Aggregate dynamic interaction method based on auxiliary service and related device

Abstract

The invention provides an auxiliary service-based polymer dynamic interaction method and a related device. The method comprises the following steps of: obtaining energy efficiency data and auxiliary service data corresponding to a target polymer; the target polymer comprises a target sets; constructing a model according to the energy efficiency data and the auxiliary service data to obtain a dynamic interaction model; obtaining power grid required power of a target power grid corresponding to the target polymer in a preset first control period; calculating according to the power grid demand power through the dynamic interaction model to obtain a reference power regulating variable; and performing power adjustment on the target polymer according to the reference power adjustment quantity to ensure that the total power of the target polymer and the power grid demand power are in a power balance state. By interactively adjusting the power of the target polymer, the load change of the power grid can be responded in real time, and the power balance between the user and the power grid is coordinated.

Description

Technical Field

[0001] The present application relates to the technical field of power systems, and in particular to a dynamic interaction method of aggregates based on auxiliary services and related devices. Background Art

[0002] With the large-scale access of distributed power sources in the power system and the diversification of power consumption characteristics of different types of users such as industry, commerce, and residents, the structure and operation of the power system have become more complex. Different types of users and power sources have different power variation characteristics, making it more difficult to control the power balance of the power grid.

[0003] In the existing power system, the interaction between users and the power grid is relatively simple, lacking effective information communication and collaborative control means. Users often passively accept the power supply arrangement of the power grid and are unable to make dynamic adjustments based on their own power consumption characteristics and the real-time needs of the power grid. This not only limits the enthusiasm of users to participate in the optimization of the power system operation, but also affects the overall operating efficiency and stability of the power system.

[0004] Therefore, how to coordinate the power balance between users and the power grid needs to be solved urgently. Summary of the invention

[0005] The embodiments of the present application provide a method and related devices for dynamic interaction of aggregates based on auxiliary services. By constructing a dynamic interaction model, the reference power adjustment amount is calculated according to the power demand of the power grid and the target aggregate power is adjusted. It can respond to changes in the power grid load in real time, avoid power shortage or surplus, and coordinate the power balance between users and the power grid.

[0006] In a first aspect, an embodiment of the present application provides a method for dynamic interaction of aggregates based on auxiliary services, the method comprising: Obtain energy efficiency data and auxiliary service data corresponding to a target aggregate; the target aggregate includes a target set; the target set includes any one of the following: an industrial user set, a commercial user set, a residential user set, and a distributed power source set; a is an integer greater than 1; Building a model based on the energy efficiency data and the auxiliary service data to obtain a dynamic interactive model; Obtaining a grid demand power of a target grid corresponding to the target aggregate within a preset first control period; Calculating according to the power demand of the power grid through the dynamic interaction model to obtain a reference power regulation amount; The target aggregate is power regulated according to the reference power regulation amount to ensure that the total power of the target aggregate is in a power balance state with the power demanded by the power grid.

[0007] In a second aspect, an embodiment of the present application provides an aggregate dynamic interaction device based on auxiliary services, the device comprising a first acquisition module, a construction module, a second acquisition module, a calculation module and an adjustment module, wherein: The first acquisition module is used to acquire energy efficiency data and auxiliary service data corresponding to a target aggregate; the target aggregate includes a target set; the target set includes any one of the following: an industrial user set, a commercial user set, a residential user set, and a distributed power source set; a is an integer greater than 1; The construction module is used to construct a model according to the energy efficiency data and the auxiliary service data to obtain a dynamic interactive model; The second acquisition module is used to acquire the grid demand power of the target grid corresponding to the target aggregate within a preset first control period; The calculation module is used to calculate according to the power demand of the power grid through the dynamic interaction model to obtain a reference power adjustment amount; The regulation module is used to perform power regulation on the target aggregate according to the reference power regulation amount to ensure that the total power of the target aggregate is in a power balance state with the power demanded by the power grid.

[0008] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps of any method in the first aspect of the embodiment of the present application.

[0009] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps described in any method of the first aspect of the embodiment of the present application.

[0010] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in any method of the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0011] By implementing the embodiments of the present application, a dynamic interactive model can be constructed to calculate the reference power adjustment amount and adjust the target aggregate power based on the power demand of the power grid. This model can respond to changes in the power grid load in real time, avoid power shortages or surpluses, and coordinate the power balance between users and the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0013] Figure 1 This is an application scenario diagram of power regulation of a target aggregate provided in an embodiment of the present application; Figure 2 is a composition structure diagram of a target polymer provided in an embodiment of the present application; Figure 3 is a system architecture diagram of a power regulation system provided in an embodiment of the present application; Figure 4 is a structural schematic diagram of an electronic device provided in an embodiment of the present application; Figure 5 It is a flowchart of a dynamic interaction method of an aggregate based on auxiliary services provided in an embodiment of the present application; Figure 6 It is a schematic diagram of a flow chart of calculating a power regulation amount provided by an embodiment of the present application; Figure 7 It is a schematic diagram of a process for adjusting the power regulation amount provided in an embodiment of the present application; Figure 8 It is a functional module composition block diagram of an aggregate dynamic interaction device based on auxiliary services provided in an embodiment of the present application. DETAILED DESCRIPTION

[0014] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0015] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0016] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0017] With the large-scale access of distributed power sources in the power system and the diversification of power consumption characteristics of different types of users such as industry, commerce, and residents, the structure and operation of the power system have become more complex. The power change characteristics of different types of users and power sources are different, which makes the power balance control of the power grid more difficult. In the existing power system, the interaction between users and the power grid is relatively simple, lacking effective information communication and collaborative control means. Users often passively accept the power supply arrangements of the power grid and are unable to make dynamic adjustments based on their own power consumption characteristics and the real-time needs of the power grid. This not only limits the enthusiasm of users to participate in the optimization of the power system operation, but also affects the overall operation efficiency and stability of the power system. Therefore, how to coordinate the power balance between users and the power grid needs to be solved urgently.

[0018] To solve the above problems, the embodiment of the present application provides a dynamic interaction method and related devices of aggregates based on auxiliary services, which obtain energy efficiency data and auxiliary service data corresponding to the target aggregate; the target aggregate includes a target set; the target set includes any one of the following: industrial user set, commercial user set, residential user set, distributed power source set; a is an integer greater than 1; a model is constructed according to the energy efficiency data and the auxiliary service data to obtain a dynamic interaction model; the grid demand power of the target power grid corresponding to the target aggregate within the preset first control cycle is obtained; the reference power adjustment amount is calculated according to the grid demand power through the dynamic interaction model; the power of the target aggregate is adjusted according to the reference power adjustment amount to ensure that the total power of the target aggregate is in a power balance state with the grid demand power. By constructing a dynamic interaction model, calculating the reference power adjustment amount according to the grid demand power and adjusting the target aggregate power, it is possible to respond to grid load changes in real time, avoid power shortages or surpluses, and coordinate the power balance between users and the grid.

[0019] For easier understanding, see Figure 1 , Figure 1This is an application scenario diagram of power regulation of a target aggregate provided in an embodiment of the present application, wherein the target aggregate is a collection of industrial users, commercial users, residential users and distributed power sources, and the target aggregate can provide energy efficiency data, auxiliary service data, power regulation capability and other information to the power regulation system, and can also receive regulation instructions from the power regulation system to adjust its own power; the target power grid is used to supply and distribute electricity, and the target power grid can provide the power regulation system with information such as power demand of the power grid, so that the target aggregate can adjust the power to match the power demand fluctuation of the target power grid; the power regulation system can receive relevant data information from the target aggregate and the target power grid, perform analysis and calculation based on the information, and then issue a power regulation instruction to the target aggregate to achieve a power balance between the total power of the target aggregate and the power demand of the power grid.

[0020] For easier understanding, see Figure 2 , Figure 2 This is a composition structure diagram of a target aggregate provided in an embodiment of the present application, wherein the target aggregate includes an industrial user set, a commercial user set, a residential user set, and a distributed power source set. The industrial user set can be set as I, the commercial user set as C, the residential user set as R, and the distributed power source set as D.

