Virtual control unit frequency response real-time control method

Abstract

The invention belongs to the technical field of power system virtual control unit frequency response real-time control, and particularly relates to a virtual control unit frequency response real-time control method. The method comprises the following steps: establishing a real-time control model of the distributed resources according to report information and a real-time control mode of the distributed resources; designing a control mode for online budgeting and real-time control according to the real-time characteristic of the real-time control model and the existing control mode; establishing a constraint model according to the online budget and the real-time control mode, and performing simulation analysis; and according to a simulation analysis result, obtaining an output curve of each distributed resource and an income condition of the virtual control unit under a normal condition and an abnormal condition, and realizing optimal distribution of the distributed resources. According to the method, distributed resources can participate in main network frequency control, and help is provided for construction of a novel power system.

Description

Technical Field

[0001] This invention belongs to the field of real-time frequency response control technology for virtual control units in power systems, and particularly relates to a real-time frequency response control method for virtual control units. Background Technology

[0002] With the construction of new power systems, the integration of high proportions of renewable energy and power electronic equipment has brought new challenges to the power system. On the supply side, the proportion of installed capacity of new energy sources has been increasing year by year, but due to their volatility and uncertainty, they threaten the safe and stable operation of the power grid. Meanwhile, the proportion of thermal power units with rotating characteristics has been declining year by year due to their continuous retirement. This has led to a weakening of the power system's frequency stability capability, insufficient frequency regulation capability of the main grid, and an increased risk of frequency accidents.

[0003] The load side possesses a vast amount of distributed energy resources (DERs) capable of bidirectional interaction with the power grid, exhibiting high flexibility and enormous potential. Utilizing these DERs to participate in grid-side control could effectively supplement grid frequency regulation resources and better maintain system frequency security. However, these distributed resources are characterized by small individual capacity, large numbers, and dispersed access points. Their output is highly uncertain, influenced by factors such as weather conditions and user behavior. Allowing them to be connected on a large scale would inevitably affect the safe and stable operation of the power system.

[0004] To overcome these challenges, virtual power plant technology can be used to aggregate distributed resources, combining them into a unified whole and constructing a virtual control unit to participate in main grid frequency control. This allows distributed resources to participate in frequency response. Therefore, the virtual control unit, by aggregating distributed resources, can participate in main grid frequency control as a whole. However, its control strategy is still immature, and a control method capable of real-time optimized scheduling is urgently needed. Summary of the Invention

[0005] To address the shortcomings of the existing technology, this invention provides a real-time frequency response control method for a virtual control unit. Its purpose is to achieve real-time control of the frequency response of distributed resources, thereby optimizing the output of these resources.

[0006] The technical solution adopted by the present invention to achieve the above objectives is as follows:

[0007] A real-time frequency response control method for a virtual control unit includes:

[0008] Based on the reported information and real-time control mode of distributed resources, a real-time control model for distributed resources is established.

[0009] Design an online budget and real-time control mode based on the real-time characteristics of the real-time control model and existing control modes;

[0010] A constraint model is established based on the control mode of online budgeting and real-time control, and simulation analysis is performed.

[0011] Based on the simulation analysis results, the output curves of each distributed resource and the revenue of the virtual control unit under normal and abnormal conditions are obtained, thereby realizing the optimal allocation of distributed resources.

[0012] Furthermore, the reported information of the distributed resources includes: reported information of electric vehicles, reported information of energy storage, and reported information of industrial loads; the reported information of electric vehicles includes: current state of charge, upper and lower limits of state of charge, rated charge and discharge power, rated capacity, expected state of charge, and off-grid time; the reported information of energy storage includes: current state of charge, upper and lower limits of state of charge, rated charge and discharge power, and rated capacity; the reported information of industrial loads includes: initial state, transferable capacity, and transferable power.

