Energy storage scheduling management system based on photovoltaic power generation system

Abstract

The invention discloses an energy storage scheduling management system based on a photovoltaic power generation system, which relates to the technical field of energy storage scheduling and comprises a power utilization area division unit, a power utilization time period division unit, a power utilization prediction unit, an energy storage scheduling generation unit, an emergency scheduling unit and a scheduling execution unit, the method comprises the steps of performing block division on an electronic fence to obtain an electronic fence section, correspondingly dividing the electronic fence section into a first-level active area, a second-level active area and a third-level active area, performing power consumption time period division on an electronic fence area based on deer group historical activity data, and predicting power consumption energy storage requirements of the electronic fence area in different time periods. Determining an electric quantity distribution scheme and a charging and discharging plan for supplying power to each electronic fence area in different time periods, judging the interception efficiency of the electronic fence area through the real-time image data of the deer group in combination with the real-time state of the deer group in the electronic area, and generating an emergency scheduling signal; therefore, electric energy transmission and distribution between the electronic fence and the photovoltaic power generation system are controlled.

Description

Technical Field

[0001] This invention relates to the field of energy storage dispatching technology, specifically to an energy storage dispatching and management system based on a photovoltaic power generation system. Background Technology

[0002] With urban expansion and increasing demand for ecological protection, nature reserves such as wetlands and mountain pastures around cities are gradually bordering human settlements and farmland. In these areas, wild animals (such as deer) may break through the boundaries of the nature reserve and enter human activity areas due to foraging, migration, or being frightened (such as by vehicles or noise), which will affect human life. To solve this problem, the traditional method is to set up a pulsed electronic fence at the boundary of the nature reserve based on photovoltaic power generation system. When the deer approach and try to cross the electronic fence, a short high-voltage pulse is released to prevent them from escaping through pain stimulation. However, traditional electronic fences are usually set up as a whole, centrally managed by a photovoltaic power generation system, and typically use a constant voltage power supply 24 hours a day. This makes it impossible for the electronic fence to adjust its energy consumption according to the activity of the deer herd and to schedule the energy storage power consumption of the electronic fence. During periods when the deer herd is not very active, the electronic fence continues to output high voltage, causing a large amount of energy to be consumed. As a result, during periods when the deer herd is very active, the energy storage is over-consumed and cannot maintain an effective interception voltage. In addition, when the deer herd escapes in large numbers, the fixed voltage may also fail to intercept the deer, which will affect human life.

[0003] Therefore, in view of this, the present invention proposes an energy storage dispatch and management system based on photovoltaic power generation system to make up for and improve the shortcomings of the prior art. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides an energy storage dispatch and management system based on a photovoltaic power generation system, thereby resolving the corresponding technical issues raised in the background section.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: an energy storage dispatch and management system based on a photovoltaic power generation system, comprising an electricity consumption area division unit, an electricity consumption time period division unit, an electricity consumption prediction unit, an energy storage dispatch generation unit, an emergency dispatch unit, and a dispatch execution unit; The electricity consumption area division unit is used to acquire electronic fence distribution data within the nature reserve, import the electronic fence distribution data into a three-dimensional model to generate an electronic fence distribution model, divide the electronic fence into blocks based on the electronic fence distribution model to obtain electronic fence segments, acquire historical activity data of deer herds within the nature reserve, construct an activity calculation model using a weighted scoring method, calculate the activity level corresponding to the electronic fence segments, and classify the electronic fence segments into first-level active areas, second-level active areas, and third-level active areas according to the preset activity level judgment interval, and send the classification results to the electricity consumption time period division unit; The electricity consumption period division unit is used to obtain the level division results. Based on the 24-hour system and combined with the historical activity data of the deer herd, the electricity consumption period is further divided according to the level division results, and the electricity consumption period division results are sent to the electricity consumption prediction unit. The electronic fence prediction unit is used to obtain the electricity consumption period division results, predict the electricity storage demand of the electronic fence area at different time periods based on the actual electricity consumption of the electronic fence area, and send the prediction results to the energy storage scheduling generation unit. The energy storage scheduling generation unit is used to obtain the prediction results, combine them with the preset energy storage data of the electronic fence, determine the power allocation scheme and charging and discharging plan for powering each electronic fence area at different time periods, and integrate them into a scheduling strategy and send it to the scheduling execution unit. The emergency dispatch unit is used to acquire real-time image data of the deer herd through cameras installed within the electronic fence area, and to determine the interception efficiency of the electronic fence area in combination with the real-time status of the deer herd within the electronic fence area, so as to generate an emergency dispatch signal and send it to the dispatch execution unit.

