Load management method and system based on user portraits

Abstract

The invention discloses a load management method and system based on a user portrait. The method comprises the following steps: analyzing demand response in a load management scene and an orderly power utilization scene; constructing a load management label system, wherein the load management label system comprises a user level load management label system; the power grid load is monitored, and if the demand response starting condition is met, the next step is executed; judging whether the user accords with the exclusion item index participating in the demand response, and if the exclusion item index is met, not participating in the demand response; if the demand response does not accord with the exclusion item index, scoring each dimension label in the user level load management label system according to the demand response, and obtaining a comprehensive score; and constructing a load management strategy in a demand response scene, and screening out a proper participation user list. The regulation and control strategy is formed based on the user portraits, the scientificity and effectiveness of load regulation and control are improved, and support is provided for a power grid company to execute load regulation and control.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of load management, in particular to a load management method and system based on user portrait. BACKGROUND

[0002] In the field of load management of power systems, with the increasing diversity of user types and the increasing complexity of user behaviors, as well as the in-depth implementation of demand response and orderly power utilization management modes, the traditional load management mode gradually exposes many deficiencies, and it is difficult to meet the needs of fine and personalized management, which is specifically manifested in: First, there are a large number of different types of power users in the power system, including industrial enterprises, commercial institutions, residential users, etc., and the power habits, equipment characteristics and adjustable potential of different users are significantly different. At the same time, demand response and orderly power utilization have their own characteristics in policy requirements, implementation conditions and management goals. The traditional management mode lacks in-depth analysis of the scene, and it is difficult to accurately match users and scenes, resulting in poor targeting of management measures and a significant reduction in execution effect. Second, the existing load management method often collects user information in a scattered manner, which cannot fully depict the key attributes of user power characteristics, adjustable capacity and participation willingness, making it difficult for management personnel to accurately grasp the real state and potential of users, limiting the scientificity and effectiveness of management strategies. Third, due to insufficient understanding of user characteristics and scene characteristics, existing load management strategies often use a "one-size-fits-all" approach, failing to develop differentiated management plans based on different user portraits and difficult to dynamically adjust according to scene changes, resulting in low user participation and unreasonable resource allocation, which cannot fully realize the effectiveness of demand response and orderly power utilization. Fourth, after the execution of load management, there is a lack of comprehensive and systematic evaluation index system to evaluate the execution effect, which cannot provide strong support for strategy optimization and iteration, affecting the continuous improvement of load management level. SUMMARY

[0003] In view of the deficiencies of the prior art, the present application provides a load management method and system based on user portrait, which not only deeply analyzes typical scenes, constructs a systematic label system, depicts accurate user portraits and develops individualized management strategies, but also establishes a comprehensive evaluation system to improve the fine level and execution effect of load management and ensure the stable operation and efficient utilization of power systems.

[0004] To achieve the above purpose, the present application designs a load management method based on user portrait, which is characterized by comprising the following steps: S1) analyzing demand response and orderly power utilization scenes in the load management scene; S2) constructing a load management label system based on the scenario analysis results of demand response and orderly power utilization, the load management label system comprising a user-level load management label system; the user-level load management label system comprising a basic information dimension label, a power utilization characteristic dimension label, an adjustable capacity dimension label, an adjustable technology dimension label, an adjustable economy dimension label, and a participation willingness dimension label; S3) monitoring the grid load, if the demand response opening condition is reached, then entering step S4) according to the gap size, occurrence time, duration, and occurrence area of the demand response; if the demand response opening condition is not reached, then continuing to monitor the grid load; S4) judging whether the user meets the exclusion item indicators of participating in the demand response, if the user meets any of the exclusion item indicators of the demand response, then not participating in this demand response; if the user does not meet all of the exclusion item indicators of the demand response, then scoring each dimension label in the user-level load management label system according to this demand response, and adding up the scores to obtain a comprehensive score; S5) constructing a load management strategy under the demand response scenario, the specific steps of the load management strategy under the demand response scenario being as follows, According to the above comprehensive score, the users are ranked, and then the ranked users are sequentially listed in the user list participating in this demand response according to the ranking until the total adjustable load exceeds the gap value, so as to screen out a suitable participation user list.

[0005] Further, S3) further comprises monitoring the grid load, if the orderly power utilization opening condition is reached, then entering step S4) according to the gap size, occurrence time, duration, and occurrence area of the orderly power utilization; if the orderly power utilization opening condition is not reached, then continuing to monitor the grid load.

[0006] Further, in S3), the opening condition of the demand response or the orderly power utilization is judged by frequency deviation, voltage overrun, power transmission / distribution equipment overload, load supply-demand gap prediction, and emergency power protection instruction.

[0007] Further, in S4), the exclusion item indicators of the demand response comprise not being in the demand area, not being in the target industry range, being a six-protection user, and the maximum adjustable load not meeting the requirement.

[0008] Further, S4) further comprises judging whether the user meets the exclusion item indicators of executing the orderly power utilization, if the user meets any of the exclusion item indicators of the orderly power utilization, then not executing this orderly power utilization; if the user does not meet all of the exclusion item indicators of the orderly power utilization, then scoring each dimension label in the user-level load management label system according to this orderly power utilization, and adding up the scores to obtain a comprehensive score; S5) also includes constructing a load management strategy for orderly electricity consumption scenarios. The specific steps for the load management strategy for orderly electricity consumption scenarios are as follows. Users are ranked based on the comprehensive score mentioned above. Then, according to the ranking, the ranked users are added to the user list for this orderly power consumption until the total adjustable load exceeds the gap value, thereby selecting a suitable list of participating users.

[0009] Furthermore, in S4), the exclusion criteria for orderly electricity use include industrial and commercial users whose summer and winter loads were both below 700 kW in the previous year, industrial and commercial users with voltage levels of 1 kV and below, temporary electricity users, high-voltage and high-energy-consuming users, landscape lighting users, other industry users whose regulation is only applied to commercial users, and other industry users whose regulation is only applied to industrial users.

[0010] Furthermore, in S2), the load management tagging system also includes a loop-level load management tagging system and an equipment-level load management tagging system; The circuit-level load management labeling system includes basic information dimension labels, electricity consumption characteristic dimension labels, adjustable capability dimension labels, adjustable technical dimension labels, and adjustable economic dimension labels; The device-level load management tagging system includes basic information dimension tags, electricity consumption characteristic dimension tags, adjustable capacity dimension tags, adjustable technical dimension tags, and adjustable economic dimension tags.

[0011] Furthermore, step S5) is followed by step S6), which establishes a load management effectiveness evaluation index system based on the above load management strategy, and then performs strategy effectiveness simulation to evaluate the strategy effectiveness simulation.

[0012] Furthermore, in S6), the strategy effect simulation evaluation includes the estimation of the dynamic adjustability of a single user and the estimation of the execution status of a single user. The process of estimating the dynamic adjustability of a single user is as follows: export the load curve data of a single user during the response period within a specified time, then calculate the average load of the user during the response period, and then calculate the dynamic adjustability of the user based on the user's adjustability ratio. The formula for calculating the dynamic adjustability of a single user is as follows: In the formula, Res This indicates the dynamic adjustability of a single user. P Ri Indicates the most recent [number] times a single user [does something]. i The load of the day, n This indicates the number of days required for a response within a specified timeframe. K For a single user, the adjustable ratio is calculated based on user tags and adjustable capabilities. The process of estimating the execution status of a single user is as follows: the execution status of a single user is calculated based on the user's participation in demand response, the average execution rate of the load, and the average on-time execution rate of the load. The formula for calculating the execution status of a single user is as follows: In the formula, P D This indicates the completion status of a single user's task. R T This indicates the average on-time performance rate of load execution. D R This indicates the level of engagement in responding to a single user's needs. R avg This indicates the average on-time performance rate of the load.

