A demand response based residential microgrid coordination interaction method and system

Abstract

The application discloses a kind of based on demand response's resident family microgrid coordination interaction method and system, comprising: the power supply parameter of resident is obtained by sensor, analysis is carried out, obtains coordination and is analyzed, and cooperation user is screened out, analysis its historical cooperation times, obtains coordination cooperation ratio;Coordination cooperation ratio is compared with coordination cooperation ratio threshold, and positive response user is screened out, and positive response signal is generated;Based on positive response signal, the power supply parameter of positive response user is analyzed, and unit cost is obtained;Unit cost is analyzed, and cost deviation ratio is obtained;Cost deviation ratio is compared with cost deviation ratio threshold, whether the family microgrid needs to be improved is judged, if yes, improvement signal is generated;Based on improvement signal, the power supply parameter of positive response user is analyzed, and microgrid excellent value is obtained, reference microgrid excellent value maximum family microgrid, the family microgrid needing to be improved is improved, and the application improves the enthusiasm of user response grid demand.

Description

Technical Field

[0001] This invention belongs to the field of energy management technology, specifically a method and system for coordinated interaction of residential microgrids based on demand response. Background Technology

[0002] A home microgrid typically comprises distributed power sources, energy storage systems, controllable loads, and their control devices, forming a relatively independent micro-system. The system uses smart interactive devices to facilitate the exchange of electricity and information, supporting functions such as renewable energy generation, energy storage device charging and discharging, and surplus electricity feeding into the grid. Successful implementation of demand response depends on the active participation and cooperation of users. However, different users have varying levels of enthusiasm for demand response; some users may be unwilling to participate due to their electricity usage habits or economic considerations. Furthermore, users may sacrifice some electricity comfort or increase electricity costs when participating in demand response, which could lead to decreased user satisfaction. The construction and operation costs of home microgrid systems are relatively high, including investments in hardware equipment, energy storage, and system maintenance.

[0003] The existing technologies for coordinating and interacting with residential microgrids mainly have the following problems at the data processing level: The lack of quantitative evaluation of user response behavior: Most existing technologies rely directly on the power supply parameters collected by physical sensors for simple comparison, lacking multi-dimensional data mining and dynamic modeling of users' historical cooperation behavior, and cannot accurately identify "actively responding users" and "non-actively responding users", resulting in a lack of data support for subsequent incentive strategies. The current methods lack sophisticated calculation and deviation analysis of electricity costs: the cost structure of different power sources (grid, distributed generation, energy storage) is complex and includes hidden costs such as equipment depreciation and maintenance. Existing methods have failed to establish a complete electricity cost data model, and cannot automatically calculate unit cost and cost deviation ratio from a large amount of user data, thus failing to locate users with abnormal costs. Lack of a data-driven microgrid optimization recommendation mechanism: When it is determined that a user's household microgrid needs improvement, the existing technology does not provide an automated, horizontal comparison method based on the calculation of best values, making it difficult to select the optimal microgrid configuration from a large number of users and generate targeted optimization solutions.

[0004] In summary, a demand-response-based method for analyzing and coordinating large-scale user electricity consumption data is needed. This method would collect user power supply parameters, historical coordination frequency, and cost data from various power sources. It would then utilize pre-defined data processing models (such as coordinated electricity consumption value models, cost deviation ratio models, and microgrid excellence value models) to perform automated calculations and threshold comparisons, generating positive response signals, improvement signals, and optimized user tags. This would guide users or the system in adjusting microgrid configurations. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for coordinated interaction of residential microgrids based on demand response, so as to solve at least one of the above-mentioned problems in the prior art.