[0021] Among them, the industrial user set includes various industrial enterprises, whose electricity consumption characteristics usually have large power demands, and the electricity consumption period is relatively fixed or has a certain production periodicity, and has high requirements for power supply reliability. For the industrial user set, considering the continuity of its production process and the stability of its electricity load, its basic electricity load can be determined by analyzing the historical electricity consumption data of the industrial user set. , and adjustable power load range In actual production, accurate monitoring and control of power load can be achieved through intelligent transformation of production equipment, such as installing smart meters and controllable switches.

[0022] Among them, the commercial user group includes shopping malls, office buildings, hotels and other commercial places. Their peak electricity consumption is generally concentrated during business hours. Lighting, air conditioning, elevators and other equipment consume a lot of electricity, with obvious daily load fluctuation characteristics, and also have certain requirements for power quality and power supply stability. Since the power load of the commercial user group is greatly affected by business hours and business activities, its power consumption characteristics in different time periods can be analyzed to determine the power load during peak hours. and off-peak hours , and interactive load regulation capabilities For example, shopping malls can optimize the control strategy of the lighting system to reduce the lighting brightness and power load during non-business hours.

[0023] The residential user set refers to residential household users. The electricity consumption behavior of the residential user set is random. The preset probability statistics method can be used to analyze the electricity consumption pattern of the residential user set to determine the average power of different electrical equipment corresponding to the residential user set. (r∈R, j represents the type of electrical equipment) and usage probability , thereby estimating the total electricity load of the residential user group Among them, the historical electricity consumption data of residential user groups can also be collected through the smart home appliance platform to establish a user electricity consumption behavior model in order to more accurately predict the electricity load of residential user groups.

[0024] Among them, the distributed power generation collection includes distributed power generation units such as small solar power generation devices, wind turbines, and biomass power generation equipment. Taking photovoltaic power generation as an example, according to its installed capacity , light intensity G, conversion efficiency , calculate its power generation To improve the efficiency of photovoltaic power generation, an intelligent tracking system can be used to ensure that the photovoltaic panels always maintain the best lighting angle.

[0025] For easier understanding, see Figure 3 , Figure 3 It is a system architecture diagram of a power regulation system provided in an embodiment of the present application, wherein the power regulation system includes a data acquisition module, a dynamic interaction module and a command output module.

[0026] The data acquisition module is responsible for collecting energy efficiency data and auxiliary service data of target aggregates (such as industrial, commercial, residential users and distributed power sources), as well as data such as the power demand of the target power grid within the preset control cycle. For example, it collects information such as the real-time power consumption of industrial users and the power generation of distributed power sources.

[0027] The dynamic interaction module can construct a dynamic interaction model based on the data obtained by the data acquisition module. The dynamic interaction model analyzes the power interaction relationship between the target aggregate and the target power grid, and calculates the reference power adjustment amount according to the power demand of the power grid. For example, according to the changes in the load of the power grid and the characteristics of each user and power source, it is determined how each part should adjust the power.

[0028] Among them, the instruction output module can convert the reference power adjustment amount calculated by the dynamic interaction module into a specific adjustment instruction, and send it to each part of the target aggregate (such as industrial user equipment, distributed power control device, etc.) to guide it to perform power adjustment operations, thereby achieving a balance between the total power of the target aggregate and the power demand of the power grid. In the communication process, it is necessary to ensure the accuracy and timeliness of data transmission. Reliable communication protocols, such as power-specific communication protocols, can be used, and communication data can be encrypted and verified to prevent data transmission errors and malicious tampering. In order to improve the reliability and anti-interference ability of communication, redundant communication links, signal enhancement technology and other means can be used to ensure that adjustment instructions or control instructions can be accurately transmitted to each user and equipment. At the same time, a communication failure emergency plan is established, so that when communication fails, timely measures can be taken to ensure the basic operation of the power system.

[0029] It can be seen that by collecting data from the target aggregate and the target power grid, covering multi-dimensional information such as the electricity consumption characteristics of various users, the power generation of distributed power sources and the demand of the power grid, an accurate and comprehensive data basis is provided for subsequent analysis and decision-making, avoiding regulation deviations caused by missing or inaccurate information; by constructing a dynamic interactive model, the dynamic change characteristics of each subject in the power system (such as the intermittent nature of distributed power sources and user load fluctuations) are fully considered, and the power interaction relationship between the power grid and the aggregate is analyzed in real time to better adapt to the complex and changeable power operation scenarios and improve the scientificity and effectiveness of the power regulation strategy; by calculating the reference power regulation amount through the dynamic interactive model, the regulation potential of each user and power source can be explored, the regulation tasks can be reasonably allocated, and the optimal allocation of power resources among different subjects can be achieved, thereby improving the overall energy utilization efficiency and reducing operating costs.

[0030] Combine the following Figure 4 The electronic device in the embodiment of the present application is described. Figure 4 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application, such as Figure 4 As shown, the electronic device includes one or more processors, a memory, a communication interface and one or more programs, and the processor is communicatively connected with the memory and the communication interface via an internal communication bus.

[0031] Among them, the processor is mainly used for: obtaining energy efficiency data and auxiliary service data corresponding to the target aggregate; the target aggregate includes a target set; the target set includes any one of the following: industrial user set, commercial user set, residential user set, distributed power source set; a is an integer greater than 1; constructing a model according to the energy efficiency data and the auxiliary service data to obtain a dynamic interaction model; obtaining the grid demand power of the target power grid corresponding to the target aggregate within a preset first control cycle; calculating according to the grid demand power through the dynamic interaction model to obtain a reference power adjustment amount; power-adjusting the target aggregate according to the reference power adjustment amount to ensure that the total power of the target aggregate is in a power balance state with the grid demand power.

[0032] The one or more programs are stored in the above-mentioned memory and are configured to be executed by the above-mentioned processor, and the one or more programs include instructions for executing any step in the above-mentioned method embodiment.

[0033] Among them, the processor can be a central processing unit, a general processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a transistor logic device, a hardware component or any combination thereof, which is not specifically limited here. The processor can also be a combination that implements a computing function, such as a combination of one or more microprocessors. The communication unit can be a communication interface, a transceiver, a transceiver circuit, etc., and the storage unit can be a memory. The memory can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories.

[0034] It is understandable that the electronic device may include more or fewer structural elements than those in the above structural block diagram, for example, including a power module, physical buttons, Wi-Fi module, speaker, Bluetooth module, sensor, display module, etc., which are not limited here. It is understandable that the electronic device may be equipped with Figure 3 The system architecture described.

[0035] After understanding the software and hardware architecture of this application, Figure 5 A dynamic interaction method of an aggregate based on auxiliary services in an embodiment of the present application is described. Figure 5 : is a flow chart of a method for dynamic interaction of aggregates based on auxiliary services provided in an embodiment of the present application, which specifically includes the following steps: Step S501, obtaining energy efficiency data and auxiliary service data corresponding to the target aggregate.

[0036] Wherein, the target aggregate includes a target sets; the target set includes any one of the following: an industrial user set, a commercial user set, a residential user set, and a distributed power source set; a is an integer greater than 1.

[0037] The step of obtaining the energy efficiency data and auxiliary service data corresponding to the target aggregate comprises: A1. Obtaining historical electricity consumption data of the target aggregate within a preset time period; A2. Analyze and calculate the historical electricity consumption data to obtain the energy efficiency data; the energy efficiency data includes energy efficiency index data, load forecast data, and energy saving potential data; A3, obtaining an adjustable load corresponding to the target polymer; A4. Calculate the adjustable load according to a preset peak load calculation formula to obtain peak load data; A5. Obtaining the actual grid frequency and the rated frequency of the target grid; A6. Determine a frequency deviation according to the actual grid frequency and the rated frequency; A7. Calculate the frequency deviation according to a preset frequency modulation calculation formula to obtain frequency modulation data; A8. Obtaining historical load data of the target power grid within the preset time period; A9. Calculate the historical load data to obtain the load fluctuation standard deviation; A10. Calculate the load fluctuation standard deviation according to a preset spare capacity calculation formula to obtain spare capacity data; A11. Determine the auxiliary service data according to the peak shaving data, the frequency regulation data and the spare capacity data.