[0006] Preferably, the scheduling execution unit is used to acquire scheduling strategies and emergency scheduling signals and convert them into specific scheduling instructions, control the power transmission and distribution between the electronic fence and the photovoltaic power generation system, perform charging or discharging operations on the electronic fence, monitor the execution of scheduling instructions in real time, and feed back the actual data during the execution process to the energy storage scheduling decision unit and the emergency scheduling unit so as to dynamically adjust and optimize the scheduling strategies and emergency scheduling signals.

[0007] As a preferred method, the specific process for calculating the activity level corresponding to the electronic fence segment is as follows: S101. Obtain the electronic fence distribution model. Using a grid-based partitioning method, divide the electronic fence distribution model according to the grid to obtain electronic fence segments. S102. Obtain historical activity data of the deer herd. Extract the frequency of deer appearance and the duration of deer stay in each electronic fence segment from the historical activity data. Construct an activity calculation model using a weighted scoring method to calculate the activity level A corresponding to each electronic fence segment. The calculation formula is as follows: ; Where f is the frequency of deer appearance, representing the number of times a deer herd appears in a certain electronic fence section per unit time. s is the duration of the deer herd's stay, representing the average time the deer herd stays in a certain section of the electronic fence; and These are the weighting coefficients for frequency of occurrence and duration of stay, respectively. .

[0008] As a preferred method, the specific process of classifying electronic fence sections into levels based on preset activity levels is as follows: S201. Obtain a preset activity level judgment interval, wherein the preset activity level judgment interval includes a low activity level interval. Medium activity range and high activity range ,in, ; S202. Compare the calculated activity level A for each electronic fence segment with the preset activity level judgment interval, and divide the electronic fence segments as follows: If activity level A is in the low activity range Within this area, the corresponding electronic fence section is designated as a Level 1 active zone; If activity level A is in the medium activity range Within this area, the corresponding electronic fence section is divided into a secondary active zone; If activity level A is in the high activity range Within the area, the corresponding electronic fence section is divided into three levels of active zones.

[0009] As a preferred option, the specific process for further dividing electricity consumption periods based on the classification results is as follows: S301. Based on a 24-hour clock and using hourly units, obtain the frequency of deer occurrence in primary, secondary, and tertiary active areas from historical deer activity data, quantify the time-specific distribution characteristics of deer activity, and obtain time-specific frequencies. The calculation formula is as follows: ; Where i∈{1,2,3} corresponds to the first-level active region, the second-level active region, and the third-level active region, respectively; j∈{0,1,…,23} corresponds to twenty-four hours; d represents the total number of days; Let represent the number of times the deer herd appears in the i-th level active area on day k in hour j, where k∈{1,2,…,d}; S302, Based on time-specific frequencies Calculate the overall time-period frequency for all hours in the Level 1, Level 2, and Level 3 active regions. The calculation formula is as follows: ; Where m represents the number of active regions; S303, Based on the overall frequency of the time period Set the threshold for high electricity consumption periods as follows: Set the threshold for low electricity consumption periods as follows: ,in, and All are preset coefficients, and , ; S304. Based on the set high electricity consumption period threshold and low electricity consumption period threshold, the electricity consumption period division criteria are set as follows: If time period-specific frequency satisfy Then mark the corresponding time period as a high electricity consumption period; If time period-specific frequency satisfy If so, the corresponding time period is marked as a low electricity consumption period.