[0013] The present invention also designs a load management system based on user profiles, which is characterized by including a scenario analysis module, a tag management module, a load monitoring module, a user profile module, and a strategy management module; The scenario analysis module is used to analyze demand response and orderly power consumption scenarios in load management scenarios; The tag management module is used to construct a load management tag system based on the scenario analysis results of demand response and orderly electricity use. The load management tag system includes a user-level load management tag system. The user-level load management tag system includes basic information dimension tags, electricity consumption characteristic dimension tags, adjustable capacity dimension tags, adjustable technical dimension tags, adjustable economic dimension tags, and participation willingness dimension tags. The load monitoring module is used to monitor the power grid load. If the demand response activation conditions are met, the module proceeds to the next step based on the size of the demand response gap, the time of occurrence, the duration, and the location of occurrence. If the demand response activation conditions are not met, the module continues to monitor the power grid load. The user profiling module is used to determine whether a user meets the exclusion criteria for participating in the demand response. If a user meets the exclusion criteria, they will not participate in this demand response. If a user does not meet the exclusion criteria, the module will score the user's load management tag system for each dimension based on this demand response and add the scores together to obtain a comprehensive score. The strategy management module is used to construct load management strategies for demand response scenarios. The specific steps of the load management strategy for demand response scenarios are as follows: users are sorted according to the above comprehensive score, and then, according to the ranking, the sorted users are added to the list of users participating in this demand response until the total adjustable load exceeds the gap value, thereby selecting a suitable list of participating users.

[0014] The advantages of this invention are: 1. This invention, through the analysis of load management scenarios, clearly defines the characteristics and boundaries of different load management scenarios. Actual load management scenarios vary significantly due to their nature, duration, and resources. Combining the voluntary nature, short timeliness, and diverse resources of demand response with the mandatory nature, clear resource requirements, and notification characteristics of orderly electricity use, this invention can effectively distinguish the core elements and applicable conditions of different scenarios. This provides accurate scenario basis for subsequent steps such as building a tagging system and creating user profiles, ensuring that subsequent work is highly adapted to the characteristics of actual scenarios, improving the pertinence and effectiveness of load management, and enabling the power system to adopt more practical strategies under different load management scenarios. 2. This invention utilizes a load management tag system that constructs three levels—users, devices, and circuits—each containing multi-dimensional tags. This system enables a comprehensive and detailed characterization of load management-related elements. Actual load management involves a wide variety of objects, and different users, devices, and circuits exhibit significant differences in basic information, electricity consumption characteristics, and regulation capabilities. By combining the tags of each dimension with specific value sources and calculation models, these differences and inherent characteristics can be accurately captured. This effectively provides solid data support and characteristic basis for subsequent user profile construction and strategy research, ensuring that load management work is scientific and targeted from the basic data level, making subsequent load management processes more aligned with actual needs. 3. This invention, by constructing a user profile system and visualization method with seven dimensions, achieves a comprehensive and accurate characterization of user characteristics in load management scenarios. The actual user-side load resources have significant differences in attributes, electricity consumption patterns, and control potential. Moreover, different load management scenarios (such as demand response and orderly electricity use) have different requirements for users. By combining the screening function of exclusion items, the accurate reflection of key user characteristics by each dimension, and the scoring details for different scenarios and diversified visualization methods, it can effectively capture the differences in adaptability, potential, and willingness of different users in load control. This provides key guidance for user screening, priority ranking, and control scheme design in load management strategy formulation, ensuring that users who meet the requirements, have great control potential, and have high willingness are selected in different scenarios, thereby improving the accuracy of load management. 4. This invention constructs a load management strategy for different scenarios, enabling precise control and arrangement for different load management scenarios. Actual load management scenarios are complex and diverse, and demand response and orderly power consumption differ in terms of startup mechanisms and resource allocation. By combining the characteristics of each scenario, specific processes for judging startup conditions, analyzing response resources, and generating user lists are designed, which can effectively adapt to the management needs of different scenarios, accurately select suitable participating users, provide a clear execution path for power grid load control, ensure the efficient implementation of load management measures, and improve the flexibility and reliability of the power system in response to different load conditions. 5. By constructing a multi-dimensional load management evaluation system, this invention achieves a comprehensive and accurate assessment of the implementation effect and overall impact of load regulation. Actual load management involves complex situations such as execution effect, resource utilization, economic impact, and user participation. By combining various rate values ​​of execution, various proportions of resource participation, calculation of economic losses and benefits, and statistical analysis of user participation, this invention can effectively capture the performance and internal correlation of load regulation in different dimensions, providing key basis for the iterative optimization of load management strategies and ensuring that regulation measures are more in line with actual needs. This invention presents a load management method and system based on user profiles, enabling systematic and precise advancement of load management. Addressing issues such as complex user characteristics and insufficient targeted regulation in load management, it first lays the foundation through scenario analysis, then constructs a multi-dimensional tagging system to generate user profiles for typical scenarios, followed by the formation of regulation strategies based on these profiles, and finally achieves iterative optimization of these strategies through an evaluation system. This interconnected approach completes the entire load management process, effectively improving the scientific rigor and effectiveness of load regulation, providing strong support for power grid companies to implement load control, and ensuring the efficient and stable operation of the power system. Attached Figure Description

[0015] Figure 1 This is a flowchart of the load management method based on user profiles according to the present invention; Figure 2 This is a flowchart illustrating the construction process of the user profiling system in this invention; Figure 3 This is a structural block diagram of the load management system based on user profiles in Embodiment 3 of the present invention; Figure 4 This is a schematic diagram of the user profiling module in Embodiment 3 of the present invention; Figure 5 This is a schematic diagram of the strategy management module in Embodiment 3 of the present invention; Figure 6 This is a schematic diagram of the execution evaluation module in Embodiment 3 of the present invention. Detailed Implementation

[0016] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0017] Example 1 like Figure 1 As shown, the present invention provides a load management method based on user profiles, comprising the following steps: S1) Analyze demand response and orderly power consumption scenarios in load management scenarios.

[0018] Scenario analysis includes policy analysis, scenario characteristics, and required resource analysis, specifically: Demand response is not mandatory. Users can voluntarily change their electricity usage patterns based on received price or invitation signals; participation is optional. Demand response typically lasts 2-4 hours, falling under short-term load regulation. Based on preparation time, it can be categorized into real-time demand response (0.5-hour advance notice), intraday demand response (0.5-24-hour advance notice), and day-ahead demand response (more than 24 hours advance notice). Adjustable loads are classified according to their advance notice execution time, as shown in Table 1 below. In practice, intraday demand response is generally the primary method.

[0019] Table 1. Classification of Adjustable Loads by Advance Notice Execution Time Attribute In terms of demand response resources, traditional user load resources include interruptible loads, shiftable loads, and flexible adjustable loads, all of which can participate in demand response. In addition, new demand-side resources such as energy storage, V2G, and distributed generation devices can also participate in demand response.

[0020] Orderly electricity use has a certain degree of mandatory nature. Emergency measures for orderly electricity use mainly cover peak-shifting, rotating shifts, and power rationing to minimize unplanned power outages. Orderly electricity use has relatively clear resource requirements, with specific regulations for the control targets and resource types at each level. Notification is generally given at least one day in advance.

[0021] This invention, through the analysis of load management scenarios, clearly defines the characteristics and boundaries of different load management scenarios. It is understood that actual load management scenarios vary significantly due to their nature, duration, and resources. Combining the voluntary nature, short timeliness, and diverse resources of demand response with the mandatory nature, clear resource requirements, and notification characteristics of orderly electricity use, this invention can effectively distinguish the core elements and applicable conditions of different scenarios. This provides accurate scenario basis for subsequent steps such as building a tagging system and creating user profiles, ensuring that subsequent work is highly adapted to the characteristics of actual scenarios, improving the pertinence and effectiveness of load management, and enabling the power system to adopt more practical strategies under different load management scenarios.

[0022] S2) Based on the scenario analysis results of demand response and orderly electricity use, a load management labeling system is constructed, which includes a user-level load management labeling system.

[0023] The user-level load management tagging system includes 221 tags, such as basic information dimension tags, electricity consumption characteristic dimension tags, adjustable capability dimension tags, adjustable technical dimension tags, adjustable economic dimension tags, and participation willingness dimension tags.