[0038] In a specific embodiment, first, the historical electricity consumption data of the target aggregate within a preset time period is obtained. The historical electricity consumption data includes but is not limited to the electricity consumption information of industrial user sets, commercial user sets, residential user sets and distributed power source sets. The preset time period includes but is not limited to one day, one week, and one month, which are not specifically limited here. Then, the historical electricity consumption data is analyzed and calculated to obtain corresponding energy efficiency data, which includes energy efficiency index data, load forecast data, and energy saving potential data. Among them, the energy efficiency index data includes but is not limited to energy efficiency ratio and power factor, which are not specifically limited here. The calculation formula of the energy efficiency index data is as follows:

[0039]

[0040] Wherein, EER stands for energy efficiency ratio; It represents power factor; P represents active power; S represents apparent power, which refers to the product of the effective values ​​of voltage and current in an AC circuit. It is used to represent the total capacity of the circuit and its unit is volt-ampere (VA).

[0041] The load forecast data of the target aggregate can be determined by a preset time series analysis method. For example, the historical power consumption data P(t) can be modeled by an autoregressive moving average model to predict the future power load P(t+k), i.e., the load forecast data. Where t represents time, and k represents the time step of the forecast. The accuracy of the load forecast data can be evaluated by calculating the mean absolute error and the root mean square error. The calculation formulas for the mean absolute error and the root mean square error are as follows:

[0042]

[0043] Wherein, MAE represents the mean absolute error; n represents the number of prediction samples; i represents the i-th prediction sample; Indicates the actual power load; Indicates the predicted electricity load.

[0044] It should be noted that by comparing the values ​​of mean absolute error and root mean square error, we can intuitively understand the accuracy of the model. The smaller the value, the more accurate the prediction. Then, through the preset big data analysis technology, combined with the values ​​of mean absolute error and root mean square error, a large amount of historical electricity consumption data is processed and analyzed, and the parameters of the model are continuously optimized, thereby improving the accuracy of load forecasting data.

[0045] The energy-saving potential data include but are not limited to energy-saving potential and energy-saving investment return rate, which are not specifically limited here. The calculation formula of energy-saving potential is as follows:

[0046] in, represents the energy saving potential of the reference user set; represents the current energy consumption of a reference user set, the reference user set including but not limited to an industrial user set, a commercial user set, and a residential user set, which are not specifically limited here; It indicates the theoretical minimum energy consumption after the reference user set adopts the preset energy-saving measures. The energy-saving measures include but are not limited to energy-saving lighting transformation, high-efficiency motor replacement, peak-shifting electricity consumption, and on-demand electricity consumption, which are not specifically limited here.

[0047] The calculation formula for energy saving investment return is as follows:

[0048] in, represents the energy saving return on investment for the reference user set; Indicates the preset energy saving cost coefficient; Represents energy saving investment.

[0049] It should be noted that by calculating the energy-saving investment return rate, the economic benefits of energy-saving measures can be evaluated. When the energy-saving investment return rate is greater than 0, it means that the benefits brought by the energy-saving measures are greater than the costs; when the energy-saving investment return rate is less than or 0, it means that the benefits brought by the energy-saving measures are less than or equal to the costs. For example, for a group of industrial users, before replacing high-efficiency energy-saving equipment, the energy-saving investment return rate can be used to determine whether the energy-saving measures are feasible and provide a quantitative basis for energy-saving decisions.

[0050] Next, the adjustable load corresponding to the target aggregate is obtained, and the adjustable load is calculated according to the preset peak load calculation formula to obtain the peak load data. , that is, the adjustable load of the industrial user set, commercial user set, and residential user set. The peak-shaving data includes but is not limited to the total peak-shaving capacity, effective peak-shaving energy, and peak-shaving effect evaluation indicators. The peak-shaving effect evaluation indicators include peak-shaving response time, peak-shaving accuracy, and peak-shaving capacity utilization, which are not specifically limited here. The peak-shaving response time refers to the time from when the target aggregate receives the peak-shaving instruction to when it reaches the corresponding adjustment power of the peak-shaving instruction. The peak-shaving accuracy is used to indicate the degree of closeness between the actual adjustment power of the target aggregate and the expected adjustment power. Among them, the peak-shaving calculation formula is as follows:

[0051] in, Indicates the total peak load capacity; represents the adjustable load of the industrial user set; An adjustable load representing a collection of commercial users; Represents the adjustable load of the collection of residential users.

[0052]

[0053] in, Indicates the peak load capacity utilization rate; Indicates the capacity actually involved in peak load regulation.

[0054]

[0055] in, It represents the effective peak-shaving energy, that is, the effective energy actually used for peak-shaving; represents the theoretical peak shaving energy, , It represents the peak-shaving response time in the peak-shaving effect evaluation index. In practical applications, the peak-shaving tasks of the target aggregate can be reasonably allocated through the preset optimization scheduling algorithm to improve the peak-shaving capacity utilization and reduce energy loss.

[0056] Then, the actual grid frequency and rated frequency of the target power grid are obtained, and the frequency deviation is calculated based on the actual grid frequency and the rated frequency. The frequency deviation is then calculated according to the preset frequency modulation calculation formula to obtain the frequency modulation data. The frequency modulation data includes but is not limited to frequency deviation, the cost of frequency modulation services, and frequency modulation effect evaluation indicators. The frequency modulation effect evaluation indicators include frequency recovery time and frequency stability, which are not specifically limited here. The frequency recovery time refers to the time required for the frequency of the target power grid to recover to the specified range under the action of frequency modulation after it deviates from the rated value due to a disturbance; the frequency stability is used to indicate the degree to which the frequency of the target power grid remains stable during the frequency modulation process. The higher the stability, the smaller the frequency fluctuation, and the more stable the operation of the target power grid. Among them, the frequency modulation calculation formula is as follows:

[0057] in, Indicates the power regulation; Indicates the preset frequency modulation coefficient; It should be noted that, considering the rotational inertia and frequency change rate of the target power grid, the calculation formula for regulating power can also be as follows:

[0058] in, Indicates the power regulation; Indicates the moment of inertia of the target power grid; represents the frequency change rate of the target power grid; t represents time.

[0059]

[0060] in, represents the cost of frequency regulation services; Indicates the preset frequency regulation cost coefficient; It indicates the frequency recovery time in the frequency regulation effect evaluation index. It should be noted that in the frequency regulation process, the frequency change of the target power grid is monitored in real time, and the power output of the target aggregate is quickly adjusted according to the frequency regulation calculation formula, while considering the cost of the frequency regulation service, so as to optimize the frequency regulation strategy.

[0061] Next, the historical load data of the target power grid within the preset time period is obtained, the historical load data is calculated to obtain the load fluctuation standard deviation, and the load fluctuation standard deviation is calculated according to the preset spare capacity calculation formula to obtain the spare capacity data. The spare capacity data includes but is not limited to the spare capacity and the maintenance cost of the spare service, which are not specifically limited here. Among them, the spare capacity calculation formula is as follows:

[0062] in, Indicates spare capacity; The coefficient representing the confidence level of the reserve capacity can be found by looking up the preset standard normal distribution table; Represents the standard deviation of load fluctuation.

[0063] The calculation formula for the maintenance cost of the standby service is as follows:

[0064] in, represents the maintenance cost of the standby service; It indicates the maintenance cost of unit reserve capacity. It should be noted that according to the actual needs and reliability requirements of the target power grid, the reasonable determination of reserve capacity can reduce the maintenance cost of reserve services and improve the cost performance of reserve services.

[0065] Finally, the peak shaving data, frequency regulation data and spare capacity data are integrated to obtain ancillary service data.