[0010] As a preferred method, the specific process for predicting the electricity storage demand of the electronic fence area at different times is as follows: S401. Obtain the actual electricity consumption data of the first-level active area, the second-level active area, and the third-level active area at different time periods and perform normalization processing. Establish an electricity consumption forecasting model using an autoregressive moving average model, the expression of which is: ; in, This represents the predicted electricity consumption of the i-th active region during the t+k time period, where k is the prediction step size and k>0; c is a constant term; P is the autoregressive order. It is the p-th autoregressive coefficient. It is the electricity consumption of the i-th level active region during the time period t+kp; Q is the order of the moving average. It is the q-th moving average coefficient. It is the error term of the i-th level active region during the time period t+kq; It is the error term of the i-th level active region during time period t+k; S402. Substitute actual electricity consumption data into the electricity consumption prediction model, and use Python to estimate parameters to determine c. and Based on the parameter values, a complete electricity consumption prediction model is established; S403. Calculate the energy storage demand for the primary, secondary, and tertiary active regions during the t+k time period. The calculation formula is as follows: ; in, It is the energy storage demand coefficient, and ;

[0011] β is the reserve energy storage, and β is a fixed value used to cope with sudden power demand and prediction errors.

[0012] As a preferred approach, the specific process of integrating into a scheduling strategy is as follows: S501. Obtain the power storage demand of the electronic fence area at different times. Combined with the energy storage data preset by the electronic fence, including the maximum energy storage capacity of the energy storage device. and minimum safe energy storage capacity The power allocation plan is determined as follows: The electricity allocation ratios for Level 1, Level 2, and Level 3 active areas are set according to the actual electricity demand of each active area. , and ,and The power supply of the first-level active region during the t+k period is... The power supply of the secondary active region during the t+k period The power supply of the Level 3 active region during the t+k period. ; S502, Based on the power allocation scheme and the current energy storage status of the energy storage device. The following charging and discharging plan is formulated: like Then, a charging operation will be performed, and the charging capacity will be [value missing]. ; like Then a discharge operation is performed, and the discharge amount is... Among them, the remaining power of the energy storage device after discharge shall not be less than ; S503: Integrate the power allocation scheme and charging / discharging plan into a scheduling strategy and send it to the scheduling execution unit.

[0013] As a preferred method, the specific process for generating emergency dispatch signals is as follows: S601. Acquire and process real-time image data of the deer herd within the electronic fence area. Use a pre-trained YOLOv5 target detection model to detect and locate the deer herd in the real-time image data and determine the electronic fence area where the deer herd is located. S602. Obtain the real-time status of the deer herd within the electronic fence area by using infrared sensors and pressure sensors installed within the electronic fence area, including infrared sensor data, pressure sensor data, and the total number of deer attempting to cross. and the number of deer successfully intercepted To determine the interception efficiency of the electronic fence area. The calculation formula is as follows: ; S603, the calculated result Compared with the preset interception efficiency threshold If a comparison is made, If the electronic fence where the deer herd is located fails to intercept the deer, an emergency dispatch signal will be generated and sent to the dispatch execution unit.

