔP) and regulation strategy: Case 1: Power change rate (ΔP) deviates in the positive direction (e.g. ΔP>0.1) Regulation strategy: If the photovoltaic power generation capacity increases significantly, it may cause the grid to be overloaded, or the load may fail to consume the excess power in time. Increase the charging operation of energy storage equipment: store excess photovoltaic power generation in the energy storage system to avoid power waste.

[0034] Turn off some PV panels: Turn off or lower the output power of some PV panels to reduce power generation and make the system more compatible with load demand.

[0035] Case 2: Power change rate (ΔP) deviates negatively (e.g. ΔP < -0.1) Regulation strategy: If the photovoltaic power generation capacity drops significantly, it may be due to weather changes, component failure or other external factors. At this time: Start up backup PV panels: Turn on more PV panels to increase power generation.

[0036] Increase the discharge operation of energy storage equipment: Supplement insufficient power through energy storage equipment to maintain stable operation of the system.

[0037] Adjust load demand: Adjust the power demand on the load side through flexible control, giving priority to the use of energy storage equipment.

[0038] For load change ratio (ΔL) and regulation strategy: Case 1: Load change ratio (ΔL) deviates in the positive direction (e.g. ΔL>0.1) Regulation strategy: Increased load demand may lead to increased system burden. At this time: Adjust the photovoltaic power generation power: If the photovoltaic power generation power is sufficient, appropriately increase the photovoltaic power generation output to meet the additional load demand.

[0039] Start discharging energy storage equipment: Provide power to additional loads through energy storage equipment to reduce dependence on the power grid.

[0040] Case 2: Load change ratio (ΔL) deviates negatively (e.g. ΔL < -0.1) Regulation strategy: A decrease in load demand may lead to excess power generation. At this time: Reduce photovoltaic power generation: properly shut down some photovoltaic panels to avoid excessive power output and maintain system balance.

[0041] Increase energy storage device charging operations: Absorb excess power through the energy storage system to prevent system overload.

[0042] For the environmental adjustment factor (E) and adjustment strategy: Case 1: The environmental adjustment factor (E) is lower than expected (e.g. E < 0.8) Adjustment strategy: If the actual power generated by the photovoltaic module is far lower than the expected power under ideal conditions, it means that the light or environmental conditions are poor. At this time: Start backup PV panels or increase power output: If there are backup equipment or PV panels that can increase power, start these panels to supplement the insufficient power generation.

[0043] Increase the discharge of energy storage equipment: Under unfavorable environmental conditions, energy storage equipment can be used to supplement electricity to ensure that load demand is not affected.

[0044] Case 2: The environmental adjustment factor (E) is high (e.g. E>1.2) Adjustment strategy: If the actual power generation of the PV panels exceeds expectations (which means that the environmental conditions are good, perhaps there is sufficient sunlight), then: Increase energy storage device charging operation: store excess power generation for future use.

[0045] Adjust load demand or shut down some PV panels: If load demand does not increase accordingly, some PV panels need to be shut down to avoid excess electricity.

[0046] Comprehensive regulation strategy generation: Based on the analysis of power change rate (ΔP), load change ratio (ΔL) and environmental adjustment coefficient (E), combined with the weight of each factor and the overall operation requirements of the system, a comprehensive regulation strategy is generated. For example: If ΔP>0.1, ΔL>0.1, E<0.8, then: increase the charging operation of energy storage equipment, start more PV panels, increase the power generation capacity to meet the additional load demand, and if the weather is bad, adjust the output of PV panels appropriately.

[0047] If ΔP<-0.1, ΔL<-0.1, E>1.2, then: shut down some PV panels, reduce power generation, increase the discharge operation of energy storage equipment, maintain a stable power supply, adjust load demand, and give priority to the use of energy storage power.

[0048] According to the regulation strategy generated above, it is passed to relevant personnel or automated control systems to perform corresponding operations. These strategies may include: adjusting the switching and power output of photovoltaic system components, controlling the charging and discharging behavior of energy storage systems, and adjusting load management systems to respond to changes in power demand.