[0066] It can be seen that by analyzing historical electricity consumption data to obtain energy efficiency data, we can clarify energy efficiency indicators, predict loads, tap energy-saving potential, and take targeted energy-saving measures to improve energy utilization efficiency and reduce electricity costs and energy losses. By calculating peak load and frequency regulation data, and calculating standby capacity data based on the standard deviation of load fluctuations, we can effectively improve the grid's ability to cope with peak and valley load changes, frequency fluctuations, and load mutations, ensure the safe and stable operation of the grid, and reduce accidents such as power outages.

[0067] In one possible embodiment, first, the energy saving contribution is determined according to the energy saving potential data; a first compensation amount is determined according to a preset energy saving compensation unit price and the energy saving contribution; then, the first compensation amount is distributed to a first target set corresponding to the energy saving contribution in the a target sets; a peak shaving effect evaluation index and a frequency modulation effect evaluation index are determined respectively according to the peak shaving data and the frequency modulation data; the peak shaving effect evaluation index and the frequency modulation effect evaluation index are calculated respectively according to a preset reward coefficient to obtain a first reward amount and a second reward amount; a second target set corresponding to the peak shaving effect evaluation index in the a target sets is determined; the first reward amount is distributed to the second target set; a third target set corresponding to the frequency modulation effect evaluation index in the a target sets is determined; and the second reward amount is distributed to the third target set.

[0068] Specifically, first, analyze the energy-saving potential data to determine the contribution of each target set in the target aggregate to energy saving, that is, the energy-saving contribution. Then, multiply the preset energy-saving compensation unit price by the energy-saving contribution to obtain the first compensation amount. Then determine the target set corresponding to the energy-saving contribution in a target set as the first target set, and issue the first compensation amount to the first target set to encourage users to continue to take energy-saving measures.

[0069] Next, the peak-shaving data and the frequency modulation data are analyzed to obtain the peak-shaving effect evaluation index and the frequency modulation effect evaluation index. Then, the peak-shaving effect evaluation index and the frequency modulation effect evaluation index are calculated respectively according to the preset frequency modulation reward coefficient to obtain the first reward amount and the second reward amount. Among them, the preset frequency modulation reward coefficient includes the peak-shaving reward coefficient and the peak-shaving reward coefficient, and the calculation formula is as follows:

[0070] in, Indicates the first reward amount; , , Both represent the peak load reward coefficient; Indicates the total peak load capacity; Indicates the peak load response time; Indicates the peak regulation accuracy.

[0071]

[0072] in, represents the second reward amount; , , Both represent the frequency modulation reward coefficient; Indicates the power regulation; Indicates frequency recovery time; Indicates frequency stability.

[0073] Finally, the target set corresponding to the peak-shaving effect evaluation index in the a target sets is determined as the second target set, and the first reward amount is issued to the second target set, so as to encourage users to actively participate in the peak-shaving auxiliary service of the target power grid. The target set corresponding to the frequency regulation effect evaluation index in the a target sets is determined as the third target set, and the second reward amount is issued to the third target set, so as to encourage users to actively participate in the frequency regulation auxiliary service of the target power grid.

[0074] It can be seen that through economic compensation and reward mechanisms, each target set in the target aggregate is encouraged to actively explore energy-saving potential and actively participate in the peak-shaving and frequency-regulating auxiliary services of the target power grid, thereby promoting efficient energy utilization and stable operation of the power system.

[0075] Step S502: construct a model according to the energy efficiency data and the auxiliary service data to obtain a dynamic interactive model.

[0076] The step of building a model based on the energy efficiency data and the auxiliary service data to obtain a dynamic interactive model specifically includes: B1. Integrate the energy efficiency data and the auxiliary service data to obtain model input data; B2. determining power exchange constraints between the target power grid and the target aggregate; B3. constructing an optimization objective function according to a preset model predictive control method to obtain a first optimization objective function; B4. Combining a preset obstacle function with the first optimization objective function to obtain an augmented objective function; The augmented objective function is as follows:

[0077] in, represents the augmented objective function; represents the first optimization objective function; Represents the barrier factor, which is used for continuous iterative updates; represents a barrier function; x represents a decision variable in vector form, including a power adjustment amounts corresponding to the a target sets; B5. Iteratively update the obstacle factor of the augmented objective function according to the model input data to obtain a target obstacle factor; B6. Adjusting the augmented objective function according to the target obstacle factor to obtain a second objective function; B7. Determine the dynamic interaction model according to the second objective function and the power exchange constraint.

[0078] In a specific embodiment, first, the energy efficiency data and the auxiliary service data are integrated to obtain the model input data. Then, the power exchange constraint conditions between the target power grid and the target aggregate are determined. The power exchange constraint conditions are as follows:

[0079] in, represents the target power flow, i.e., the power flowing from the target aggregate to the target grid; Indicates the lower limit value corresponding to the target power flow; Indicates the upper limit value corresponding to the target power flow. The calculation formula of the target power flow is as follows:

[0080] in, represents the total power of the target aggregate; It indicates the real-time power demand of the power grid. It should be noted that when the target power flow is greater than 0, it means that the target aggregate transmits power to the target power grid; when the target power flow is less than 0, it means that the target aggregate absorbs power from the target power grid; when the target power flow is equal to 0, it means that there is no interactive power transmission between the target aggregate and the target power grid.

[0081]

[0082] in, represents the power of a single industrial user, i represents an individual in the industrial user set I; represents the power of a single commercial user, c represents an individual in the commercial user set C; represents the power of a single residential user, r represents an individual in the residential user set R; Represents the power of a single distributed generation, and d represents the individual in the distributed generation set D.

[0083] Next, an optimization objective function is constructed according to the preset model predictive control method to obtain a first optimization objective function. The first optimization objective function is as follows:

[0084] in, represents the first optimization objective function; N represents the prediction time domain; k represents the time interval of the prediction time domain; , , All represent weight coefficients; t represents the current time; represents the real-time power demand of the power grid at the kth moment in the future; represents the total power of the target aggregate at the kth moment in the future; represents the power regulation amount of a single industrial user at the kth moment in the future; represents the power regulation amount of a single commercial user at the kth moment in the future; It should be noted that power regulation can be performed only on each user set, or on each user set and distributed power source set, which is not specifically limited here.

[0085] Then, the preset barrier function is combined with the first optimization objective function to obtain an augmented objective function, which is as follows:

[0086] in, represents the augmented objective function; represents the first optimization objective function; Represents the barrier factor, which is used for continuous iterative updates; represents the barrier function; x represents the decision variable in vector form, including a power adjustment quantities corresponding to a target set. Among them, the decision variable x in vector form can be expressed as [ ] and no specific limitation is given here.

[0087] It should be noted that when optimizing the first optimization objective function by using a preset optimization algorithm, for the inequality , introduce the corresponding barrier function , then during the optimization process, we can select the nodes close to the constraint boundary (so that The solution close to 0 is penalized to prevent the iteration point of the optimization algorithm from crossing the constraint boundary, ensuring that the solution is always within the feasible domain. represents a function of the decision variable x, m represents the number of constraints, and the obstacle function As shown below:

[0088] Finally, the barrier factor is iteratively updated according to the preset iterative algorithm. During the iteration process, the barrier factor is continuously adjusted according to the model input data, so that the constraint effect of the barrier function on the decision variable is gradually reasonable, avoiding the decision variable from exceeding the constraints such as power exchange, and approaching the optimal solution of the optimization problem, thereby obtaining the target barrier factor. Among them, the iterative algorithm can be an iterative rule related to the interior point method, which is not specifically limited here. Then, the target barrier factor is substituted into the augmented objective function, and the augmented objective function is adjusted to obtain the second optimization objective function. Then, the second optimization objective function is used as the optimization target, and combined with the power exchange constraint, a dynamic interaction model is constructed.