[0024] (1) Basic information dimension tags Basic information mainly includes subordinate information, industry classification, power supply information, and user classification. Subordinate information includes user ID and user name. Industry classification includes industry categories, industrial classification, upstream industries, and downstream industries. Power supply information includes power supply unit, substation area, administrative division, power grid zone, street / industrial park, power grid, transmission section, and power supply voltage level. User classification includes whether the user is a "six-guarantee" user, a "high-voltage" user, an industrial / commercial user, a large-scale enterprise, and whether it is an industrial / commercial user.

[0025] (2) Electricity consumption characteristic dimension labels Electricity consumption characteristics mainly include capacity, power distribution structure, user equipment composition, load characteristics, and production characteristics. Capacity includes contracted capacity, operating capacity, and electricity consumption from the previous year. Power distribution structure includes total number of distribution lines, total distribution voltage level, total number of outgoing lines, number of distribution lines, distribution voltage level, number of outgoing lines, number of high-voltage feeders, high-voltage feeder voltage level, and low-voltage feeders. Equipment composition includes total equipment power, security equipment power, security equipment power percentage, main production equipment power, main production equipment power percentage, auxiliary production equipment power, auxiliary production equipment power percentage, non-production equipment power, and production equipment power percentage. Load characteristics include 72 tags such as the maximum summer load of the past three years, the maximum winter load of the past three years, and the average daily load of the maximum summer load of the past three years. Production characteristics include annual production periods, daily production periods, main products, main production processes, production mechanism models, and factory holidays.

[0026] (3) Adjustable capability dimension labels Adjustable capacity mainly includes total adjustable capacity, adjustable capacity at various time scales, various adjustable resources, and adjustable capacity based on minimizing and maximizing adjustment targets. Total adjustable capacity includes maximum adjustable load, adjustment method, adjustable ratio, advance notice time, adjustable duration, production recovery time, number of adjustable high-voltage circuits, number of adjustable low-voltage circuits, number of adjustable high-voltage feeders, number of adjustable low-voltage feeders, peak-shaving adjustable load (demand response), peak-shifting adjustable load (orderly power consumption), valley-filling adjustable load (demand response), and peak-avoidance adjustable load (orderly power consumption). For users who have not undergone load screening, some of their label values ​​can be calculated through the model. The specific calculation formula is as follows. ① Maximum adjustable load: The user's maximum adjustable load is the portion excluding the security load. Generally, the user's security load accounts for less than 10%, so the user's maximum adjustable load can be estimated using the following formula.

[0027] Maximum adjustable load for users = average operating load over the past 7 days × 90%.

[0028] ② Adjustable Ratio: This tag mainly refers to the reduction ratio under normal generation conditions, and the adjustable ratio in the industry model can be directly adopted. K If industry model ratio data is unavailable, it can be calculated using load curve data. The specific calculation formula is as follows: In the formula, K This indicates the user-adjustable ratio. T imax This indicates that the user has been in the first month of i The maximum load at any given time. T imin This indicates that the user has been in the first month of i The minimum load at any given time.

[0029] ③ Peak-shaving adjustable load: Calculated based on the average load and adjustable ratio during the user's peak-shaving period, using the following formula: In the formula, P p This indicates peak-shaving adjustable load. P it Indicates user i The load at time t (peak time), K This indicates the user-adjustable ratio. T Indicates the duration of load regulation.

[0030] ④ Adjustable load during peak periods: This is calculated based on the difference between the average peak periods of the past 5 days for each user, using the following formula: In the formula, P p This indicates an adjustable load for filling valleys. P M This indicates the user's maximum load during off-peak hours over the past 5 days. P it Indicates user i The load at time t (the trough time), T Indicates the duration of load regulation.

[0031] Various adjustable resources include rigid adjustable loads, flexible adjustable loads, industrial adjustable loads, air conditioning adjustable loads, main production adjustable loads, auxiliary production adjustable loads, and non-production adjustable loads. If the tag values ​​for user adjustable loads T1-T6 are missing, they can be estimated based on existing data. First, select 5 companies in the same industry with the closest electricity consumption in the previous year from the system.

[0032] ⑤ The formulas for calculating adjustability at different time scales are: Ti Adjustable Load = Average User Operating Load × Average Adjustment Ratio of Similar Enterprises In the formula, the value of i is 1, 2, ..., 6.

[0033] ⑥ The formula for calculating the maximum / minimum target adjustability is: Adjustable capacity = Average load during user control period × Model control ratio ⑦ Advance notification time, adjustable duration, and production recovery time are directly taken from the relevant parameters in the industry model.

[0034] (4) Adjustable technical dimension labels Adjustability includes both monitorability and remote controllability. Both are comprised of the number of loops, loop percentage, adjustable load, and load percentage. The tag values ​​for the number of loops and adjustable load are obtained through user investigation, while the tag values ​​for the loop percentage and the monitorable / controllable load percentage are primarily obtained through model calculation. The specific calculation formulas are as follows: ①Proportion of monitorable circuits = Number of monitorable circuits / Total number of circuits ② Controllable loop percentage = Number of controllable loops / Total number of loops ③ Measurable load percentage = Measurable load / Total load ④ Controllable load percentage = Controllable load / Total load (5) Adjustable economic dimension label Adjustable economic efficiency includes overall indicators, sub-indicators, and other operational information. Overall indicators include electricity regulation cost per unit of electricity, output value per unit of electricity, production cost per unit of electricity, and the electricity regulation / production cost ratio. Sub-indicators include the previous year's total output, previous year's total output value, previous year's total production cost, total regulation cost, previous year's total human resource cost, previous year's total working hours, human resource cost unit price compensation coefficient, quantity of lost materials, unit price of lost materials, quantity of lost energy, unit price of lost energy, product sales unit price, fulfillment cost unit price coefficient, and product sales profit coefficient. Other operational information includes the average output value (ten thousand yuan) of the past three years, the average output (tons) of the past three years, land area (square meters), and total number of employees. The calculation formula for the tags requiring model calculation is as follows: ① Adjusting total cost The adjusted total cost is the sum of six items: increased human resource costs, production material loss costs, energy loss costs, production equipment depreciation costs, increased fulfillment costs, and reduced sales profit costs. The calculation formula is as follows: In the formula, E T总 Indicates the adjustment of total cost. E Ti This indicates costs related to increased human resources, production material losses, energy consumption, production equipment depreciation, increased fulfillment costs, and decreased sales profits. i Indicates the first i Adjustment costs.

[0035] ②Electricity regulation cost The cost per kilowatt-hour for regulation is the sum of the total regulation cost and the maximum adjustable capacity of the regulated object (maximum adjustable load). P Tmax With adjustable duration T T The ratio of the product of the two products is calculated using the following formula: In the formula, E TD Indicates the cost of regulating electricity per kilowatt-hour. E T总 Indicates the total adjustment cost. P Tmax Indicates the maximum adjustable load. T TIndicates the duration of adjustment. For users whose total cost of adjustment cannot be determined without conducting user surveys, the value per kilowatt-hour can be used as an approximation.

[0036] ③Energy output per kilowatt-hour The value per kilowatt-hour of electricity output is the ratio of the total output value of the regulated entity to its total annual electricity consumption. The larger the value, the greater the impact of regulation on the economy; conversely, the smaller the value, the smaller the impact of regulation on the economy. The calculation formula is as follows: In the formula, E CD Indicates the value of electricity generated per kilowatt-hour. E C总 It represents the total output value of the object being regulated. W Y总 This indicates the user's total electricity consumption for the previous year.

[0037] For users who have not been investigated, their electricity output value can be estimated by using the previous year's gross domestic product and the previous year's total electricity consumption of the user's industry.

[0038] ④ Production cost per kilowatt-hour The production cost per kilowatt-hour (kWh) is the cost of manpower, materials, and equipment consumed by the object. The calculation formula is as follows: In the formula, E PD This represents the production cost per kilowatt-hour. W Y总 This indicates the user's total electricity consumption in the previous year. Q Y总 This represents the user's total output value for the previous year. g This represents the user's sales profit from the previous year.