[0049] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0050] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A distributed photovoltaic management method based on four fusion terminals, characterized by: The method comprises the following steps: Step S100. Obtain historical data and related switching and flexible control records of the distributed photovoltaic system in the low-voltage area from the database, analyze the corresponding historical data according to the switching and flexible control records, and thus obtain historical data characteristics; classify the switching and flexible control records based on the historical data characteristics; Step S200. According to the classification results of the switching and flexible control records, for the switching and flexible control records of the same category, the corresponding historical data features are obtained, and the key features related to the switching and flexible control strategies are identified by analyzing the historical data features of the switching and flexible control records of the same category and combining the corresponding switching and flexible control records; Step S300. Use the four fusion terminals to obtain real-time data of the distributed photovoltaic system in the low-voltage area, analyze the real-time data, and obtain real-time key features; compare and analyze the real-time key features with the key features corresponding to each category of switching and flexible control records, so as to match the corresponding switching and flexible control strategies; Step S400. According to the matched switching and flexible control strategies, the current distributed photovoltaic system is subjected to corresponding switching and flexible control operations, and feedback data after switching and flexible control is obtained; the feedback data is analyzed, the effects of the current switching and flexible control are evaluated, and a corresponding adjustment strategy is generated according to the evaluation results, and the generated adjustment strategy is processed accordingly by relevant personnel.

2. According to claim 1, a distributed photovoltaic management method based on four fusion terminals is characterized in that: The step S100 includes: S101. Obtain historical data and related switching and flexible control records of the distributed photovoltaic system in the low-voltage area from the database, wherein the historical data includes photovoltaic power generation data, environmental data and load data, wherein the historical data is composed of a plurality of historical data segments, and each historical data segment has a one-to-one correspondence with a switching and flexible control record; the switching and flexible control record refers to a control behavior record of the switching and flexible control strategy that meets the corresponding system state and requirements during the operation of the distributed photovoltaic system in the low-voltage area; according to the correspondence between the historical data segment and the switching and flexible control record, the corresponding historical data segment and the switching and flexible control record are combined into a historical data unit; S102. For each historical data unit, the corresponding historical data is analyzed to extract the corresponding historical data features, and the numerical values ​​corresponding to the extracted historical data features are normalized to form a historical data feature vector V, and V=[v1,v2,...,vn], wherein n represents the dimension of the historical data feature vector V, v1 represents the eigenvalue corresponding to the first dimension of the historical data feature vector, v2 represents the eigenvalue corresponding to the second dimension of the historical data feature vector, and so on, vn represents the eigenvalue corresponding to the nth dimension of the historical data feature vector; the historical data feature vectors V of all historical data units are summarized, and the historical data feature vectors V are classified using the support vector machine method to obtain several categories of switching and flexible control records.

3. According to claim 2, a distributed photovoltaic management method based on four fusion terminals is characterized in that: The step S200 includes: S201. According to the classification results of the switching and flexible control records, for the switching and flexible control records of the same category, the corresponding historical data feature vector V is extracted; for each dimension of the historical data feature vector V, the mean μi and standard deviation σi of the corresponding eigenvalue vi are calculated, where i ranges from 1 to n; the degree of difference between the eigenvalue vi and the corresponding mean μi and standard deviation σi is analyzed to calculate the corresponding difference index Ci, and the specific calculation formula is: Ci=(vi-μi) / σi; the difference index Ci of all dimensional eigenvalues ​​is summarized to form a difference index set CY of the historical data feature vector V, and CY={C1,C2,...,Cn}, where C1 represents the difference index of the 1st dimension eigenvalue of the historical data feature vector V, C2 represents the difference index of the 1st dimension eigenvalue of the historical data feature vector V, C3 represents the difference index of the 2nd dimension eigenvalue of the historical data feature vector V, and so on, Cn represents the difference index of the nth dimension eigenvalue of the historical data feature vector V; S202. For the difference index set CY of the historical data feature vector V corresponding to the switching and flexible control records of the same category, perform intersection calculation in sequence, summarize all intersections, classify the same intersections into one category, count the number of each intersection category, extract the intersection category with the largest number, and obtain its corresponding historical data feature vector V; according to the dimension of the historical data feature vector corresponding to the elements in the intersection, extract the historical data features of the corresponding dimension, and mark them as key features; S203. Extract the switching and flexible control records of the historical data feature vector V corresponding to the intersection category, perform semantic analysis on the switching and flexible control records to obtain the corresponding switching and flexible control strategy, and convert the format of the switching and flexible control strategy to obtain the corresponding switching and flexible control strategy feature vector K, and K=[k1,k2,...,km], where m represents the dimension of the switching and flexible control strategy feature vector K, k1 represents the first dimension feature value of the switching and flexible control strategy feature vector, k2 represents the second dimension feature value of the switching and flexible control strategy feature vector, and so on, km represents the mth dimension feature value of the switching and flexible control strategy feature vector; perform intersection calculation on all the switching and flexible control strategy feature vectors K, summarize the dimensional features of the switching and flexible control strategy feature vectors corresponding to the intersection calculation results, and correspond the key features to the dimensional features of the corresponding switching and flexible control strategy feature vectors; traverse all categories of switching and flexible control records in turn to obtain the key features related to the switching and flexible control strategy.