[0089] It should be noted that the target power grid can send control instructions to the target aggregate based on the real-time total aggregate power and the power demand of the power grid, and the target aggregate can adjust the power of each target set, that is, the power of each user and device, according to the control instructions, thereby achieving real-time power balance.

[0090] It can be seen that by integrating multi-source data and considering power exchange constraints, the model can fully reflect the actual operation of the power grid and the aggregate, improve the accuracy and reliability of the model, and provide a more accurate basis for decision-making. Then, by constructing and optimizing the objective function and using the barrier function to handle the constraints, the optimal solution can be found in different operating scenarios, so that the model can adapt to the complex and changeable power system operating environment and improve the efficiency and stability of the power grid operation.

[0091] Step S503, obtaining the grid demand power of the target grid corresponding to the target aggregate within a preset first control period.

[0092] Specifically, a preset fixed time interval is determined as a control cycle. The fixed time interval can be set according to factors such as the dynamic characteristics of the target power grid, the response speed of the user equipment, and the transmission delay of the communication system. For example, for a power system with faster changes, such as a system containing a large amount of distributed energy, the fixed time interval can be set to seconds or milliseconds; for a system with relatively slow changes, the fixed time interval can be appropriately extended. Among them, the preset first control cycle represents the fixed time interval, and the power grid demand power of the target power grid in the preset first control cycle can be obtained to provide a data basis for subsequent power regulation, resource allocation and other operations. It should be noted that in each control cycle, the power grid demand power of the target power grid and the total power of the target aggregate are monitored and analyzed in real time to facilitate the balance of power supply and demand and ensure the stable operation of the target power grid.

[0093] Step S504: Calculate the power demand of the power grid through the dynamic interaction model to obtain a reference power adjustment amount.

[0094] For easier understanding, see Figure 6 , Figure 6 : is a schematic diagram of a process for calculating a power regulation amount provided by an embodiment of the present application, wherein the reference power regulation amount is obtained by calculating according to the power demand of the power grid through the dynamic interaction model, and the specific steps include: C1. Obtaining the actual power of each target set in the a target sets within a preset second control period to obtain a first power; the preset second control period is a control period before the preset first control period; C2. Determine the sum of the a first powers as the first total power; C3. Obtain the power regulation constraint condition of each target set in the a target sets to obtain a power regulation constraint conditions; C4. determining a first power adjustment amount according to the first total power and the power required by the power grid; C5. Determine a first power adjustment amount corresponding to the a power adjustment constraint conditions according to the first power adjustment amount through the dynamic interaction model; C6. Determine the reference power adjustment amount according to the a first power adjustment amounts.

[0095] In a specific embodiment, first, the actual power of each target set in a target set within a preset second control cycle is obtained to obtain a first power, and the preset second control cycle is the previous control cycle of the preset first control cycle. Then, the a first powers are added to obtain the first total power. Then, the power regulation constraint conditions of each target set in the a target set are obtained to obtain a power regulation constraint conditions. The first power regulation amount is determined according to the first total power and the power required by the power grid, that is, by comparing the difference between the first total power and the power required by the power grid, the first power regulation amount that the target aggregate needs to adjust to meet the power required by the power grid is calculated. Then, using the dynamic interaction model, a first power regulation amount is determined according to the first power regulation amount and a power regulation constraint conditions. Among them, each first power regulation amount in the a first power regulation amount corresponds to a target set. Finally, the a first power regulation amounts are added to obtain a reference power regulation amount.

[0096] It can be seen that by comprehensively considering historical power, current demand, constraints, etc., the dynamic interactive model is used to accurately determine the power adjustment amount of each target set, realize the refined regulation of the power system, and ensure the balance of power supply and demand in the power grid.

[0097] In a possible embodiment, in the tth control cycle, the power update formula of industrial user i is as follows:

[0098] in, represents the actual power consumption of industrial user i in the tth control cycle; represents the actual power consumption of industrial user i in the previous control period of the t-th control period; It represents the power regulation amount of industrial user i in the tth control cycle.

[0099] Among them, the power regulation constraints of industrial user i are as follows:

[0100] in, Indicates the lower limit of the power regulation amount of industrial user i; Represents the upper limit of the power regulation of industrial user i. It should be noted that the power regulation of industrial users must take into account the process requirements and operational stability of production equipment to ensure that the power regulation is within a reasonable and safe range, and avoid excessive or small regulation that affects equipment operation, production processes and grid stability. For example, continuous production processes such as steel smelting and chemical production have high requirements for power stability, and power regulation cannot interfere with production continuity and product quality. Therefore, under the premise of meeting production needs, the power regulation amount is reasonably determined based on the power regulation constraints to achieve a balance between power system regulation and industrial production needs.

[0101] In a possible embodiment, in the tth control cycle, the power update formula of commercial user c is as follows:

[0102] in, represents the actual power consumption of commercial user c in the tth control period; represents the actual power consumption of commercial user c in the previous control period of the t-th control period; Represents the power adjustment amount of commercial user c in the tth control cycle.

[0103] It should be noted that for the commercial user set C, the power consumption characteristics and load regulation capacity constraints need to be considered to ensure that the adjusted power is within a reasonable range. Commercial users can reasonably adjust the power consumption time and power consumption without affecting normal business operations. For example, shopping malls can reduce the power consumption of non-critical equipment during peak power consumption periods, such as reducing lighting brightness and adjusting air conditioning temperature settings.

[0104] In a possible embodiment, in the tth control period, the power update formula of the residential user r is as follows:

[0105] in, represents the actual power consumption of residential user r in the tth control period; represents the actual power consumption of residential user r in the previous control period of the tth control period; It represents the power regulation amount of residential user r in the tth control cycle.

[0106] It should be noted that for the set of residential users R, the randomness of their electricity consumption behavior needs to be considered. At the same time, the use probability and average power changes of various types of electrical equipment need to be comprehensively considered during the adjustment process to ensure that the normal electricity demand of residential users is not greatly affected. Among them, residential users can independently choose the way and degree of participation in demand response through smart electrical equipment and user interaction interfaces. For example, residential users can set some non-essential electrical equipment to automatically shut down during peak electricity consumption periods, or adjust the charging time of electric vehicles to low electricity consumption periods, without specific restrictions here.

[0107] In a possible embodiment, in the tth control cycle, for a distributed power source d, such as a photovoltaic power generation device, its actual power generation power is not only affected by the light intensity and conversion efficiency, but also needs to consider the power regulation when interacting with the target power grid. The power update formula of the distributed power source d is as follows:

[0108] in, represents the actual power generation of distributed generation d in the tth control cycle; Relevant parameters of distributed power source d, such as photovoltaic panel area of ​​photovoltaic power generation equipment; represents the conversion efficiency of the tth control cycle; Represents the light intensity of the tth control cycle.

[0109] Among them, the power generation power of the distributed power source d can be adjusted by adjusting the relevant parameters thereof, and the power update formula after adjustment is as follows:

[0110] in, It represents the actual power generation of distributed power source d in the tth control cycle after adjusting the relevant parameters of distributed power source d; It indicates the influence coefficient of adjusting the relevant parameters of the distributed power source d on its power generation. Among them, the maximum power point tracking technology can also be used to adjust the working point of the photovoltaic array of the photovoltaic power generation equipment in real time according to conditions such as light intensity and ambient temperature, so that it always works at the maximum power output state, further improving the power generation.

[0111] In a possible embodiment, the energy storage device can also be integrated into the target polymer to coordinate and optimize the power regulation engineering of the target polymer. , when the energy storage device is in charging state, is a negative value. When the energy storage device is in a discharging state, is a positive value. Among them, the state of charge of the energy storage device To reflect the remaining power, the calculation formula is as follows:

[0112] in, Indicates the state of charge of the energy storage device in the tth control cycle; Indicates the charge state of the energy storage device in the previous control cycle of the t-th control cycle; Indicates the charging efficiency of the energy storage device; Indicates the discharge efficiency of the energy storage device; Indicates the rated capacity of the energy storage device; Indicates the duration corresponding to a single control cycle; Among them, the charging and discharging power of the energy storage device must meet its power limit, and the power constraint conditions corresponding to the energy storage device are as follows:

[0113] in, Indicates the lower limit of the charging and discharging power of the energy storage device; Indicates the upper limit of the charging and discharging power of the energy storage device.