[0039] For users who have not conducted investigations, estimates can be made using data from the previous year's statistical yearbook of their industry.

[0040] (6) Participation willingness dimension label Participation intentions mainly include whether registration has been completed in the trading center, whether demand-side response resources have been entered into the database, whether a demand response agreement has been signed, the value of demand response contracts, the number of responses in the past year, the maximum response volume in the past year, and the historical maximum response value.

[0041] The load management labeling system also includes a loop-level load management labeling system and an equipment-level load management labeling system.

[0042] The device layer includes multiple tags such as basic information dimension, power consumption characteristic dimension, adjustable capability dimension, adjustable technical dimension, and adjustable economic dimension.

[0043] (1) Basic information dimension tags The basic information includes subordinate information, equipment classification, and quantity information. Subordinate information includes equipment number, equipment name, user account number, process number, and circuit number; equipment classification covers equipment type, equipment load type, equipment energy consumption type, equipment production type, and equipment resource type; and quantity information is the number of equipment units.

[0044] (2) Electricity consumption characteristic dimension labels Electricity consumption characteristics include equipment parameters and operating characteristics. Among them, equipment parameters include equipment voltage level, rated power of a single unit, average operating power, and maximum output power; operating characteristics include operating time, morning peak load, mid-peak load, and evening peak load.

[0045] (3) Adjustable capability dimension labels Adjustability includes maximum adjustable load, adjustment method, adjustable ratio, advance notice time, adjustment duration, and production recovery time.

[0046] (4) Adjustable technical dimension labels Adjustable technology includes whether it is connected to the grid, the type of switch, whether it can be monitored, and whether it can be remotely controlled.

[0047] (5) Adjustable economic dimension label Adjustable economic efficiency includes overall indicators and sub-indicators. The overall indicator includes the cost per kilowatt-hour for energy regulation; the sub-indicators consist of the total value of equipment assets, the total annual electricity consumption of the equipment, the total annual output of the equipment, the sales price of the products produced by the equipment, the cost price of the products produced by the equipment, the total annual human resource cost of the equipment, the total annual operating hours of the equipment, the total number of start-ups and shutdowns throughout the equipment's life cycle, the equipment's maintenance power, the compensation coefficient for the unit price of human resource cost, the quantity of lost materials, the unit price of lost materials, the quantity of energy lost, the unit price of energy lost, the unit price coefficient of performance cost, and the product sales profit coefficient.

[0048] The circuit-level load management labeling system includes basic information dimension labels, electricity consumption characteristic dimension labels, adjustable capacity dimension labels, adjustable technical dimension labels, and adjustable economic dimension labels.

[0049] (1) Basic information dimension tags The basic information includes subordinate information, classification information, and quantity information. Subordinate information includes circuit number, circuit name, user account number, and process number. Equipment classification is further subdivided into circuit type, circuit distribution type, circuit load type, circuit energy consumption type, circuit production type, and circuit resource type. Quantity information indicates the number of connected devices.

[0050] (2) Electricity consumption characteristic dimension labels Electricity consumption characteristics include circuit parameters and operating characteristics. Circuit parameters include circuit voltage level, circuit capacity, average circuit power, and maximum circuit power; operating characteristics include operating time, morning peak load, mid-peak load, and evening peak load.

[0051] (3) Adjustable capability dimension labels Adjustability includes maximum adjustable load, adjustment method, adjustable ratio, advance notice time, adjustment duration, and production recovery time.

[0052] (4) Adjustable technical dimension labels Adjustable technology includes switch type, whether it is connected to the grid, whether it can be monitored, and whether it can be remotely controlled.

[0053] (5) Adjustable economic dimension label Adjustable economic efficiency includes overall indicators and sub-indicators. The overall indicator includes the cost per kilowatt-hour for energy regulation; the sub-indicators include the total value of equipment assets, the total annual electricity consumption of the equipment, the total annual output of the equipment, the sales price of the products produced by the equipment, the cost price of the products produced by the equipment, the total annual human resource cost of the equipment, the total annual operating hours of the equipment, the total number of start-ups and shutdowns throughout the equipment's life cycle, the equipment's maintenance power, the compensation coefficient for the unit price of human resource cost, the quantity of lost materials, the unit price of lost materials, the quantity of lost energy, the unit price of lost energy, the unit price coefficient of performance cost, and the product sales profit coefficient.

[0054] This invention utilizes a load management tagging system that constructs three levels—users, devices, and circuits—each containing multi-dimensional tags, to achieve a comprehensive and detailed characterization of load management-related elements. It is understandable that actual load management involves a wide variety of objects, and different users, devices, and circuits exhibit significant differences in basic information, electricity consumption characteristics, and regulation capabilities. By combining the tags of each dimension with specific value sources and calculation models, these differences and inherent characteristics can be accurately captured. This effectively provides solid data support and characteristic basis for subsequent user profile construction and strategy research, ensuring that load management work is scientific and targeted from the basic data level, making subsequent load management processes more aligned with actual needs.

[0055] S3) Monitor the grid load. If the demand response activation conditions are met, proceed to step S4 based on the size of the demand response gap, the time of occurrence, the duration, and the location of occurrence. If the demand response activation conditions are not met, continue monitoring the grid load.

[0056] Preferably, step S3) further includes monitoring the power grid load; if the conditions for starting orderly power consumption are met, then proceed to step S4 based on the size of the orderly power consumption gap, the time of occurrence, the duration, and the location of occurrence; if the conditions for starting orderly power consumption are not met, then continue monitoring the power grid load.

[0057] Specifically, the conditions for initiating demand response or orderly power consumption are determined through factors such as frequency deviation, voltage exceeding limits, overload of transmission / distribution equipment, load supply-demand gap prediction, and emergency power supply instructions. This part is prior art and will not be described in detail here.

[0058] S4) Determine whether a user meets the exclusion criteria for participating in demand response. If a user meets any of the exclusion criteria for demand response, they will not participate in this demand response. If a user does not meet all the exclusion criteria for demand response, then the user-level load management tag system will be scored according to this demand response, and the scores will be added together to obtain a comprehensive score.

[0059] Specifically, the exclusion criteria for demand response include not being in the demand area, not being in the target industry, being a user of the "six guarantees" (a system for ensuring basic living needs, market entities, food and energy security, and food and energy security), and not meeting the maximum adjustable load requirements.

[0060] Preferably, S4) further includes judging whether the user meets the exclusion criteria for orderly power consumption. If the user meets any of the exclusion criteria for orderly power consumption, then orderly power consumption will not be performed this time. If the user does not meet all the exclusion criteria for orderly power consumption, then the user-level load management tag system will be scored according to the orderly power consumption this time, and the scores will be added together to obtain a comprehensive score.

[0061] Based on the various dimensions of the user-level load management tagging system, "exclusion items" are added to form a user profile system. The user characteristic information represented by each aspect of the user profile system is as follows: ① Exclusion criteria: Used to remove users who do not meet the requirements for participating in demand response or the corresponding round of orderly electricity use; ②Basic information: Used to determine whether a user is a priority control target; ③ Electricity consumption characteristics: used to determine whether the user's electricity consumption period falls within the user's normal production electricity consumption period during the control period; ④ Adjustability: Used to determine the load that can be reduced or increased when the user performs adjustments; ⑤ Adjustable technology: used to determine whether the user has the ability to monitor and remotely control; ⑥ Adjustable economics: Used to analyze the income and expenditure of users participating in regulation, and can provide a basis for the formulation of subsidy standards; ⑦ Willingness to participate: This reflects the strength of users' willingness to participate in demand response or orderly electricity use, and is dynamically updated mainly based on users' historical participation in demand response.

[0062] Specifically, when scoring the various dimensions of the user-level load management tag system, the scores of each dimension of the user are displayed intuitively through user profile scoring tables, multi-dimensional images of user profiles, and descriptive text of user profiles.