4. According to claim 3, a distributed photovoltaic management method based on four fusion terminals is characterized in that: The step S300 includes: S301. Use the four fusion terminals to obtain the real-time data of the distributed photovoltaic system in the low-voltage area, analyze the real-time data with reference to the analysis method of historical data, so as to obtain the real-time data features, normalize the values ​​corresponding to the real-time data features, and thus form a real-time data feature vector V'; refer to the key features corresponding to the switching and flexible control records of each category, and extract the real-time key features of the corresponding categories from the real-time data feature vector V' in turn; S302. For the key features corresponding to the switching and flexible control records of each category, the real-time key features of the corresponding category are calculated in turn with the key features corresponding to each switching and flexible control record, and the average value is taken as the average similarity of the key features of the corresponding category, and the category with the largest average similarity is selected as the real-time matching category, and the switching and flexible control strategy corresponding to the key features of the real-time matching category is used as the current matching switching and flexible control strategy.

5. According to claim 4, a distributed photovoltaic management method based on four fusion terminals is characterized in that: The step S400 includes: S401. According to the matched switching and flexible control strategy, the current distributed photovoltaic system is subjected to corresponding switching and flexible control operations, and feedback data after switching and flexible control is obtained; the switching and flexible control operations include switching operations and flexible control, wherein the switching operations are executed to turn on or off certain photovoltaic components or adjust their output power according to the control strategy, and the flexible control is performed to adjust the photovoltaic power generation power or the charging and discharging operation of the energy storage device according to the load demand or system status; the feedback data includes photovoltaic power generation data, load data and environmental data; S402. According to the feedback data, analyze the change of photovoltaic power generation, compare the photovoltaic power generation data before and after control, calculate the power change rate ΔP, and ΔP=(P_after-P_before) / P_before, where P_after represents the power generation after control, and P_before represents the power generation before control; compare the load change, calculate the load change ratio ΔL, and ΔL=(L_after-L_before) / L_before, where L_after and L_before represent the load after control and the load before control respectively; calculate the environmental adjustment coefficient E, and E=P_actual / P_theoretical, where P_actual represents the actual power generation of the photovoltaic module under the current actual environmental conditions, and P_theoretical represents the expected power generation of the photovoltaic module under ideal environmental conditions; S403. Comprehensively evaluate the effects of the current switching and flexible control according to the power change rate ΔP, the load change ratio ΔL and the environmental adjustment coefficient E, and calculate the corresponding comprehensive evaluation index R, and R=w1×ΔP+w2×ΔL+w3×E, and w1, w2 and w3 represent different weight coefficients, and w1+w2+w3=1; compare the calculated comprehensive evaluation index R with the corresponding threshold R0, if R≥R0, it means that the current matching switching and flexible control strategy is reasonable, and no operation is performed; if R<R0, it means that the current matching switching and flexible control strategy is unreasonable, then generate a corresponding adjustment strategy according to the power change rate ΔP, the load change ratio ΔL and the environmental adjustment coefficient E, and output the adjustment strategy to relevant personnel, who will perform corresponding processing on the generated adjustment strategy.