[0006] In a first aspect, the present invention provides a method for coordinated interaction of residential microgrids based on demand response, comprising: Step 1: Acquire power supply information from each power source in the household through sensors. Analyze the data on the user's off-grid power supply and grid power supply during high-load periods to obtain the coordinated power consumption value. If the user's coordinated power consumption value is greater than or equal to the coordinated power consumption threshold, the user is marked as a cooperating user. Analyze the historical number of times the cooperating user has cooperated to obtain the coordination ratio. Step 2: Compare the coordination ratio with the coordination ratio threshold, and determine whether the user is a positive responder based on the comparison result. If so, generate a positive response signal. Step 3: Based on the positive response signal, obtain the power supply sources of all positive response users and the electricity cost of each power supply source, perform data analysis, and obtain the average unit cost per kilowatt-hour used by positive response users; Step 4: Analyze the unit cost of all active response users to obtain the cost deviation ratio; compare the cost deviation ratio with the cost deviation ratio threshold, and determine whether the home microgrid of active response users needs to be improved based on the comparison result. If improvement is needed, generate an improvement signal. Step 5: Based on the improved signal, process the electricity consumption and unit cost of the users who actively respond to obtain the microgrid excellence value. Compare the microgrid excellence value with the microgrid excellence threshold. Based on the comparison result, determine whether the user's household microgrid needs to be optimized. If so, mark the corresponding user as an optimized user.

[0007] Secondly, the present invention provides a demand-response-based residential microgrid coordination and interaction system, comprising: Response parameter acquisition module: It acquires power supply information from each power source in the household through sensors, analyzes the user's non-grid power supply and grid power supply during high load periods, and obtains the coordinated power consumption value; if the user's coordinated power consumption value is greater than or equal to the coordinated power consumption threshold, the user is marked as a cooperating user, and the historical number of cooperations of cooperating users is analyzed to obtain the coordination ratio; Response parameter analysis module: compares the coordination ratio with the coordination ratio threshold, and determines whether the user is a positive responder based on the comparison result. If so, it generates a positive response signal. Cost parameter acquisition module: Based on the positive response signal, acquire the power supply source of all positive response users and the electricity cost of each power supply source, perform data analysis, and obtain the unit cost per kilowatt-hour of electricity used by the positive response users on average; Cost parameter analysis module: Analyzes the unit cost of all active response users to obtain the cost deviation ratio; compares the cost deviation ratio with the cost deviation ratio threshold, and determines whether the microgrid of the active response users' homes needs to be improved based on the comparison result. If improvement is needed, an improvement signal is generated. Improvement Analysis Module: Based on the improvement signal, the module processes the electricity consumption and unit cost of users who respond positively to obtain the microgrid excellence value. The microgrid excellence value is compared with the microgrid excellence threshold. Based on the comparison result, it is determined whether the user's household microgrid needs optimization. If so, the corresponding user is marked as an optimized user.

[0008] The beneficial effects of this invention are: 1. By acquiring power supply information from all power sources in a user's household through sensors, and analyzing this information, it is determined whether the user actively responds to the grid's load reduction requests during periods of high grid load. Further analysis of the user's historical response frequency determines whether the user is an active responder. Users are then screened to identify active responders, providing a basis for analyzing their electricity consumption information and determining their electricity costs. This analysis lays the foundation for determining how to reduce users' electricity costs.

[0009] 2. Obtain the power supply sources and power supply costs of all actively responding users, analyze and process them to obtain the unit cost per kilowatt-hour of electricity used by actively responding users on average; analyze the obtained unit cost, and determine whether the user's home microgrid needs improvement based on the analysis results; this invention analyzes the average cost per kilowatt-hour of electricity for actively responding users, determines whether the user's home microgrid is reasonable, and whether the user's home microgrid needs improvement, which can reduce the user's cost and make the user's home microgrid more reasonable; improve the user's enthusiasm for responding to grid demand and the user's response capability.