[0063] The user profile scoring table primarily displays a user's scores across different dimensions in a tabular format, providing a clear understanding of the user's ability and willingness to participate in load regulation. The table scores users based on fundamental information, electricity usage characteristics, adjustability, adjustability technology, adjustability economy, and willingness to participate. The score for each dimension depends mainly on the corresponding tag value. The score for each tag in the table is related to factors such as the user's industry and load management scenario; the specific calculations differ depending on the scenario.

[0064] First, for demand response scenarios: Exclusion criteria are mainly used to remove users who do not meet the conditions for participating in demand response. Exclusion criteria for demand response include not being in the demand area, not being in the target industry, being a user of the "six guarantees" (a government-mandated service for the people in need of insurance and taxation), and not meeting the maximum adjustable load requirements.

[0065] The basic information dimension is worth 20 points, including two indicators: "Industry Priority" and "High-Energy-Consuming Industries". The "Industry Priority" indicator is worth 10 points, awarded to users in the chemical raw materials and chemical products manufacturing industry, ferrous metal smelting and rolling processing industry, non-ferrous metal smelting and rolling processing industry, non-metallic mineral products industry, and petroleum processing, coking and nuclear fuel processing industry; 6 points for general industrial users; and 2 points for general commercial users. The "High-Energy-Consuming Industries" indicator is worth 10 points, awarded to users in high-energy-consuming industries such as petrochemicals, chemicals, non-metallic mineral products, steel, and non-ferrous metals; and 0 points for users in other industries.

[0066] The electricity consumption characteristics dimension is worth 20 points, consisting of "Electricity Scale" and "Time Period Matching Degree". ① Electricity Scale Index: Electricity scale includes operating capacity, contracted capacity, and annual electricity consumption, reflecting the user's daily production electricity consumption patterns and macro-load characteristics. The scoring details for this index are as follows: User electricity consumption ≥ industry average electricity consumption, 10 points; otherwise, score = 10 × user's industry consumption / industry average electricity consumption. ② Time Period Matching Degree Index: Time period matching degree reflects the proportion of the user's working hours within the response period; Working hours overlapping with the response period / response period ≥ 80%, 10 points; Working hours overlapping with the response period / response period ≤ 10%, 0 points; otherwise, equal score = 10 × working hours overlapping with the response period / response period.

[0067] The adjustability dimension is worth 20 points, including "peak shaving / valley filling capability" and "peak shaving / valley filling duration". ① Peak shaving / valley filling capability: This evaluates the amount of load that can be reduced or increased by various user-owned rigidly adjustable devices, flexible adjustable devices, distributed generation devices, energy storage devices, and charging piles during demand response periods. The scoring details for this indicator are as follows: Peak shaving / valley filling load ≥ average value of all users in the resource pool, 12 points; otherwise, score = 12 × reduceable load / average value of all users in the resource pool. ② Peak shaving / valley filling duration: This evaluates the duration for which various user resources can sustainably participate in demand response. The scoring details for this indicator are as follows: Duration ≥ demand response control duration, 8 points; otherwise, score = 8 × duration / demand response control duration.

[0068] The adjustable technical dimension is worth 20 points, including: remote control capability and remote monitoring capability. If user equipment can be remotely monitored and controlled, the score is as follows: Score = 10 + 10 × Power of remotely monitored equipment / Total power of all equipment; if only user equipment can be remotely monitored, the score is as follows: Score = 10 × Power of remotely monitored equipment / Total power of all equipment.

[0069] The adjustable economics dimension is worth 20 points and only includes the "adjustable economics" indicator. It measures the economic feasibility of user participation in demand response based on the levelized cost per kilowatt-hour (kWh) of electricity. Levelized cost per kilowatt-hour (kWh): This evaluates the economic loss incurred by a user for each kWh of electricity regulated. The scoring details for this indicator are as follows: Levelized cost per kWh ≥ Levelized subsidy, 0 points; Levelized subsidy per kWh ≥ Levelized cost per kWh ≥ Industry average, 10 points; Other cases, score = 10 × Levelized cost per kWh / Industry average. Referring to local demand response policies, the levelized subsidy standard is generally between 5 and 10 yuan / kWh.

[0070] The participation willingness dimension is worth 20 points, including the "participation willingness level" indicator. If you have already registered at the trading center: 20 points. If you have signed a demand response agreement and participated in demand responses more than 5 times in the past year, the score is also 20 points; if you have signed a demand response agreement and participated in demand responses less than 5 times in the past year, the score is calculated as follows: Score = 10 + 2 × Number of Participations; if none of the above conditions are met (other situations): 0 points.

[0071] For orderly electricity use scenarios: The exclusion criteria are mainly used to remove users who do not meet the requirements for participating in the corresponding round of orderly electricity use.

[0072] The exclusion criteria for orderly electricity use include: industrial and commercial users whose summer and winter loads in the previous year were both below 700 kilowatts, industrial and commercial users with voltage levels of 1 kV and below, temporary electricity users, high-energy-consuming and high-emission users (mainly referring to high-energy-consuming and high-emission industrial users), landscape lighting users, other industry users that are only regulated for commercial users, and other industry users that are only regulated for industrial users.

[0073] The basic information dimension is worth 20 points, with specific scores as follows: ① Level I: High-voltage and high-power users, 20 points; temporary power users or landscape lighting users, 18 points; industrial high-voltage users, 16 points; commercial high-voltage users, 14 points; ② Level II: High-voltage and high-power users, 20 points; temporary power users or landscape lighting users, 18 points; industrial high-voltage users, 16 points; commercial high-voltage users, 14 points; ③ Level III: Industrial high-voltage users, 20 points; commercial high-voltage users, 18 points; landscape lighting users, 16 points; ④ Level IV: Industrial high-voltage users, 20 points; commercial high-voltage users, 18 points; commercial low-voltage users, 16 points; ⑤ Level V: Commercial high-voltage users, 20 points; commercial low-voltage users, 16 points; ⑥ Level VI: High-voltage and high-power users, 20 points; industrial high-voltage users, 18 points; industrial low-voltage users, 16 points.

[0074] The electricity consumption characteristic dimension is worth 20 points, including annual electricity consumption, the previous year's maximum load, and time period matching degree. Specifically: ① Annual electricity consumption: reflects the user's total electricity consumption in the previous year. The scoring details are as follows: User electricity consumption ≥ industry average electricity consumption, 8 points; otherwise, score = 8 × user's industry consumption / industry average electricity consumption. ② Previous year's maximum load: reflects the user's maximum load in summer and winter of the previous year. The scoring details are as follows: User's maximum load ≥ industry average maximum load, 8 points; otherwise, score = 8 × user's maximum load / industry average maximum load. ③ Time period matching degree: Time period matching degree reflects the proportion of the user's working hours within the response period. ≥80% overlap between working hours and response period / response period, 4 points; ≤10% overlap between working hours and response period / response period, 0 points; otherwise, equal score = 4 × overlap between working hours and response period / response period.

[0075] The adjustable capability dimension is worth 20 points, including adjustable capability and control duration. If the control duration is greater than or equal to the orderly power consumption control duration, 8 points are awarded; otherwise, the score = 8 × control duration / orderly power consumption control duration. If the adjustable capability of the user's orderly power consumption level K (K=I,Ⅱ,…, Ⅵ) is greater than the industry average, 12 points are awarded; otherwise, the score = 12 × adjustable capability of level K / industry average adjustable capability of level K.

[0076] The adjustable technical dimension is worth 20 points, including: remote control capability and remote monitoring capability. If user equipment can be remotely monitored and controlled, the score is as follows: Score = 10 + 10 × Power of remotely monitored equipment / Total power of all equipment; if only user equipment can be remotely monitored, the score is as follows: Score = 10 × Power of remotely monitored equipment / Total power of all equipment.

[0077] The adjustable economic dimension is worth 20 points, with only the "adjustable economic" indicator. The cost per kilowatt-hour (kWh) of electricity regulation evaluates the economic loss incurred by a user for each kWh of electricity regulated. The scoring details for this indicator are as follows: 0 points if the kWh regulation cost ≥ kWh subsidy; 10 points if the kWh subsidy ≥ kWh regulation cost ≥ industry average; otherwise, score = 10 × kWh regulation cost / industry average.