[0114] It should be noted that the upper and lower limits of the charging and discharging power of the energy storage device can be constrained to avoid damage to the device due to power exceeding the device's tolerance range. At the same time, the charge state of the energy storage device must be maintained within a preset reasonable range. During the power regulation process, the power changes of the energy storage device work in coordination with other users and devices. For example, when the target grid has excess power, the excess energy is preferentially stored in the energy storage device; when the target grid has insufficient power, the energy storage device is discharged.

[0115] The calculation formula of the updated target aggregate total power is as follows:

[0116] It should be noted that in order to optimize the charging and discharging strategy of energy storage equipment, a model predictive control method can be used to combine the grid power demand of the target grid, the charge state of the energy storage equipment and the power forecast for a period of time in the future to formulate the optimal charging and discharging plan and improve the utilization efficiency and service life of the energy storage equipment.

[0117] For easier understanding, see Figure 7 , Figure 7 is a flow chart of adjusting a power regulation amount provided by an embodiment of the present application. After determining a first power regulation amount corresponding to the a power regulation constraint conditions according to the first power regulation amount through the dynamic interaction model, the specific steps further include: D1. If the frequency deviation is greater than a preset frequency deviation threshold, determining a first adjustment parameter according to the frequency deviation; D2. adjusting the first adjustment parameter according to a preset frequency correction coefficient to obtain a second adjustment parameter; D3. Adjust each of the a first power adjustment amounts according to the second adjustment parameter to obtain a second power adjustment amounts; D4. Determine the reference power adjustment amount according to the a second power adjustment amounts.

[0118] In a specific embodiment, first, if the frequency deviation is greater than a preset frequency deviation threshold, a first adjustment parameter is determined according to the frequency deviation. Among them, the preset frequency deviation threshold can be determined according to factors such as the target power grid structure, the characteristics of the power equipment, and the type of power load. Then, the first adjustment parameter is adjusted according to the preset frequency correction coefficient to obtain the second adjustment parameter. Then, each of the a first power adjustment amounts is adjusted according to the second adjustment parameter to obtain a second power adjustment amounts. Among them, the a first power adjustment amounts correspond one-to-one to the a target sets. Finally, the reference power adjustment amount is determined according to the a second power adjustment amounts.

[0119] Among them, a target sets include industrial user set I, commercial user set C, residential user set R, and distributed power source set D. For example, for industrial user i in industrial user set I, the corresponding power regulation amount correction formula is as follows:

[0120] in, represents the second power adjustment amount corresponding to the industrial user i; represents the first power adjustment amount corresponding to industrial user i; Indicates the frequency correction factor; Indicates frequency deviation; Indicates the actual grid frequency of the target grid; Indicates the rated frequency of the target power grid.

[0121] It can be seen that adjusting the power regulation amount according to the frequency deviation can effectively deal with the frequency fluctuation problem of the target power grid. When the frequency deviation exceeds the preset frequency deviation threshold, timely adjusting the power regulation amount of each target set will help restore the power grid frequency to normal levels, ensure the frequency stability of the power system, and avoid affecting the normal operation of equipment or even causing system failures due to frequency anomalies.

[0122] Step S505: Power is adjusted on the target aggregate according to the reference power adjustment amount to ensure that the total power of the target aggregate is in a power balance state with the power demanded by the power grid.

[0123] The step of performing power regulation on the target polymer according to the reference power regulation amount specifically includes: E1. determining a second total power of the target aggregate according to the reference power adjustment amount and the first total power; E2. Obtain a deviation between the power grid demand power and the second total power to obtain a first power deviation; E3. Obtain the power deviation upper limit and the power deviation lower limit corresponding to the preset power deviation range; E4. If the first power deviation is greater than the power deviation upper limit, determining a first adjustment factor according to a difference between the first power deviation and the power deviation upper limit; E5. adjusting the power of the target polymer according to the first adjustment factor; E6. If the first power deviation is less than the power deviation lower limit, determining a second adjustment factor according to a difference between the power deviation lower limit and the first power deviation; E7. Adjust the power of the target polymer according to the second adjustment factor.

[0124] In a specific embodiment, first, the first total power is adjusted according to the reference power adjustment amount to obtain the second total power of the target aggregate. Then, the deviation between the power grid demand power and the second total power is calculated to obtain the first power deviation. Then, the power deviation upper limit and the power deviation lower limit corresponding to the preset power deviation range are obtained. The preset power deviation range can be pre-set according to the safety and stability requirements of the target power grid operation and the bearing capacity of the equipment.

[0125] Next, if the first power deviation is greater than the upper limit of the power deviation, it means that the power demanded by the power grid is too high relative to the total power of the target aggregate, that is, the power supply is insufficient. The first adjustment factor is determined according to the difference between the first power deviation and the upper limit of the power deviation. Then, the power of the target aggregate is adjusted according to the first adjustment factor, for example, the power generation power of the target aggregate is increased, or the power of some users or equipment in the target aggregate is reduced, so that the total power of the target aggregate is close to a reasonable range. If the first power deviation is less than the lower limit of the power deviation, it means that the power demanded by the power grid is too low relative to the total power of the target aggregate, that is, the power supply is excessive. The second adjustment factor can be determined according to the difference between the lower limit of the power deviation and the first power deviation, and the power of the target aggregate can be adjusted according to the second adjustment factor, for example, the power generation power of the target aggregate is reduced, or the power load is increased. It should be noted that in each control cycle, by adjusting the power of the target aggregate, the total power of the target aggregate meets the real-time power demand of the power grid, ensuring that the power supply and demand can be basically balanced in each control cycle, avoiding serious power surplus or shortage.

[0126] It can be seen that by real-time monitoring and adjusting the power relationship between the target aggregate and the power grid, the total power of the target aggregate can be ensured to match the power demand of the power grid, the power balance of the power system can be maintained, and problems such as grid instability or equipment damage caused by power deviation beyond a reasonable range can be avoided.

[0127] Among them, the power exchange constraints should be observed between the target aggregate and the target power grid, that is, the power flowing from the target aggregate to the target power grid must meet the upper and lower limit constraints. Among them, the target power flow rate represents the power flowing from the target aggregate to the target power grid. When the target power flow rate is greater than the upper limit value, it means that the target aggregate transmits too much power to the target power grid, which may affect the stability of the target power grid. In this case, it is necessary to adjust the power generation and power consumption inside the target aggregate to reduce the power transmitted to the outside; when the target power flow rate is less than the lower limit value, it means that the target aggregate absorbs too much power from the target power grid, and corresponding measures need to be taken to reduce the power load of the target aggregate or increase the power generation. Among them, in actual operation, the upper and lower limit constraints of power exchange can be dynamically adjusted according to the real-time status and safety margin of the target power grid to ensure the stable operation of the target power grid and the target aggregate.

[0128] It should be noted that when adjusting power, various users and equipment of the target aggregate must meet their corresponding equipment operation constraints. For example, the production equipment of industrial users cannot affect the normal production process due to power adjustment, and its power adjustment speed cannot exceed the maximum adjustment rate allowed by the equipment; the adjustment of the power generation of distributed power sources must also be carried out within the technical parameter range of the equipment, such as the conversion efficiency of photovoltaic power generation equipment cannot be lower than its minimum technical guarantee value. For equipment operation constraints, the equipment operation parameters of the target aggregate can be monitored in real time. When the equipment operation parameters are close to or exceed the corresponding constraint range, the power adjustment strategy is adjusted in time to ensure safe and stable operation of the equipment.

[0129] The above mainly introduces the scheme of the embodiment of the present application from the perspective of the execution process of the method side. It is understandable that in order to realize the above functions, the electronic device includes a hardware structure and / or software module corresponding to each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment provided herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software.