[0010] 3. By selecting better home microgrids and optimizing them, users' home microgrids can be improved, reducing their electricity costs and increasing their willingness to respond to grid demands and coordinate with the grid. Increasing the proportion of non-grid power supply in users' home microgrids and optimizing energy storage systems also helps improve users' ability to controllably dispatch loads according to grid demands. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a flowchart illustrating a method for obtaining the coordination ratio of a residential microgrid based on demand response, as provided in Embodiment 1 of the present invention. Figure 2 This is a flowchart illustrating a method for obtaining unit cost based on demand response in a residential microgrid coordination and interaction according to Embodiment 2 of the present invention; Figure 3 This is a flowchart of a method for obtaining microgrid excellence values ​​based on demand response and coordinated interaction in residential microgrids, provided in Embodiment 3 of the present invention. Figure 4 This is a schematic diagram of a demand-response-based residential microgrid coordination and interaction system provided in Embodiment 4 of the present invention. Detailed Implementation

[0013] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.

[0014] Example 1 like Figure 1 As shown in the figure, the present invention provides a method for coordinated interaction of residential microgrids based on demand response, which specifically includes the following steps: Step 1: Acquire power supply information from each power source in the household through sensors. Analyze the data on the user's off-grid power supply and grid power supply during high-load periods to obtain the coordinated power consumption value. If the user's coordinated power consumption value is greater than or equal to the coordinated power consumption threshold, the user is marked as a cooperating user. Analyze the historical number of times the cooperating user has cooperated to obtain the coordination ratio. It should be noted that, in addition to the public power grid, the power supply sources for households in a home microgrid generally include distributed power stations, energy storage devices, etc.; based on demand response, power is supplied to users through distributed power sources, energy storage devices, etc. in the home microgrid to reduce the load on the power grid. When the power grid is under high load, a response is sent to users; after the response is sent, the user's electricity consumption information is analyzed to determine whether the user responds actively and cooperates in reducing the load; The power source for the user's power supply is obtained through sensors, as well as the power output of each power source; Obtain the power supply to users from the community's distributed power stations and energy storage devices; It should be noted that community distributed power stations include, but are not limited to, household distributed photovoltaic power stations; energy storage devices store the excess electricity generated by community distributed power stations and charge the storage devices when electricity prices are low; and provide power to users when electricity prices are high. The power supply to users from the community's distributed power station is labeled as distributed power supply; the power supply to users from energy storage devices is labeled as energy storage power supply; the distributed power supply and energy storage power supply are summed to obtain the off-grid power supply, which is labeled as FD. During periods of high grid load, the amount of electricity supplied by the power grid to users is obtained. The ratio of the amount of electricity supplied by the power grid to users to the total electricity consumption of users throughout the entire period is processed to obtain the high load electricity consumption ratio, which is denoted as GF. It should be noted that the total electricity consumption period includes periods of high grid load and periods of low grid load; the total electricity consumption includes both grid power supply and non-grid power supply. The non-grid power supply (FD) and the high-load power consumption ratio (GF) are processed using the formula. The coordinated electricity consumption value XT is obtained; where a1 and a2 are preset proportional coefficients. It should be noted that the coordinated electricity consumption value represents the degree of cooperation of the user with the grid demand response when the grid demand response is received; The coordinated power consumption value is compared with the coordinated power consumption threshold. If the coordinated power consumption value is greater than or equal to the coordinated power consumption threshold, a high coordination signal is generated; otherwise, a low coordination signal is generated. It should be noted that a high-cooperation signal indicates that the corresponding user is cooperating with the demand issued by the power grid. Obtain the user's historical number of cooperations, and then calculate the ratio between the user's historical number of cooperations and the number of times the power grid issues a demand to obtain the coordination ratio. Step 2: Compare the coordination ratio with the coordination ratio threshold, and determine whether the user is a positive responder based on the comparison result. If so, generate a positive response signal. The coordinated mix ratio is compared with the coordinated mix ratio threshold. The comparison process is as follows: If the coordination ratio is greater than or equal to the coordination ratio threshold, a positive response signal is generated; If the coordination ratio is less than the coordination ratio threshold, a non-positive response signal is generated. Based on positive response signals, the corresponding users are marked as positive response users; Based on the non-positive response signal, users will be marked as non-positive response users; The technical solution of this invention is as follows: Power supply information from all power sources in a user's household is acquired through sensors; this information is analyzed to determine whether the user actively responds to the grid's load reduction requests during periods of high grid load; further, by analyzing the user's historical response frequency, it is determined whether the user is an active responder. This invention filters power supply users to identify active responders, providing a basis for analyzing their electricity consumption information and determining their electricity costs, thus offering insights into how to reduce user electricity costs.