[0014] Compared with existing technologies, the beneficial effects of this invention are as follows: Electronic fences are divided into sections based on distribution data within nature reserves. Based on historical deer activity data, the activity level of each electronic fence section is calculated using an activity calculation model, classifying these sections into primary, secondary, and tertiary active areas. Furthermore, based on historical deer activity data, the electronic fence areas are further divided into electricity consumption periods. According to the actual electricity consumption of the electronic fence areas, the energy storage demand of the electronic fence areas at different times is predicted. Combined with the preset energy storage data of the electronic fences, the power allocation scheme and charging / discharging plan for supplying power to each electronic fence area at different times are determined. Additionally, by using real-time image data of the deer and combining it with the real-time status within the electronic area where the deer are located, the interception efficiency of the electronic fence area is judged, generating an emergency dispatch signal to control the power transmission and distribution between the electronic fences and the photovoltaic power generation system. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the overall structure of a preferred embodiment of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Embodiments of the present invention: Please refer to Figure 1 As shown, an energy storage dispatch and management system based on a photovoltaic power generation system includes an electricity consumption area division unit, an electricity consumption time period division unit, an electricity consumption forecasting unit, an energy storage dispatch generation unit, an emergency dispatch unit, and a dispatch execution unit. The electricity consumption area division unit is used to acquire electronic fence distribution data within the nature reserve and import the electronic fence distribution data into a 3D model to generate an electronic fence distribution model. Based on the electronic fence distribution model, the electronic fence is divided into blocks to obtain electronic fence segments. At the same time, historical activity data of deer herds within the nature reserve is acquired. An activity calculation model is constructed using a weighted scoring method to calculate the activity level corresponding to the electronic fence segments. According to the preset activity judgment interval, the electronic fence segments are classified into first-level active areas, second-level active areas, and third-level active areas. The classification results are then sent to the electricity consumption time period division unit. The electricity consumption period segmentation unit is used to obtain the level segmentation results. Based on the 24-hour system and combined with the historical activity data of the deer herd, the electricity consumption period is further segmented according to the level segmentation results, and the electricity consumption period segmentation results are sent to the electricity consumption forecasting unit. The electronic fence prediction unit is used to obtain the results of electricity consumption period division, predict the electricity storage demand of the electronic fence area at different times based on the actual electricity consumption of the electronic fence area, and send the prediction results to the energy storage scheduling generation unit. The energy storage scheduling generation unit is used to obtain the prediction results, combine them with the preset energy storage data of the electronic fence, determine the power allocation scheme and charging and discharging plan for each electronic fence area at different time periods, and integrate them into a scheduling strategy and send it to the scheduling execution unit. The emergency dispatch unit is used to acquire real-time image data of the deer herd through cameras installed within the electronic fence area, and to determine the interception efficiency of the electronic fence area in combination with the real-time status of the deer herd within the electronic fence area, so as to generate an emergency dispatch signal and send it to the dispatch execution unit.

[0018] The scheduling execution unit is used to acquire scheduling strategies and emergency scheduling signals and convert them into specific scheduling instructions. It controls the power transmission and distribution between the electronic fence and the photovoltaic power generation system, performs charging or discharging operations on the electronic fence, and monitors the execution of scheduling instructions in real time. It feeds back the actual data during the execution process to the energy storage scheduling decision unit and the emergency scheduling unit so as to dynamically adjust and optimize the scheduling strategies and emergency scheduling signals.

[0019] The specific process for calculating the activity level of a segment within an electronic fence is as follows: S101. Obtain the electronic fence distribution model. Using a grid-based partitioning method, divide the electronic fence distribution model according to the grid to obtain electronic fence segments. S102. Obtain historical activity data of the deer herd. Extract the frequency of deer appearance and the duration of deer stay in each electronic fence segment from the historical activity data. Construct an activity calculation model using a weighted scoring method to calculate the activity level A corresponding to each electronic fence segment. The calculation formula is as follows: ; Where f is the frequency of deer appearance, representing the number of times a deer herd appears in a certain electronic fence section per unit time. s is the duration of the deer herd's stay, representing the average time the deer herd stays in a certain section of the electronic fence; and These are the weighting coefficients for frequency of occurrence and duration of stay, respectively. .