[0130] The embodiment of the present application can divide the electronic device into functional units according to the above method example. For example, each functional unit can be divided according to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. It should be noted that the division of units in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0131] In the case of dividing each functional module into corresponding functional modules, Figure 88 is a functional module composition block diagram of an auxiliary service-based aggregate dynamic interaction device provided in an embodiment of the present application. The auxiliary service-based aggregate dynamic interaction device 800 includes a first acquisition module 810, a construction module 820, a second acquisition module 830, a calculation module 840 and an adjustment module 850, wherein: The first acquisition module 810 is used to acquire energy efficiency data and auxiliary service data corresponding to a target aggregate; the target aggregate includes a target set; the target set includes any one of the following: an industrial user set, a commercial user set, a residential user set, and a distributed power source set; a is an integer greater than 1; The construction module 820 is used to construct a model according to the energy efficiency data and the auxiliary service data to obtain a dynamic interactive model; The second acquisition module 830 is used to obtain the grid demand power of the target grid corresponding to the target aggregate within a preset first control period; The calculation module 840 is used to calculate according to the power demand of the power grid through the dynamic interaction model to obtain a reference power adjustment amount; The regulation module 850 is used to perform power regulation on the target aggregate according to the reference power regulation amount to ensure that the total power of the target aggregate is in a power balance state with the power demanded by the power grid.

[0132] Optionally, in the aspect of acquiring the energy efficiency data and auxiliary service data corresponding to the target aggregate, the first acquisition module 810 is specifically used to: Acquire historical electricity consumption data of the target aggregate within a preset time period; Analyze and calculate the historical electricity consumption data to obtain the energy efficiency data; the energy efficiency data includes energy efficiency index data, load forecast data, and energy saving potential data; Obtaining an adjustable load corresponding to the target polymer; Calculate the adjustable load according to a preset peak load calculation formula to obtain peak load data; Acquiring an actual grid frequency and a rated frequency of the target grid; determining a frequency deviation according to the actual grid frequency and the rated frequency; Calculating the frequency deviation according to a preset frequency modulation calculation formula to obtain frequency modulation data; Acquire historical load data of the target power grid within the preset time period; Calculating the historical load data to obtain a load fluctuation standard deviation; Calculating the load fluctuation standard deviation according to a preset spare capacity calculation formula to obtain spare capacity data; The auxiliary service data is determined according to the peak shaving data, the frequency regulation data and the spare capacity data.

[0133] Optionally, the first acquisition module 810 is further specifically configured to: Determining an energy saving contribution amount based on the energy saving potential data; Determine a first compensation amount according to a preset energy-saving compensation unit price and the energy-saving contribution amount; Distribute the first compensation amount to a first target set corresponding to the energy saving contribution amount in the a target sets; Determine a peak shaving effect evaluation index and a frequency modulation effect evaluation index according to the peak shaving data and the frequency modulation data respectively; The peak load regulation effect evaluation index and the frequency regulation effect evaluation index are calculated respectively according to a preset reward coefficient to obtain a first reward amount and a second reward amount; Determine a second target set corresponding to the peak load effect evaluation index in the a target sets; distributing the first reward amount to the second target set; Determine a third target set corresponding to the frequency modulation effect evaluation index in the a target sets; The second reward amount is distributed to the third target set.

[0134] Optionally, in the aspect of constructing a model according to the energy efficiency data and the auxiliary service data to obtain a dynamic interactive model, the constructing module 820 is specifically used to: Integrate the energy efficiency data and the auxiliary service data to obtain model input data; Determining power exchange constraints between the target power grid and the target aggregate; Constructing an optimization objective function according to a preset model predictive control method to obtain a first optimization objective function; Combining a preset obstacle function with the first optimization objective function to obtain an augmented objective function; The augmented objective function is as follows:

[0135] in, represents the augmented objective function; represents the first optimization objective function; Represents the barrier factor, which is used for continuous iterative updates; represents a barrier function; x represents a decision variable in vector form, including a power adjustment amounts corresponding to the a target sets; Iteratively updating the obstacle factor of the augmented objective function according to the model input data to obtain a target obstacle factor; Adjusting the augmented objective function according to the target obstacle factor to obtain a second optimization objective function; The dynamic interaction model is determined according to the second optimization objective function and the power exchange constraint condition.

[0136] Optionally, in the aspect of calculating according to the power grid demand power through the dynamic interaction model to obtain the reference power adjustment amount, the calculation module 840 is specifically used for: Acquire the actual power of each target set in the a target sets within a preset second control period to obtain a first power; the preset second control period is a control period before the preset first control period; Determine the sum of the a first powers as a first total power; Obtaining a power regulation constraint condition of each target set in the a target sets to obtain a power regulation constraint conditions; Determine a first power adjustment amount according to the first total power and the power grid demand power; Determining a first power adjustment amounts corresponding to the a power adjustment constraint conditions according to the first power adjustment amount through the dynamic interaction model; The reference power adjustment amount is determined according to the a first power adjustment amounts.

[0137] Optionally, after determining the a first power adjustment amounts corresponding to the a power adjustment constraints according to the first power adjustment amount through the dynamic interaction model, the calculation module 840 is further specifically used to: If the frequency deviation is greater than a preset frequency deviation threshold, determining a first adjustment parameter according to the frequency deviation; Adjust the first adjustment parameter according to a preset frequency correction coefficient to obtain a second adjustment parameter; Adjust each of the a first power adjustment amounts according to the second adjustment parameter to obtain a second power adjustment amounts; The reference power adjustment amount is determined according to the a second power adjustment amounts.

[0138] Optionally, in the aspect of performing power regulation on the target aggregate according to the reference power regulation amount, the regulation module 850 is specifically configured to: Determine a second total power of the target aggregate according to the reference power adjustment amount and the first total power; Obtaining a deviation between the power grid demand power and the second total power to obtain a first power deviation; Obtain the power deviation upper limit and power deviation lower limit corresponding to the preset power deviation range; If the first power deviation is greater than the power deviation upper limit, determining a first adjustment factor according to a difference between the first power deviation and the power deviation upper limit; adjusting the power of the target polymer according to the first adjustment factor; If the first power deviation is less than the power deviation lower limit, determining a second adjustment factor according to a difference between the power deviation lower limit and the first power deviation; The power of the target polymer is adjusted according to the second adjustment factor.

[0139] It can be seen that by constructing a dynamic interactive model, calculating the reference power adjustment amount according to the power demand of the power grid and adjusting the target aggregate power, it is possible to respond to changes in the power grid load in real time, avoid power shortages or surpluses, and coordinate the power balance between users and the power grid.

[0140] It should be noted that the specific implementation of each operation can adopt the corresponding description of the method embodiment shown above, and the aggregate dynamic interaction device 800 based on auxiliary services can be used to execute the above method embodiment of the present application, which will not be repeated here.

[0141] An embodiment of the present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps of any method recorded in the above method embodiments, and the above computer includes an electronic device.

[0142] The embodiment of the present application also provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer includes an electronic device.

[0143] It should be noted that, for the above-mentioned various embodiments, for the sake of simple description, they are all expressed as a series of action combinations. Those skilled in the art should be aware that the present application is not limited by the described order of actions, because some steps in the embodiments of the present application can be performed in other orders or simultaneously. In addition, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions, steps, modules or units involved are not necessarily required by the embodiments of the present application.

[0144] In the above embodiments, the embodiments of the present application have different focuses on the description of each embodiment. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0145] Those skilled in the art should be aware that in one or more of the above examples, the functions described in the embodiments of the present application can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiments of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server, a data center, etc. that contains one or more available media integrations.