[0015] Example 2 like Figure 2 As shown in the figure, the present invention provides a method for coordinated interaction of residential microgrids based on demand response, which specifically includes the following steps: Step 3: Based on the positive response signal, obtain the power supply sources of all positive response users and the electricity cost of each power supply source, perform data analysis, and obtain the average unit cost per kilowatt-hour used by positive response users; Obtain information on the power supply sources of users who respond positively, including the number of power supply devices, power supply volume, and power supply cost of the non-grid power supply part; and the power supply volume, power supply time, and corresponding electricity price of the grid power supply part. The electricity costs for actively responding to users are calculated in detail; The electricity cost for actively responding to users will be marked as Y; During a user's electricity consumption, the electricity price varies at different times. The entire electricity consumption period is evenly divided into m sub-periods, each with a duration of t, and the electricity price is the same within each sub-period. The electricity price cost for non-grid power supply within a single sub-period t is denoted as ; ; in: n represents the total number of power supply devices; Indicates the operating status of the i-th power supply device, when When the value is 1, it indicates that the i-th power supply device is running; when... When the value is 0, it means that the i-th power supply device has stopped operating; This represents the power output of the i-th power supply device (unit: kW). This represents the electricity price required to supply power to the i-th power supply device; This indicates the duration of each sub-period; For off-grid power supply equipment, including but not limited to distributed power stations and energy storage batteries, the power generation efficiency and energy storage efficiency decrease with the increase of usage time, and maintenance and inspection are required during use; therefore, the cost of using off-grid power supply equipment is not limited to purchase and installation costs, but also includes maintenance and inspection costs. The cost of using a single device in a single sub-period is C; ; in: This indicates the purchase cost of a single device. This is the depreciation factor, representing the ratio of the total cost of equipment installation and maintenance to the cost of purchasing the equipment. Indicates the maximum time the device can be used; Among them, depreciation factor The method of obtaining it is: The equipment current is collected by a current sensor, analyzed, and the equipment damage is determined to count the number of equipment repairs. It should be noted that by recording the equipment current, if the equipment current becomes abnormal, the equipment is shut down, and at this time the equipment current is zero; the number of times the equipment current becomes zero after the abnormality is counted is recorded as the number of equipment maintenance. The number of equipment repairs is denoted as T, where the first repair is denoted as... The nth maintenance is marked as ; Obtain the time interval t between two equipment maintenance operations, where the time interval between the first and second maintenance operations is... The time interval between the (n-1)th maintenance and the nth maintenance is ; Construct a two-dimensional coordinate system Tt with the number of equipment repairs T as the horizontal axis and the interval t between two equipment repairs as the vertical axis; mark the repair intervals in the two-dimensional coordinate system Tt and connect them sequentially to obtain the repair interval curve; divide the repair interval curve according to the number of repairs to obtain the repair interval sub-curve. Obtain the slope of each maintenance interval sub-curve, and calculate the variance of the slope of each maintenance interval sub-curve to obtain the slope variance. The slope variance is compared with the variance threshold. If the slope variance is greater than the variance threshold, a divergent signal is generated. If the slope variance is less than or equal to the variance threshold, a convergent signal is generated. Based on the divergent signal, a nonlinear correlation is shown between the time intervals between two equipment maintenance operations; the equipment usage time and the number of equipment maintenance operations are obtained; the ratio of the number of equipment maintenance operations to the equipment usage time is processed to obtain the average maintenance interval; The longest time the device can be used The remaining usage time is obtained by taking the difference from the equipment usage time; the remaining usage time is then compared with the average maintenance interval to obtain the estimated number of maintenance operations. Based on the convergent signal, it indicates a linear correlation between the time interval between two equipment maintenance sessions; by extending the maintenance interval curve, the time interval between each equipment maintenance session within the remaining usage time is obtained, and thus the expected number of remaining maintenance sessions is obtained. Calculate all repair prices, sum them up, and take the average to obtain the average equipment repair price. Sum the estimated remaining number of repairs with the number of equipment repairs to get the estimated total number of equipment repairs; multiply the estimated total number of equipment repairs with the average equipment repair price to get the estimated equipment repair cost; Obtain the equipment installation cost, sum it with the estimated equipment maintenance cost to get the total cost of equipment installation and maintenance, and then ratio the total cost of equipment installation and maintenance to the equipment purchase cost to obtain the depreciation factor. ; The usage costs of all non-grid-powered devices within the same sub-period are summed to obtain the usage cost of the non-grid-powered devices in a single sub-period, denoted as . ; Based on the calculation and Calculate the electricity price cost for users' electricity supplied outside the grid throughout the entire time period, and mark it as... ; ; Where m is the number of sub-time periods; This represents the non-grid power supply cost for the i-th sub-time period; Obtain the electricity price cost of the user using grid power throughout the entire time period, and mark it as... ; The electricity cost Y for users who receive a positive response throughout the entire period is: ; Obtain the total daily electricity consumption G of users who actively respond throughout the entire period; Based on the obtained electricity cost Y of positive response users throughout the entire period and the daily electricity consumption G throughout the entire period, the formula is used. The unit cost R is obtained; It should be noted that unit cost represents the average cost per kilowatt-hour used by a user in a proactive response. Step 4: Analyze the unit cost of all active response users to obtain the cost deviation ratio; compare the cost deviation ratio with the cost deviation ratio threshold, and determine whether the home microgrid of active response users needs to be improved based on the comparison result. If improvement is needed, generate an improvement signal. The average unit cost is obtained by summing the unit costs R of all positive-responding users. The cost deviation ratio is obtained by comparing the unit cost R with the average unit cost. The cost deviation ratio is compared with the cost deviation ratio threshold. The comparison process is as follows: If the cost deviation ratio is greater than or equal to the cost deviation ratio threshold, an improvement signal is generated; If the cost deviation ratio is less than the cost deviation ratio threshold, a non-improvement signal is generated; Based on the unmodified signal, no action is required. Based on the improved signal, improvements were made to the user's home microgrid; The technical solution of this invention is as follows: Obtain the power supply sources and power supply costs of all actively responding users, analyze and process them to obtain the unit cost per kilowatt-hour of electricity used by actively responding users; analyze the obtained unit cost, and determine whether improvements to the user's home microgrid are needed based on the analysis results; this invention analyzes the average cost per kilowatt-hour of electricity for actively responding users, determines whether the user's home microgrid is reasonable, and whether improvements are needed, thereby reducing user costs and making the user's home microgrid more reasonable; and increasing users' enthusiasm for responding to grid demands.