[0020] The specific process of classifying electronic fence sections into levels based on preset activity levels is as follows: S201. Obtain a preset activity level judgment range, which includes a low activity level range. Medium activity range and high activity range ,in, ; S202. Compare the calculated activity level A for each electronic fence segment with the preset activity level judgment interval, and divide the electronic fence segments as follows: If activity level A is in the low activity range Within this area, the corresponding electronic fence section is designated as a Level 1 active zone; If activity level A is in the medium activity range Within this area, the corresponding electronic fence section is divided into a secondary active zone; If activity level A is in the high activity range Within the area, the corresponding electronic fence section is divided into three levels of active zones.

[0021] The specific process for further dividing electricity usage periods based on the classification results is as follows: S301. Based on a 24-hour clock and using hourly units, obtain the frequency of deer occurrence in primary, secondary, and tertiary active areas from historical deer activity data, quantify the time-specific distribution characteristics of deer activity, and obtain time-specific frequencies. The calculation formula is as follows: ; Where i∈{1,2,3} corresponds to the first-level active region, the second-level active region, and the third-level active region, respectively; j∈{0,1,…,23} corresponds to twenty-four hours; d represents the total number of days; Let represent the number of times the deer herd appears in the i-th level active area on day k in hour j, where k∈{1,2,…,d}; S302, Based on time-specific frequencies Calculate the overall time-period frequency for all hours in the Level 1, Level 2, and Level 3 active regions. The calculation formula is as follows: ; Where m represents the number of active regions; S303, Based on the overall frequency of the time period Set the threshold for high electricity consumption periods as follows: Set the threshold for low electricity consumption periods as follows: ,in, and All are preset coefficients, and , ; S304. Based on the set high electricity consumption period threshold and low electricity consumption period threshold, the electricity consumption period division criteria are set as follows: If time period-specific frequency satisfy Then mark the corresponding time period as a high electricity consumption period; If time period-specific frequency satisfy If so, the corresponding time period is marked as a low electricity consumption period.

[0022] The specific process for predicting the electricity and energy storage demand of an electronic fence area at different times is as follows: S401. Obtain the actual electricity consumption data of the first-level active area, the second-level active area, and the third-level active area at different time periods and perform normalization processing. Establish an electricity consumption forecasting model using an autoregressive moving average model, the expression of which is: ; in, This represents the predicted electricity consumption of the i-th active region during the t+k time period, where k is the prediction step size and k>0; c is a constant term; P is the autoregressive order. It is the p-th autoregressive coefficient. It is the electricity consumption of the i-th level active region during the time period t+kp; Q is the order of the moving average. It is the q-th moving average coefficient. It is the error term of the i-th level active region during the time period t+kq; It is the error term of the i-th level active region during time period t+k; S402. Substitute actual electricity consumption data into the electricity consumption prediction model, and use Python to estimate parameters to determine c. and Based on the parameter values, a complete electricity consumption prediction model is established; S403. Calculate the energy storage demand for the primary, secondary, and tertiary active regions during the t+k time period. The calculation formula is as follows: ; in, It is the energy storage demand coefficient, and ;

[0023] β is the reserve energy storage, and β is a fixed value used to cope with sudden power demand and prediction errors.

[0024] The specific process of integrating them into a scheduling strategy is as follows: S501. Obtain the power storage demand of the electronic fence area at different times. Combined with the energy storage data preset by the electronic fence, including the maximum energy storage capacity of the energy storage device. and minimum safe energy storage capacity The power allocation plan is determined as follows: The electricity allocation ratios for Level 1, Level 2, and Level 3 active areas are set according to the actual electricity demand of each active area. , and ,and The power supply of the first-level active region during the t+k period is... The power supply of the secondary active region during the t+k period The power supply of the Level 3 active region during the t+k period. ; S502, Based on the power allocation scheme and the current energy storage status of the energy storage device. The following charging and discharging plan is formulated: like Then, a charging operation will be performed, and the charging capacity will be [value missing]. ; like Then a discharge operation is performed, and the discharge amount is... Among them, the remaining power of the energy storage device after discharge shall not be less than ; S503: Integrate the power allocation scheme and charging / discharging plan into a scheduling strategy and send it to the scheduling execution unit.