[0078] The participation willingness dimension is worth 20 points, including the "participation willingness level" indicator. If you have already registered at the trading center: 20 points; if you have signed a demand response agreement and participated in demand responses more than 5 times in the past year, the score is also 20 points; if you have signed a demand response agreement and participated in demand responses less than 5 times in the past year, the score is calculated as follows: Score = 10 + 2 × Number of Participations; if none of the above conditions are met (other situations): 0 points.

[0079] Multidimensional user profile images refer to the use of graphics to intuitively display the scores of six dimensions: basic user information, electricity consumption characteristics, adjustability, adjustability technology, adjustability economy, and willingness to participate.

[0080] User profile descriptions are textual descriptions of a user's core information, which includes six dimensions: basic user information, electricity usage characteristics, adjustability, adjustability technology, adjustability cost, and willingness to participate.

[0081] This invention, by constructing a seven-dimensional user profile system and visualization method, achieves a comprehensive and accurate characterization of user features in load management scenarios. It is understood that actual user-side load resources vary significantly in attributes, electricity consumption patterns, and control potential. Furthermore, different load management scenarios (such as demand response and orderly power consumption) have different requirements for users. By combining the filtering function of exclusion criteria, the accurate reflection of key user characteristics across various dimensions, and the scenario-specific scoring rules and diverse visualization methods, this invention effectively captures the adaptability, potential, and willingness differences of different users in load control. This provides crucial guidance for user selection, prioritization, and control scheme design in load management strategy formulation, ensuring that users who meet the requirements, have high control potential, and high willingness are selected in different scenarios, thereby improving the accuracy of load management.

[0082] S5) Construct a load management strategy for the demand response scenario. The specific steps for constructing a load management strategy for the demand response scenario are as follows: Figure 2 As shown, Users are ranked based on the comprehensive scores mentioned above. Then, according to the ranking, users are sequentially added to the list of users participating in this demand response, until the total adjustable load exceeds the shortfall value, thus selecting a suitable list of participating users. This final selection of a suitable list of participating users is a key component of this load management strategy.

[0083] Preferably, S5) further includes constructing a load management strategy for an orderly electricity consumption scenario. The specific steps of the load management strategy for an orderly electricity consumption scenario are as follows: Users are ranked based on the comprehensive score mentioned above. Then, according to the ranking, the ranked users are added to the user list for this orderly power consumption until the total adjustable load exceeds the gap value, thereby selecting a suitable list of participating users.

[0084] Preferably, users are sorted in descending order of comprehensive score, and then listed in descending order of comprehensive score in the user list for this demand response or orderly power consumption, until the total adjustable load exceeds the gap value, thereby selecting a suitable user list to participate.

[0085] Step S5 is followed by step S6), which establishes a load management effectiveness evaluation index system based on the above load management strategy, and then performs strategy effectiveness simulation to evaluate the strategy effectiveness simulation.

[0086] Specifically, the load management effectiveness evaluation index system includes implementation status, resource participation status, economic evaluation indicators, and user participation status.

[0087] The execution status includes individual users. ti Real-time load execution rate, average user load execution rate, average user load execution on-time rate, overall execution rate, and overall execution on-time rate.

[0088] single user ti Real-time load execution rate: refers to ti The ratio of the difference between the user's baseline load and the user's actual load at any given time to the user's planned load reduction is calculated using the following formula: In the formula, Indicates the first ti The target load execution rate at any given time. User ti Baseline load at any given time User ti Actual load at all times This is a user plan to reduce load.

[0089] In the formula and It can be exported through the marketing system. It can be obtained by averaging the user's load data from the previous 5-7 days.

[0090] Average User Load Execution Rate: This refers to the average user load execution rate during the load control period. The calculation formula is as follows: In the formula, R avg This indicates the average user load fulfillment rate. Indicates the first ti The target load execution rate at any given time. T Indicates the duration of load regulation.

[0091] User average load on-time performance rate: refers to the ratio of the user's actual effective response time to the target response time, calculated as follows: In the formula, R T This indicates the average on-time performance rate per user load. T U This refers to the effective response time of the user, which in this invention refers to the period during which the execution completion rate exceeds 80%. T C To adjust the total duration.

[0092] Overall execution rate: This refers to the average execution rate of all users participating in this regulation. The specific calculation formula is as follows: In the formula, R A Indicates the overall implementation rate. Indicates the first i Average load fulfillment rate per user M This indicates the number of users participating in this regulation.

[0093] Overall On-Time Performance Rate: This refers to the average on-time performance rate of all users participating in this regulation. The specific calculation formula is as follows: In the formula, R AT Indicates the overall on-time execution rate. R Ti Indicates the first i Average on-time performance per user's load. M represents the number of users participating in this regulation.

[0094] The resource participation information is used to analyze the utilization of various resources during load regulation, including the proportion of rigidly adjustable resources, the proportion of flexibly adjustable resources, and the proportion of air conditioning adjustable resources.

[0095] Ratio of rigidly adjustable resources: This refers to the proportion of rigidly adjustable resources among the resources involved in this regulation. The calculation formula is as follows: In the formula, P S This indicates the proportion of rigidly adjustable resources. S GThis represents the rigid resource participation value, which can be obtained by statistically analyzing each participating user's tag, adjustable capacity, and rigid adjustable load. S A This indicates the total pressure reduction in this round of regulation.

[0096] The proportion of flexible and adjustable resources: refers to the proportion of flexible and adjustable resources among the resources involved in this regulation. The calculation formula is as follows: In the formula, P S This indicates the proportion of flexible and adjustable resources. S R The flexible resource participation value can be obtained by statistically analyzing each participating user's tag, adjustable capacity, and flexible adjustable load. S A This indicates the total pressure reduction in this round of regulation.

[0097] Air conditioning adjustable resource ratio: This refers to the proportion of air conditioning adjustable resources among the resources involved in this regulation. The calculation formula is as follows: In the formula, P S This indicates the proportion of adjustable resources available for air conditioning. S k This is the air conditioning resource participation value, which can be obtained by statistically analyzing each participating user's tag, adjustable capacity, and adjustable air conditioning load. S A This indicates the total pressure reduction in this round of regulation.

[0098] The economic evaluation indicators include user-controlled economic losses, user-controlled economic income, and user-controlled economic profit rate.

[0099] User-managed economic losses: refers to the economic losses incurred by users participating in this regulation, calculated using the following formula: In the formula, Cs represents the economic loss caused by user intervention. K S This represents the user's electricity consumption control cost, derived from the user tag - adjustable economy. R avg This indicates the average user load fulfillment rate. P UThis indicates the response capacity declared by the user. T C To adjust the total duration.

[0100] User-managed economic income: refers to subsidies received by users for participating in economic regulation, and its calculation formula is as follows: In the formula, C I This indicates that users can regulate their economic income. Ks represents the user's electricity consumption control cost, derived from the user tag - adjustable economy. R avg This indicates the average user load fulfillment rate. P U This indicates the response capacity declared by the user. Kc This is the subsidy coefficient, and its value is mainly based on policy documents issued by local government departments.

[0101] User-controlled economic profit rate: This measures the relationship between user participation in regulation and their income and expenditure. The calculation formula is as follows: In the formula, R CP This indicates that users adjust the economic profit rate. C I This indicates that users can regulate their economic income. Cs This indicates the economic losses incurred by users in controlling their spending.

[0102] User engagement: Evaluate the frequency of individual user participation in demand response and orderly electricity use, as well as the average engagement of all invited users.

[0103] The user participation data includes demand response participation, orderly electricity consumption participation, overall demand response participation, and overall orderly electricity consumption participation.

[0104] Demand Response Engagement: Measures the degree of user participation in demand response activities, calculated using the following formula: In the formula, D R Indicates the level of participation in demand response. Indicates the number of times the demand response was participated in. This indicates the number of times a request for a response has been made.