[0016] Example 3 like Figure 3 As shown in the figure, the present invention provides a method for coordinated interaction of residential microgrids based on demand response, which specifically includes the following steps: Step 5: Based on the improved signal, process the electricity consumption and unit cost of the users who actively respond to obtain the microgrid excellence value. Compare the microgrid excellence value with the microgrid excellence threshold. Based on the comparison result, determine whether the user's household microgrid needs to be optimized. If so, mark the corresponding user as an optimized user. Based on the improved signal, the daily electricity consumption of extreme response users is obtained, and the daily electricity consumption is compared with the daily electricity consumption threshold to obtain the daily electricity consumption ratio, which is marked as YD. Obtain the unit cost of users who respond positively, and then compare the unit cost with a unit cost threshold to obtain the unit cost ratio, which is denoted as CB. The data of daily electricity consumption ratio and unit cost ratio were processed using the formula. The microgrid performance value YU is obtained; where c1 and c2 are preset proportional coefficients. It should be noted that the microgrid excellence value indicates the excellence level of a user's home microgrid. The higher the microgrid excellence value, the stronger the home microgrid's ability to store electricity, and the stronger the user's ability to respond to the grid's demands. The microgrid excellence value is compared with the microgrid excellence threshold. The comparison process is as follows: If the microgrid's excellence value is greater than or equal to the microgrid's excellence threshold, an excellence signal is generated, and the corresponding user is marked as an excellent user; no action is taken on the excellent user. If the microgrid's excellence value is less than the microgrid's excellence threshold, an optimization signal is generated, and the corresponding user is marked as an optimized user. The system optimizes users' home microgrid systems by introducing an intelligent monitoring system to monitor the operating status and parameters of the microgrid system in real time; through data analysis, it can promptly identify and address problems and faults in the system; and by utilizing remote control technology, it can achieve remote maintenance and fault diagnosis of the microgrid system; thereby reducing maintenance costs and improving the reliability and availability of the system. The technical solution of this invention is as follows: by selecting better home microgrids, the user's home microgrid is improved, reducing the user's electricity expenses while increasing the user's enthusiasm for responding to grid demands; increasing the proportion of non-grid power supply in the user's home microgrid also helps to improve the user's controllable load dispatching capability for grid demands.