[0025] The specific process for generating emergency dispatch signals is as follows: S601. Acquire and process real-time image data of the deer herd within the electronic fence area. Use a pre-trained YOLOv5 target detection model to detect and locate the deer herd in the real-time image data and determine the electronic fence area where the deer herd is located. S602. Obtain the real-time status of the deer herd within the electronic fence area by using infrared sensors and pressure sensors installed within the electronic fence area, including infrared sensor data, pressure sensor data, and the total number of deer attempting to cross. and the number of deer successfully intercepted To determine the interception efficiency of the electronic fence area. The calculation formula is as follows: ; S603, the calculated result Compared with the preset interception efficiency threshold If a comparison is made, If the electronic fence where the deer herd is located fails to intercept the deer, an emergency dispatch signal will be generated and sent to the dispatch execution unit.

[0026] Compared with existing technologies, this method uses data on the distribution of electronic fences within a nature reserve to divide the electronic fences into blocks, creating electronic fence sections. Based on historical deer activity data, an activity calculation model is used to calculate the activity level of each electronic fence section, classifying them into Level 1, Level 2, and Level 3 active areas. Furthermore, based on historical deer activity data, the electricity consumption periods within the electronic fence areas are further divided. Based on the actual electricity consumption of each electronic fence area, the energy storage demand at different times is predicted. Combined with pre-set energy storage data for the electronic fences, the required electricity supply to each electronic fence area at different times is determined. The system includes a power allocation scheme and a charging / discharging plan. Furthermore, by using real-time image data of the deer herd and combining it with the real-time status of the electronic area where the deer herd is located, the interception efficiency of the electronic fence area is determined, and an emergency dispatch signal is generated. This controls the power transmission and distribution between the electronic fence and the photovoltaic power generation system, thereby achieving energy storage dispatch and management of the electronic fence. Power supply to each active area is scheduled according to specific power consumption periods. Energy storage is increased during high-power consumption periods and reduced during low-power consumption periods. This not only avoids excessive energy consumption but also effectively intercepts deer herds approaching or attempting to cross, thus improving the interception efficiency of the deer herds and reducing their impact on human life.

[0027] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value.

[0028] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. In the two embodiments provided in this application, it should be understood that the disclosed apparatus and system can be implemented in other ways; for example, the apparatus embodiments described above are merely illustrative, and the division of modules is merely a logical functional division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed; furthermore, the coupling or direct coupling or communication connection between the shown or discussed mutuals can be through some interfaces, and the indirect coupling or communication connection between the apparatus or modules can be electrical, mechanical or other forms. The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A storage dispatch and management system based on a photovoltaic power generation system, characterized in that, It includes a power consumption area division unit, a power consumption time period division unit, a power consumption forecasting unit, an energy storage dispatch generation unit, an emergency dispatch unit, and a dispatch execution unit; The electricity consumption area division unit is used to acquire electronic fence distribution data within the nature reserve, import the electronic fence distribution data into a three-dimensional model to generate an electronic fence distribution model, divide the electronic fence into blocks based on the electronic fence distribution model to obtain electronic fence segments, acquire historical activity data of deer herds within the nature reserve, construct an activity calculation model using a weighted scoring method, calculate the activity level corresponding to the electronic fence segments, and classify the electronic fence segments into first-level active areas, second-level active areas, and third-level active areas according to the preset activity level judgment interval, and send the classification results to the electricity consumption time period division unit; The electricity consumption period division unit is used to obtain the level division results. Based on the 24-hour system and combined with the historical activity data of the deer herd, the electricity consumption period is further divided according to the level division results, and the electricity consumption period division results are sent to the electricity consumption prediction unit. The electronic fence prediction unit is used to obtain the electricity consumption period division results, predict the electricity storage demand of the electronic fence area at different time periods based on the actual electricity consumption of the electronic fence area, and send the prediction results to the energy storage scheduling generation unit. The energy storage scheduling generation unit is used to obtain the prediction results, combine them with the preset energy storage data of the electronic fence, determine the power allocation scheme and charging and discharging plan for powering each electronic fence area at different time periods, and integrate them into a scheduling strategy and send it to the scheduling execution unit. The emergency dispatch unit is used to acquire real-time image data of the deer herd through cameras installed within the electronic fence area, and to determine the interception efficiency of the electronic fence area in combination with the real-time status of the deer herd within the electronic fence area, so as to generate an emergency dispatch signal and send it to the dispatch execution unit.