[0105] Orderly Electricity Consumption Participation: This measures the degree to which users participate in orderly electricity consumption activities. The calculation formula is as follows: In the formula, D E Indicates the degree of orderly electricity consumption participation. Indicates the number of times participants engaged in orderly electricity use. This indicates the number of times an orderly electricity usage invitation has been made.

[0106] Overall Engagement with Demand Response: Measures the average engagement of all invited users, calculated using the following formula: In the formula, D RA Indicates overall participation in demand response. D Ri Indicates the first i The level of user participation in demand response. M This indicates the number of users who requested a response.

[0107] Overall participation in orderly electricity use: This measures the average participation of all invited users, calculated using the following formula: In the formula, D EA Indicates the overall participation rate in orderly electricity use. D Ei Indicates the first i The degree of participation of individual users in orderly electricity use. M represents the number of users invited to participate in the orderly electricity consumption program.

[0108] Specifically, the strategy effectiveness simulation evaluation includes estimating the dynamic adjustability of individual users and estimating the execution status of individual users.

[0109] The process for estimating the dynamic adjustability of a single user is as follows: Extracting the near-term value of a single user... n The load curve data during the response period is used to calculate the average load of the user during the response period, and then the dynamic adjustable capacity of the user is calculated based on the adjustable ratio of the user. The formula for calculating the dynamic adjustability of a single user is as follows: In the formula, Res This indicates the dynamic adjustability of a single user. P Ri Indicates the most recent [number] times a single user [does something]. i The load of the day, n This indicates the number of days required for a response within a specified timeframe. K The adjustable ratio for a single user is calculated based on user tags and adjustable capabilities.

[0110] If the user's dynamic adjustable capacity is higher than the declared response capacity, the calculation will be based on the declared value; if the dynamic adjustable capacity is less than the declared value, the estimation will be based on the dynamic adjustable capacity.

[0111] The process for estimating the execution status of a single user is as follows: the execution status of a single user is calculated based on the user's participation in demand response, the average execution rate of the load, and the average on-time execution rate of the load. The formula for calculating the execution status of a single user is as follows: In the formula, P D This indicates the completion status of a single user's task. R T This indicates the average on-time performance rate of load execution. D R This indicates the level of engagement in responding to a single user's needs. R avg This indicates the average on-time performance rate of the load.

[0112] This invention achieves accurate measurement of the actual execution effect when users participate in load regulation through a step-by-step execution effect simulation process. It is understood that the actual load regulation capacity of users is affected by various factors such as historical data, adjustable ratios, and participation performance, resulting in complex situations and individual differences. By combining scientific estimation of the dynamic adjustable capacity of individual users, comprehensive calculation of execution effectiveness, and comparison with the pre-regulation load baseline, the invention effectively captures the differences in actual performance and effects of different users during regulation, providing a reliable basis for evaluating the actual effectiveness of load regulation. Furthermore, by constructing a multi-dimensional load management evaluation system, a comprehensive and accurate assessment of the implementation effect and overall impact of load regulation is achieved. It is understood that actual load management involves complex situations such as execution effectiveness, resource utilization, economic impact, and user participation. By combining various rate values ​​of execution effectiveness, various proportions of resource participation, calculation of economic losses and gains, and statistical analysis of user participation, the invention effectively captures the performance and inherent correlation of load regulation in different dimensions, providing key basis for the iterative optimization of load management strategies and ensuring that regulation measures are more aligned with actual needs.

[0113] Example 2 The present invention also designs a load management system based on user profiles, which executes the above-mentioned load management method based on user profiles, including a scenario analysis module 1, a tag management module 2, a load monitoring module 3, a user profile module 4, and a strategy management module 5.

[0114] The scenario analysis module 1 is used to analyze demand response and orderly power consumption scenarios in load management scenarios.

[0115] The tag management module 2 is used to construct a load management tag system based on the scenario analysis results of demand response and orderly electricity use. The load management tag system includes a user-level load management tag system. The user-level load management tag system includes basic information dimension tags, electricity consumption characteristic dimension tags, adjustable capability dimension tags, adjustable technical dimension tags, adjustable economic dimension tags, and participation willingness dimension tags.

[0116] The load monitoring module 3 is used to monitor the power grid load. If the demand response activation conditions are met, the module proceeds to the next step based on the size of the demand response gap, the time of occurrence, the duration, and the location of occurrence. If the demand response activation conditions are not met, the module continues to monitor the power grid load.

[0117] The user profiling module 4 is used to determine whether a user meets the exclusion criteria for participating in demand response. If a user meets any of the exclusion criteria for demand response, the user will not participate in this demand response. If a user does not meet all the exclusion criteria for demand response, the user will be scored on each dimension of the load management tag system based on this demand response, and the scores will be added together to obtain a comprehensive score.

[0118] The strategy management module 5 is used to construct a load management strategy for demand response scenarios. The specific steps of the load management strategy for demand response scenarios are as follows: users are sorted according to the above comprehensive score, and then, according to the ranking, the sorted users are sequentially included in the list of users participating in this demand response until the total adjustable load exceeds the gap value, thereby selecting a suitable list of participating users.

[0119] Example 3 This invention also designs a user profile-based load management system, which executes the aforementioned user profile-based load management method, including an account registration and login module, a tag management module, a user profile module, a policy management module, an execution evaluation module, and an information notification module, such as... Figure 3 As shown.

[0120] The account registration and login module is used for administrators to register and log in to the load management system. Specifically, administrators log in using an account and password provided by the power grid company; electricity customer registration includes filling in an account, password, identity, basic customer information, and a participation intention form, whereby the basic customer information includes the electricity user number, legal representative information, company account, and business-related information.

[0121] The tag management module is used by administrators to edit, add, remove, publish, and withdraw multiple tags at the user, loop, and device levels, thereby achieving full lifecycle management of tags.

[0122] The user profile module is used to evaluate whether users meet the conditions for participating in demand response or orderly electricity use in the corresponding round, as well as the scores of users in various dimensions, and to display the scores intuitively. Then, users are sorted from high to low according to the comprehensive score of each user profile, and the enterprise list menu bar is listed.

[0123] Specifically, the enterprise user profile is used to analyze basic information, electricity consumption characteristics, adjustability, adjustability technology, adjustability economy, and willingness to participate, and to create a graph based on the analysis results. Additionally, the enterprise user profile includes a two-dimensional visualization map of the enterprise's location, used for positioning and obtaining location tags on the map. The user profile module in this embodiment is as follows: Figure 4 As shown.

[0124] The strategy management module is used to generate load management strategies for demand response and orderly power consumption scenarios, and to view the load management strategy generation information of each enterprise.

[0125] Specifically, the load management strategy generation information includes scenario settings and strategy settings. The scenario settings are used to configure the strategy execution area, admission conditions, and priority; the strategy settings are used to configure the load management measures, type, level, and gap parameters of the strategy, thereby generating the load management strategy. The strategy management module in this embodiment is as follows: Figure 5 As shown.

[0126] The execution evaluation module is used to combine load management strategies with user tags and load data to simulate the strategy effects, establish a load management effect evaluation index system, evaluate the strategy effect simulation, and output evaluation information. The execution evaluation module in this embodiment is as follows: Figure 6 As shown.

[0127] The information notification module is used by administrators to send load management strategies, strategy effect simulations, and strategy effect evaluation information to the enterprises receiving the notification. Administrators can compose notifications through the text box, select the enterprises that need to receive the notification in the recipient field, or upload scanned documents to send the notification, and then click the send button to send it.

[0128] The load management system based on user profiles in this invention corresponds to the aforementioned load management method based on user profiles. Therefore, any content in the load management system based on user profiles in this invention that is not specifically described, including but not limited to functional definitions, working principles, and technical effects, can be referred to the aforementioned load management method based on user profiles. This text will not elaborate further on these aspects.