[0146] The modules / units included in the devices and products described in the above embodiments may be software modules / units or hardware modules / units, or may be partially software modules / units and partially hardware modules / units. For example, for the devices and products applied to or integrated in the chip, the modules / units included therein may all be implemented in the form of hardware such as circuits, or at least some of the modules / units may be implemented in the form of software programs, which run on the processor integrated inside the chip, and the remaining (if any) modules / units may be implemented in the form of hardware such as circuits; for the devices and products applied to or integrated in the chip module, the modules / units included therein may all be implemented in the form of hardware such as circuits, and different modules / units may be located in the same component (such as chip, circuit module, etc.) or different components of the chip module, or at least some of the modules / units may be implemented in the form of software programs. It is implemented in the form of a software program that runs on a processor integrated inside the chip module, and the remaining (if any) modules / units can be implemented in hardware such as circuits; for various devices and products applied to or integrated in the terminal equipment, the various modules / units contained therein can be implemented in hardware such as circuits, and different modules / units can be located in the same component (for example, chip, circuit module, etc.) or different components in the terminal equipment, or at least some of the modules / units can be implemented in the form of a software program that runs on a processor integrated inside the terminal equipment, and the remaining (if any) modules / units can be implemented in hardware such as circuits.

[0147] The specific implementation methods described above further illustrate the purpose, technical solutions and beneficial effects of the embodiments of the present application. It should be understood that the above description is only the specific implementation method of the embodiments of the present application and is not intended to limit the protection scope of the embodiments of the present application. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solutions of the embodiments of the present application should be included in the protection scope of the embodiments of the present application.

Claims

1. A dynamic interaction method of aggregates based on auxiliary services, characterized in that: The method comprises: Obtain energy efficiency data and auxiliary service data corresponding to a target aggregate; the target aggregate includes a target set; the target set includes any one of the following: an industrial user set, a commercial user set, a residential user set, and a distributed power source set; a is an integer greater than 1; Building a model based on the energy efficiency data and the auxiliary service data to obtain a dynamic interactive model; Obtaining a grid demand power of a target grid corresponding to the target aggregate within a preset first control period; Calculating according to the power demand of the power grid through the dynamic interaction model to obtain a reference power regulation amount; The target aggregate is power regulated according to the reference power regulation amount to ensure that the total power of the target aggregate is in a power balance state with the power demanded by the power grid.

2. The method according to claim 1, characterized in that The obtaining of energy efficiency data and auxiliary service data corresponding to the target aggregate includes: Acquire historical electricity consumption data of the target aggregate within a preset time period; Analyze and calculate the historical electricity consumption data to obtain the energy efficiency data; the energy efficiency data includes energy efficiency index data, load forecast data, and energy saving potential data; Obtaining an adjustable load corresponding to the target polymer; Calculate the adjustable load according to a preset peak load calculation formula to obtain peak load data; Acquiring an actual grid frequency and a rated frequency of the target grid; determining a frequency deviation according to the actual grid frequency and the rated frequency; Calculating the frequency deviation according to a preset frequency modulation calculation formula to obtain frequency modulation data; Acquire historical load data of the target power grid within the preset time period; Calculating the historical load data to obtain a load fluctuation standard deviation; Calculating the load fluctuation standard deviation according to a preset spare capacity calculation formula to obtain spare capacity data; The auxiliary service data is determined according to the peak shaving data, the frequency regulation data and the spare capacity data.

3. The method according to claim 2, characterized in that The method further comprises: Determining an energy saving contribution amount based on the energy saving potential data; Determine a first compensation amount according to a preset energy-saving compensation unit price and the energy-saving contribution amount; Distribute the first compensation amount to a first target set corresponding to the energy saving contribution amount in the a target sets; Determine a peak shaving effect evaluation index and a frequency modulation effect evaluation index according to the peak shaving data and the frequency modulation data respectively; The peak load regulation effect evaluation index and the frequency regulation effect evaluation index are calculated respectively according to a preset reward coefficient to obtain a first reward amount and a second reward amount; Determine a second target set corresponding to the peak load effect evaluation index in the a target sets; distributing the first reward amount to the second target set; Determine a third target set corresponding to the frequency modulation effect evaluation index in the a target sets; The second reward amount is distributed to the third target set.

4. The method according to claim 1, characterized in that The step of constructing a model according to the energy efficiency data and the auxiliary service data to obtain a dynamic interactive model includes: Integrate the energy efficiency data and the auxiliary service data to obtain model input data; Determining power exchange constraints between the target power grid and the target aggregate; Constructing an optimization objective function according to a preset model predictive control method to obtain a first optimization objective function; Combining a preset obstacle function with the first optimization objective function to obtain an augmented objective function; The augmented objective function is as follows: in, represents the augmented objective function; represents the first optimization objective function; Represents the barrier factor, which is used for continuous iterative updates; represents a barrier function; x represents a decision variable in vector form, including a power adjustment amounts corresponding to the a target sets; Iteratively updating the obstacle factor of the augmented objective function according to the model input data to obtain a target obstacle factor; Adjusting the augmented objective function according to the target obstacle factor to obtain a second optimization objective function; The dynamic interaction model is determined according to the second optimization objective function and the power exchange constraint condition.

5. The method according to claim 2, characterized in that The step of calculating the power demand of the power grid by the dynamic interaction model to obtain a reference power adjustment amount includes: Acquire the actual power of each target set in the a target sets within a preset second control period to obtain a first power; the preset second control period is a control period before the preset first control period; Determine the sum of the a first powers as a first total power; Obtaining a power regulation constraint condition of each target set in the a target sets to obtain a power regulation constraint conditions; Determine a first power adjustment amount according to the first total power and the power grid demand power; Determining a first power adjustment amounts corresponding to the a power adjustment constraint conditions according to the first power adjustment amount through the dynamic interaction model; The reference power adjustment amount is determined according to the a first power adjustment amounts.

6. The method according to claim 5, characterized in that After determining the a first power adjustment amounts corresponding to the a power adjustment constraints according to the first power adjustment amount through the dynamic interaction model, the method further includes: If the frequency deviation is greater than a preset frequency deviation threshold, determining a first adjustment parameter according to the frequency deviation; Adjust the first adjustment parameter according to a preset frequency correction coefficient to obtain a second adjustment parameter; Adjust each of the a first power adjustment amounts according to the second adjustment parameter to obtain a second power adjustment amounts; The reference power adjustment amount is determined according to the a second power adjustment amounts.

7. The method according to claim 5 or 6, characterized in that The power regulation of the target polymer according to the reference power regulation amount includes: Determine a second total power of the target aggregate according to the reference power adjustment amount and the first total power; Obtaining a deviation between the power grid demand power and the second total power to obtain a first power deviation; Obtain the power deviation upper limit and power deviation lower limit corresponding to the preset power deviation range; If the first power deviation is greater than the power deviation upper limit, determining a first adjustment factor according to a difference between the first power deviation and the power deviation upper limit; adjusting the power of the target polymer according to the first adjustment factor; If the first power deviation is less than the power deviation lower limit, determining a second adjustment factor according to a difference between the power deviation lower limit and the first power deviation; The power of the target polymer is adjusted according to the second adjustment factor.

8. A dynamic interactive device based on auxiliary services, characterized in that: The device comprises a first acquisition module, a construction module, a second acquisition module, a calculation module and an adjustment module, wherein: The first acquisition module is used to acquire energy efficiency data and auxiliary service data corresponding to a target aggregate; the target aggregate includes a target set; the target set includes any one of the following: an industrial user set, a commercial user set, a residential user set, and a distributed power source set; a is an integer greater than 1; The construction module is used to construct a model according to the energy efficiency data and the auxiliary service data to obtain a dynamic interactive model; The second acquisition module is used to acquire the grid demand power of the target grid corresponding to the target aggregate within a preset first control period; The calculation module is used to calculate according to the power demand of the power grid through the dynamic interaction model to obtain a reference power adjustment amount; The regulation module is used to perform power regulation on the target aggregate according to the reference power regulation amount to ensure that the total power of the target aggregate is in a power balance state with the power demanded by the power grid.

9. An electronic device, characterized in that: include: A processor, a memory, a communication interface, and one or more programs; The one or more programs are stored in the memory and configured to be executed by the processor, the programs comprising instructions for executing the steps in the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 7.

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