2. The energy storage dispatch and management system based on a photovoltaic power generation system according to claim 1, characterized in that, The scheduling execution unit is used to acquire scheduling strategies and emergency scheduling signals and convert them into specific scheduling instructions, control the power transmission and distribution between the electronic fence and the photovoltaic power generation system, perform charging or discharging operations on the electronic fence, monitor the execution of scheduling instructions in real time, and feed back the actual data during the execution process to the energy storage scheduling decision unit and the emergency scheduling unit so as to dynamically adjust and optimize the scheduling strategies and emergency scheduling signals.

3. The energy storage dispatch and management system based on a photovoltaic power generation system according to claim 2, characterized in that, The specific process for calculating the activity level of a segment within an electronic fence is as follows: S101. Obtain the electronic fence distribution model. Using a grid-based partitioning method, divide the electronic fence distribution model according to the grid to obtain electronic fence segments. S102. Obtain historical activity data of the deer herd. Extract the frequency of deer appearance and the duration of deer stay in each electronic fence segment from the historical activity data. Construct an activity calculation model using a weighted scoring method to calculate the activity level A corresponding to each electronic fence segment. The calculation formula is as follows: ； Where f is the frequency of deer appearance, representing the number of times a deer herd appears in a certain electronic fence section per unit time. s is the duration of the deer herd's stay, representing the average time the deer herd stays in a certain section of the electronic fence; and These are the weighting coefficients for frequency of occurrence and duration of stay, respectively. .

4. The energy storage dispatch and management system based on a photovoltaic power generation system according to claim 3, characterized in that, The specific process of classifying electronic fence sections into different levels based on preset activity levels is as follows: S201. Obtain a preset activity level judgment interval, wherein the preset activity level judgment interval includes a low activity level interval. Medium activity range and high activity range ,in, ; S202. Compare the calculated activity level A for each electronic fence segment with the preset activity level judgment interval, and divide the electronic fence segments as follows: If activity level A is in the low activity range Within this area, the corresponding electronic fence section is designated as a Level 1 active zone; If activity level A is in the medium activity range Within this area, the corresponding electronic fence section is divided into a secondary active zone; If activity level A is in the high activity range Within the area, the corresponding electronic fence section is divided into three levels of active zones.

5. The energy storage dispatch and management system based on a photovoltaic power generation system according to claim 4, characterized in that, The specific process for further dividing electricity usage periods based on the classification results is as follows: S301. Based on a 24-hour clock and using hourly units, obtain the frequency of deer occurrence in primary, secondary, and tertiary active areas from historical deer activity data, quantify the time-specific distribution characteristics of deer activity, and obtain time-specific frequencies. The calculation formula is as follows: ； Where i∈{1,2,3} corresponds to the first-level active region, the second-level active region, and the third-level active region, respectively; j∈{0,1,…,23} corresponds to twenty-four hours; d represents the total number of days; Let represent the number of times the deer herd appears in the i-th level active area on day k in hour j, where k∈{1,2,…,d}; S302, Based on time-specific frequencies Calculate the overall time-period frequency for all hours in the Level 1, Level 2, and Level 3 active regions. The calculation formula is as follows: ； Where m represents the number of active regions; S303, Based on the overall frequency of the time period Set the threshold for high electricity consumption periods as follows: Set the threshold for low electricity consumption periods as follows: ,in, and All are preset coefficients, and , ; S304. Based on the set high electricity consumption period threshold and low electricity consumption period threshold, the electricity consumption period division criteria are set as follows: If time period-specific frequency satisfy Then mark the corresponding time period as a high electricity consumption period; If time period-specific frequency satisfy If so, the corresponding time period is marked as a low electricity consumption period.