6. A distributed photovoltaic management system based on four fusion terminals, applied to a distributed photovoltaic management method based on four fusion terminals as claimed in any one of claims 1 to 5, characterized in that: The system includes: a data collection and classification module, a data analysis and feature extraction module, a real-time data analysis and strategy matching module, and a control operation and feedback evaluation module; The data acquisition and classification module acquires historical data of the distributed photovoltaic system in the low-voltage area and related switching and flexible control records, analyzes the corresponding historical data according to the switching and flexible control records, and obtains historical data characteristics; based on the historical data characteristics, classifies the switching and flexible control records; The data analysis and feature extraction module obtains corresponding historical data features for the switching and flexible control records of the same category according to the classification results of the switching and flexible control records, and identifies key features related to the switching and flexible control strategies by analyzing the historical data features of the switching and flexible control records of the same category and combining the corresponding switching and flexible control records; The real-time data analysis and strategy matching module obtains the real-time data of the distributed photovoltaic system in the low-voltage area, analyzes the real-time data, and obtains the real-time key features; compares and analyzes the real-time key features with the key features corresponding to each category of switching and flexible control records, and matches the corresponding switching and flexible control strategies; The control operation and feedback evaluation module performs corresponding switching and flexible control operations on the current distributed photovoltaic system according to the matched switching and flexible control strategies, and obtains feedback data after switching and flexible control; analyzes the feedback data, evaluates the effects of the current switching and flexible control, and generates corresponding adjustment strategies according to the evaluation results, and the generated adjustment strategies are processed accordingly by relevant personnel.

7. A distributed photovoltaic management system based on four fusion terminals according to claim 6, characterized in that: The data acquisition and classification module includes a data acquisition unit and a data classification unit; The data acquisition unit acquires historical data of the distributed photovoltaic system in the low-voltage area and the corresponding switching and flexible control records from the database; the data classification unit analyzes the corresponding historical data according to the switching and flexible control records to obtain historical data characteristics; based on the historical data characteristics, the switching and flexible control records are classified.

8. A distributed photovoltaic management system based on four fusion terminals according to claim 6, characterized in that: The data analysis and feature extraction module includes a data analysis unit and a key feature extraction unit; The data analysis unit extracts the corresponding historical data feature vectors for the same category of switching and flexible control records based on the classification results of the switching and flexible control records; and calculates the difference index of each dimension of the historical data feature vector based on the historical data feature vector; the key feature extraction unit establishes a difference index set based on the difference index of each dimension of the historical data feature vector, and identifies the key features related to the switching and flexible control strategies by analyzing the difference index set and intersection calculation.

9. A distributed photovoltaic management system based on four fusion terminals according to claim 6, characterized in that: The real-time data analysis and strategy matching module includes a real-time data analysis unit and a strategy matching unit; The real-time data analysis unit collects real-time data of the photovoltaic system through the four fusion terminals, analyzes and processes the real-time data, extracts real-time data features, and generates a real-time data feature vector; refers to the key features corresponding to each category of switching and flexible control records, and extracts the real-time key features of the corresponding categories from the real-time data feature vector in turn; The strategy matching unit calculates the similarity between the real-time key features of the corresponding category and the key features corresponding to each switching and flexible control record for the key features corresponding to each category of switching and flexible control records, and calculates the average value as the average similarity of the key features of the corresponding category, selects the category with the largest average similarity as the real-time matching category, and uses the switching and flexible control strategy corresponding to the key features of the real-time matching category as the currently matched switching and flexible control strategy.

10. A distributed photovoltaic management system based on four fusion terminals according to claim 6, characterized in that: The control operation and feedback evaluation module includes a control operation unit and a feedback evaluation unit; The control operation unit performs corresponding operations according to the switching and flexible control strategies matched in real time, and collects feedback data after control; the feedback evaluation unit analyzes the changes in photovoltaic power generation power, load changes and environmental adjustment coefficients according to the feedback data, calculates comprehensive evaluation indicators, conducts comprehensive evaluation on the switching and flexible control effects, generates an adjustment strategy according to the comprehensive evaluation results, and feeds back the adjustment strategy to relevant personnel, who then perform corresponding processing.

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