[0129] This invention presents a load management method and system based on user profiles, enabling systematic and precise advancement of load management. Addressing issues such as complex user characteristics and insufficient targeted regulation in load management, it first lays the foundation through scenario analysis, then constructs a multi-dimensional tagging system to generate user profiles for typical scenarios, followed by the formation of regulation strategies based on these profiles, and finally achieves iterative optimization of these strategies through an evaluation system. This interconnected approach completes the entire load management process, effectively improving the scientific rigor and effectiveness of load regulation, providing strong support for power grid companies to implement load control, and ensuring the efficient and stable operation of the power system.

[0130] In the embodiments provided in this application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code, or any suitable combination thereof. For hardware implementation, the processor may be implemented in one or more of the following: application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, other electronic units designed to implement the functions described herein, or combinations thereof. For software implementation, some or all of the processes of the embodiments may be performed by a computer program instructing the associated hardware. During implementation, the program may be stored in a computer-readable storage medium or transmitted as one or more instructions or code on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. Storage media may be any available medium accessible to a computer. Computer-readable storage media may include, but are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code having the form of instructions or data structures and accessible to a computer.

[0131] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A load management method based on user profiles, characterized in that, Includes the following steps: S1) Analyze demand response and orderly power consumption scenarios in load management scenarios; S2) Based on the scenario analysis results of demand response and orderly electricity use, a load management labeling system is constructed. The load management labeling system includes a user-level load management labeling system. The user-level load management labeling system includes basic information dimension labels, electricity consumption characteristic dimension labels, adjustable capability dimension labels, adjustable technical dimension labels, adjustable economic dimension labels, and participation willingness dimension labels. S3) Monitor the grid load. If the demand response activation conditions are met, proceed to step S4 based on the size of the demand response gap, the time of occurrence, the duration, and the location of occurrence. If the demand response activation conditions are not met, continue monitoring the grid load. S4) Determine whether a user meets the exclusion criteria for participating in demand response. If a user meets any of the exclusion criteria for demand response, they will not participate in this demand response. If a user does not meet all the exclusion criteria for demand response, then the user-level load management tag system will be scored according to this demand response, and the scores will be added together to obtain a comprehensive score. S5) Construct a load management strategy for the demand response scenario. The specific steps for constructing a load management strategy for the demand response scenario are as follows. Users are ranked based on the comprehensive score mentioned above. Then, according to the ranking, the ranked users are added to the list of users participating in this demand response until the total adjustable load exceeds the gap value, thereby selecting a suitable list of participating users.

2. The load management method based on user profiles according to claim 1, characterized in that: S3) also includes monitoring the power grid load. If the conditions for starting orderly power consumption are met, then proceed to step S4 based on the size of the orderly power consumption gap, the time of occurrence, the duration, and the location of occurrence. If the conditions for starting orderly power consumption are not met, then continue monitoring the power grid load.

3. The load management method based on user profiles according to claim 2, characterized in that: In S3), the conditions for starting demand response or orderly power consumption are determined by frequency deviation, voltage over-limit, power transmission / distribution equipment overload, load supply and demand gap prediction, and emergency power supply instructions.

4. The load management method based on user profiles according to claim 1, wherein its features The key feature is that, in S4), the exclusion criteria for demand response include not being in the demand area, not being in the target industry, being a user of the "six guarantees" (a system for ensuring basic living needs and safety), and not meeting the maximum adjustable load requirements.

5. The load management method based on user profiles according to claim 1, wherein... The feature is that: S4) also includes judging whether the user meets the exclusion criteria for orderly power consumption. If the user meets any of the exclusion criteria for orderly power consumption, then orderly power consumption will not be implemented this time; if the user does not meet all the exclusion criteria for orderly power consumption, then the user-level load management label system will be scored according to the orderly power consumption this time, and the scores will be added together to obtain a comprehensive score. S5) also includes constructing a load management strategy for orderly electricity consumption scenarios. The specific steps for the load management strategy for orderly electricity consumption scenarios are as follows. Users are ranked based on the comprehensive score mentioned above. Then, according to the ranking, the ranked users are added to the user list for this orderly power consumption until the total adjustable load exceeds the gap value, thereby selecting a suitable list of participating users.

6. The load management method based on user profiles according to claim 5, wherein its features are as follows: The key feature is that, in S4), the exclusion criteria for orderly electricity use include industrial and commercial users whose summer and winter loads were both below 700 kilowatts in the previous year, industrial and commercial users with voltage levels of 1 kV and below, temporary electricity users, high-voltage and high-energy-consuming users, landscape lighting users, other industry users whose regulation is only applied to commercial users, and other industry users whose regulation is only applied to industrial users.

7. The load management method based on user profiles according to claim 1, characterized in that: In S2), the load management tagging system also includes a loop-level load management tagging system and an equipment-level load management tagging system; The circuit-level load management labeling system includes basic information dimension labels, electricity consumption characteristic dimension labels, adjustable capability dimension labels, adjustable technical dimension labels, and adjustable economic dimension labels; The device-level load management tagging system includes basic information dimension tags, electricity consumption characteristic dimension tags, adjustable capacity dimension tags, adjustable technical dimension tags, and adjustable economic dimension tags.

8. The load management method based on user profiles according to claim 7, characterized in that: Step S5 is followed by step S6), which establishes a load management effectiveness evaluation index system based on the above load management strategy, and then performs strategy effectiveness simulation to evaluate the strategy effectiveness simulation.

9. The load management method based on user profiles according to claim 8, characterized in that: In S6), the strategy effect simulation evaluation includes the estimation of the dynamic adjustability of a single user and the estimation of the execution status of a single user. The process of estimating the dynamic adjustability of a single user is as follows: export the load curve data of a single user during the response period within a specified time, then calculate the average load of the user during the response period, and then calculate the dynamic adjustability of the user based on the user's adjustability ratio. The formula for calculating the dynamic adjustability of a single user is as follows: In the formula, Res This indicates the dynamic adjustability of a single user. P Ri Indicates the most recent [number] times a single user [does something]. i The load of the day, n This indicates the number of days required for a response within a specified timeframe. K For a single user, the adjustable ratio is calculated based on user tags and adjustable capabilities. The process of estimating the execution status of a single user is as follows: the execution status of a single user is calculated based on the user's participation in demand response, the average execution rate of the load, and the average on-time execution rate of the load. The formula for calculating the execution status of a single user is as follows: In the formula, P D This indicates the completion status of a single user's task. R T This indicates the average on-time performance rate of load execution. D R This indicates the level of engagement in responding to a single user's needs. R avg This indicates the average on-time performance rate of the load.

10. A load management system based on user profiles, characterized in that, It includes a scenario analysis module (1), a tag management module (2), a load monitoring module (3), a user profile module (4), and a strategy management module (5); The scenario analysis module (1) is used to analyze demand response and orderly power consumption scenarios in load management scenarios; The tag management module (2) is used to construct a load management tag system based on the scenario analysis results of demand response and orderly electricity use. The load management tag system includes a user-level load management tag system. The user-level load management tag system includes basic information dimension tags, electricity consumption characteristic dimension tags, adjustable capability dimension tags, adjustable technical dimension tags, adjustable economic dimension tags, and participation willingness dimension tags. The load monitoring module (3) is used to monitor the power grid load. If the demand response activation conditions are met, the module proceeds to the next step based on the size of the demand response gap, the time of occurrence, the duration, and the location of occurrence. If the conditions for triggering demand response are not met, continue monitoring the grid load; The user profile module (4) is used to determine whether a user meets the exclusion criteria for participating in the demand response. If a user meets any of the exclusion criteria for the demand response, the user will not participate in this demand response. If a user does not meet all the exclusion criteria for the demand response, the user will be scored according to the various dimensions of the user-level load management tag system based on this demand response, and the scores will be added together to obtain a comprehensive score. The strategy management module (5) is used to construct a load management strategy for the demand response scenario. The specific steps of the load management strategy for the demand response scenario are as follows: users are sorted according to the above comprehensive score, and then, according to the ranking, the sorted users are included in the list of users participating in this demand response until the total adjustable load exceeds the gap value, thereby selecting a suitable list of participating users.

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