6. The energy storage dispatch and management system based on a photovoltaic power generation system according to claim 5, characterized in that, The specific process for predicting the electricity and energy storage demand of an electronic fence area at different times is as follows: S401. Obtain the actual electricity consumption data of the first-level active area, the second-level active area, and the third-level active area at different time periods and perform normalization processing. Establish an electricity consumption forecasting model using an autoregressive moving average model, the expression of which is: ； in, This represents the predicted electricity consumption of the i-th active region during the t+k time period, where k is the prediction step size and k>0; c is a constant term; P is the autoregressive order. It is the p-th autoregressive coefficient. It is the electricity consumption of the i-th level active region during the time period t+kp; Q is the order of the moving average. It is the q-th moving average coefficient. It is the error term of the i-th level active region during the time period t+kq; It is the error term of the i-th level active region during time period t+k; S402. Substitute actual electricity consumption data into the electricity consumption prediction model, and use Python to estimate parameters to determine c. and Based on the parameter values, a complete electricity consumption prediction model is established; S403. Calculate the energy storage demand for the primary, secondary, and tertiary active regions during the t+k time period. The calculation formula is as follows: ； in, It is the energy storage demand coefficient, and ; β is the reserve energy storage, and β is a fixed value used to cope with sudden power demand and prediction errors.

7. The energy storage dispatch and management system based on a photovoltaic power generation system according to claim 6, characterized in that, The specific process of integrating them into a scheduling strategy is as follows: S501. Obtain the power storage demand of the electronic fence area at different times. Combined with the energy storage data preset by the electronic fence, including the maximum energy storage capacity of the energy storage device. and minimum safe energy storage capacity The power allocation plan is determined as follows: The electricity allocation ratios for Level 1, Level 2, and Level 3 active areas are set according to the actual electricity demand of each active area. , and ,and The power supply of the first-level active region during the t+k period is... The power supply of the secondary active region during the t+k period The power supply of the Level 3 active region during the t+k period. ; S502, Based on the power allocation scheme and the current energy storage status of the energy storage device. The following charging and discharging plan is formulated: like Then, a charging operation will be performed, and the charging capacity will be [value missing]. ; like Then a discharge operation is performed, and the discharge amount is... Among them, the remaining power of the energy storage device after discharge shall not be less than ; S503: Integrate the power allocation scheme and charging / discharging plan into a scheduling strategy and send it to the scheduling execution unit.

8. The energy storage dispatch and management system based on a photovoltaic power generation system according to claim 7, characterized in that, The specific process for generating emergency dispatch signals is as follows: S601. Acquire and process real-time image data of the deer herd within the electronic fence area. Use a pre-trained YOLOv5 target detection model to detect and locate the deer herd in the real-time image data and determine the electronic fence area where the deer herd is located. S602. Obtain the real-time status of the deer herd within the electronic fence area by using infrared sensors and pressure sensors installed within the electronic fence area, including infrared sensor data, pressure sensor data, and the total number of deer attempting to cross. and the number of deer successfully intercepted To determine the interception efficiency of the electronic fence area. The calculation formula is as follows: ； S603, the calculated result Compared with the preset interception efficiency threshold If a comparison is made, If the electronic fence where the deer herd is located fails to intercept the deer, an emergency dispatch signal will be generated and sent to the dispatch execution unit.

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