[0017] Example 4 like Figure 4 As shown in the figure, the residential microgrid coordination and interaction system based on demand response provided by this embodiment of the invention specifically includes the following modules: Response parameter acquisition module: It acquires power supply information from each power source in the household through sensors, analyzes the user's non-grid power supply and grid power supply during high load periods, and obtains the coordinated power consumption value; if the user's coordinated power consumption value is greater than or equal to the coordinated power consumption threshold, the user is marked as a cooperating user, and the historical number of cooperations of cooperating users is analyzed to obtain the coordination ratio; Response parameter analysis module: compares the coordination ratio with the coordination ratio threshold, and determines whether the user is a positive responder based on the comparison result. If so, it generates a positive response signal. Cost parameter acquisition module: Based on the positive response signal, acquire the power supply source of all positive response users and the electricity cost of each power supply source, perform data analysis, and obtain the unit cost per kilowatt-hour of electricity used by the positive response users on average; Cost parameter analysis module: Analyzes the unit cost of all active response users to obtain the cost deviation ratio; compares the cost deviation ratio with the cost deviation ratio threshold, and determines whether the microgrid of the active response users' homes needs to be improved based on the comparison result. If improvement is needed, an improvement signal is generated. Optimization Analysis Module: Based on the improvement signal, the module processes the electricity consumption and unit cost of users who respond positively to obtain the microgrid excellence value. The microgrid excellence value is compared with the microgrid excellence threshold. Based on the comparison result, it is determined whether the user's household microgrid needs optimization. If so, the corresponding user is marked as an optimized user.

[0018] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A method for coordinated interaction of residential microgrids based on demand response, characterized in that, Includes the following steps: Step 1: Acquire power supply information from each power source in the household through sensors. Analyze the data on the user's off-grid power supply and grid power supply during high-load periods to obtain the coordinated power consumption value. If the user's coordinated power consumption value is greater than or equal to the coordinated power consumption threshold, the user is marked as a cooperating user. Analyze the historical number of times the cooperating user has cooperated to obtain the coordination ratio. By analyzing distributed power supply and energy storage power supply, the off-grid power supply FD is obtained; The power supply of the power grid was analyzed to obtain the high load power consumption ratio GF; The non-grid power supply (FD) and the high-load power consumption ratio (GF) are processed using the formula. The coordinated electricity consumption value XT is obtained; where a1 and a2 are preset proportional coefficients. Step 2: Compare the coordination ratio with the coordination ratio threshold, and determine whether the user is a positive responder based on the comparison result. If so, generate a positive response signal. Step 3: Based on the positive response signal, obtain the power supply sources of all positive response users and the electricity cost of each power supply source, perform data analysis, and obtain the average unit cost per kilowatt-hour used by positive response users; Step 4: Analyze the unit cost of all active responders to obtain the cost deviation ratio; The cost deviation ratio is compared with the cost deviation ratio threshold. Based on the comparison result, it is determined whether improvements are needed for the home microgrids of responsive users. If improvements are needed, an improvement signal is generated. Step 5: Based on the improved signal, process the electricity consumption and unit cost of the users who actively respond to obtain the microgrid excellence value. Compare the microgrid excellence value with the microgrid excellence threshold. Based on the comparison result, determine whether the user's household microgrid needs to be optimized. If so, mark the corresponding user as an optimized user. The method for obtaining the microgrid's excellence values ​​is as follows: Based on the improved signal, the daily electricity consumption of extreme response users is obtained, and the daily electricity consumption is compared with the daily electricity consumption threshold to obtain the daily electricity consumption ratio, which is marked as YD. Obtain the unit cost of users who respond positively, and then compare the unit cost with a unit cost threshold to obtain the unit cost ratio, which is denoted as CB. The data of daily electricity consumption ratio and unit cost ratio were processed using the formula. The microgrid performance value YU is obtained; where c1 and c2 are preset proportional coefficients.

2. The method for coordinated interaction of residential microgrids based on demand response as described in claim 1, characterized in that, The method for obtaining the non-grid power supply is as follows: The power supply to users from the community's distributed power station is labeled as distributed power supply; the power supply to users from the energy storage device is labeled as energy storage power supply; the distributed power supply and the energy storage power supply are summed to obtain the off-grid power supply, which is labeled as FD.

3. The method for coordinated interaction of residential microgrids based on demand response as described in claim 1, characterized in that, The method for obtaining the high-load electricity consumption ratio is as follows: During periods of high grid load, the amount of electricity supplied by the power grid to users is obtained. The ratio of the amount of electricity supplied by the power grid to users to the total electricity consumption of users throughout the entire period is processed to obtain the high load electricity consumption ratio, which is denoted as GF.

4. The method for coordinated interaction of residential microgrids based on demand response according to claim 1, characterized in that, The method for obtaining the coordination ratio is as follows: The coordinated power consumption value is compared with the coordinated power consumption threshold. If the coordinated power consumption value is greater than or equal to the coordinated power consumption threshold, a high coordination signal is generated. Based on the high cooperation signal, the user corresponding to the high cooperation signal is marked as a cooperative user; Obtain the user's historical number of cooperation attempts, and then calculate the ratio between the user's historical number of cooperation attempts and the number of times the power grid issues demands to obtain the coordination ratio.

5. A method for coordinated interaction of residential microgrids based on demand response, as described in claim 1, characterized in that, The method for obtaining the unit cost is as follows: Obtain the electricity price cost of the user using grid power throughout the entire time period, and mark it as... ; The electricity cost Y for users who receive a positive response throughout the entire period is: Obtain the total daily electricity consumption G of users who actively respond throughout the entire period; Based on the obtained electricity cost Y of positive response users throughout the entire period and the daily electricity consumption G throughout the entire period, the formula is used. The unit cost R is obtained.

6. A method for coordinated interaction of residential microgrids based on demand response, as described in claim 5, is characterized in that... The electricity price cost of the off-grid power supply The method of obtaining it is: Divide the entire electricity consumption period into m sub-periods, each sub-period having a duration of t, and the electricity price is the same in each sub-period. Using formula Obtain the electricity price cost of non-grid power supply within a single sub-period t, and label it as... ; Where n represents the total number of power supply devices; Indicates the operating status of the i-th power supply device, when When the value is 1, it indicates that the i-th power supply device is running; when... When the value is 0, it means that the i-th power supply device has stopped operating; This represents the power output of the i-th power supply device (unit: kW). This represents the electricity price required to supply power to the i-th power supply device; This indicates the duration of each sub-period; Using formula The cost of using a single device in a single sub-period is C; in, This indicates the purchase cost of a single device. This is the depreciation factor; Indicates the maximum time the device can be used; The usage costs of all non-grid-powered devices within the same sub-period are summed to obtain the usage cost of the non-grid-powered devices in a single sub-period, denoted as . ; Based on the calculation and Using the formula Calculate the electricity price cost for the user's electricity supplied outside the grid throughout the entire time period, and label it as follows. .

7. A method for coordinated interaction of residential microgrids based on demand response, as described in claim 6, is characterized in that, The depreciation factor s1 is obtained as follows: Mark the number of equipment repairs as T; obtain the interval t between each two equipment repairs; Construct a two-dimensional coordinate system Tt; in the two-dimensional coordinate system Tt, mark and connect the maintenance interval time t to obtain the maintenance interval curve, and divide it into maintenance interval sub-curves according to the number of maintenance. Obtain the slope and variance of each maintenance interval sub-curve to obtain the slope variance; compare the slope variance with the variance threshold. If the slope variance is greater than the variance threshold, a divergent signal is generated; otherwise, a convergent signal is generated. Based on the divergent signal; the ratio of the number of equipment repairs to the equipment usage time is processed to obtain the average repair interval; the ratio of the remaining usage time to the average repair interval is processed to obtain the estimated remaining number of repairs; Based on the convergence signal, the time interval between each equipment maintenance within the remaining usage time is obtained, thereby yielding the estimated remaining number of maintenance operations. The estimated remaining maintenance count is summed with the total number of equipment maintenance operations, and then multiplied by the average equipment maintenance cost to obtain the estimated equipment maintenance cost. The depreciation factor is obtained by ratioing the total cost of equipment installation and maintenance to the equipment purchase cost. .

8. A demand-response-based residential microgrid coordination and interaction system, based on the demand-response-based residential microgrid coordination and interaction method according to any one of claims 1 to 7, characterized in that, Includes the following modules: Response parameter acquisition module: It acquires power supply information from each power source in the household through sensors, analyzes the user's non-grid power supply and grid power supply during high load periods, and obtains the coordinated power consumption value; if the user's coordinated power consumption value is greater than or equal to the coordinated power consumption threshold, the user is marked as a cooperating user, and the historical number of cooperations of cooperating users is analyzed to obtain the coordination ratio; Response parameter analysis module: compares the coordination ratio with the coordination ratio threshold, and determines whether the user is a positive responder based on the comparison result. If so, it generates a positive response signal. Cost parameter acquisition module: Based on the positive response signal, acquire the power supply source of all positive response users and the electricity cost of each power supply source, perform data analysis, and obtain the unit cost per kilowatt-hour of electricity used by the positive response users on average; Cost parameter analysis module: Analyzes the unit cost of all active responders to obtain the cost deviation ratio; The cost deviation ratio is compared with the cost deviation ratio threshold. Based on the comparison result, it is determined whether improvements are needed for the home microgrids of responsive users. If improvements are needed, an improvement signal is generated. Improvement Analysis Module: Based on the improvement signal, the module processes the electricity consumption and unit cost of users who respond positively to obtain the microgrid excellence value. The microgrid excellence value is compared with the microgrid excellence threshold. Based on the comparison result, it is determined whether the user's household microgrid needs optimization. If so, the corresponding user is marked as an optimized user.

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