[0013] Furthermore, the design of an online budget and real-time control mode based on the real-time characteristics of the real-time control model and existing control modes specifically involves: dividing a 24-hour day into 96 equal periods, setting a control period of 15 minutes, assuming that the operating state of distributed resources remains unchanged within the control period, and setting the control cycle to 30 minutes. The reporting information of distributed resources is determined 5 minutes in advance, and the adjustability of each distributed resource is calculated. Simultaneously, simulation analysis is performed on all possible disturbances to form a control strategy table. If a large disturbance occurs, the information in the strategy table is matched to obtain the control strategy for each distributed resource. If no large disturbance occurs, the next period continues.

[0014] Furthermore, a constraint model is established based on the online budget and real-time control mode, and simulation analysis is performed. Specifically, when a large disturbance occurs in the power grid, the main grid sends control tasks to the virtual control unit, including lag time, ramp-up time, sustainability time, and power regulation parameters. The virtual control unit also makes requirements on its subordinate distributed resources, including requirements for adjustability, pricing regulations for distributed resources participating in primary frequency regulation, and basic requirements for the power recovery capability of distributed resources.

[0015] Furthermore, the establishment of the constraint model based on the online budget and real-time control mode includes:

[0016] Maximizing the revenue of the virtual control unit is the objective function of the model:

[0017] Right now:

[0018] in: The revenue generated from the sale of power from the grid by the virtual control unit. The cost factor for purchasing virtual control unit power for the power grid is then... ; The intermediary fee paid to the virtual control unit for distributed resources. , and Let T represent the power of electric vehicles, energy storage, and industrial load participating in the first frequency regulation in time period t, respectively, where T is the duration. For intermediary fees, All variables are binary, and N, M, and H represent the number of the three types of distributed resources participating in a single frequency modulation. Then:

[0019]

[0020] in: The electricity purchase fee paid to the virtual control unit for purchasing distributed resource power. Electricity purchase cost coefficients for electric vehicles, energy storage, and industrial loads. and These are the battery compensation fees paid by the virtual control unit to electric vehicles and battery storage, respectively, where: Let i be the discharge power of electric vehicle i during time period t. Let i be the discharge power of the battery energy storage during time period t, then:

[0021]

[0022] in: The penalty fee payable to the power grid by the virtual control unit for failing to complete the control tasks issued by the power grid. As a penalty cost coefficient, For the control and regulation tasks issued by the power grid, Let be the power of the virtual control unit participating in primary frequency regulation during time period t. Then:

[0023] ;

[0024] Electric vehicle constraints include:

[0025] (1) Charge and discharge power constraints: , ,in These represent the discharge power and charging power of electric vehicle i during time period t, respectively.

[0026] (2) Charge state constraints: ,in Let i be the battery capacity of electric vehicle i during time period t. and These are the minimum and maximum states of charge for electric vehicles, respectively.

[0027] (3) Time coupling constraint: ,in and These refer to the charging efficiency and discharging efficiency of electric vehicles, respectively. Let i be the battery capacity of electric vehicle i during time period t. The time from the end of the electric vehicle's response to the end of the current time period. The duration for electric vehicles to participate in one frequency regulation;

[0028] Battery energy storage constraints include:

[0029] (1) Charge and discharge power constraints: , ,in: These represent the discharge power and charging power of battery energy storage i during time period t, respectively. This refers to the maximum discharge power of the battery energy storage device. This refers to the maximum charging power of the battery energy storage device. It is a binary variable;

[0030] (2) Charge state constraints: ,in Let i be the battery capacity of the battery energy storage device during time period t. and These represent the minimum and maximum states of charge for the specified battery energy storage. Let i be the battery capacity of the battery energy storage device during time period t.

[0031] (3) Time coupling constraint: ,in and These are the charging efficiency and discharging efficiency of battery energy storage, respectively. Charging efficiency for battery energy storage Charging efficiency for battery energy storage Let i be the battery capacity of the battery during time period t;

[0032] Industrial load constraints include:

[0033] (1) Response capacity constraint: ,in and Let i be the minimum and maximum output of the industrial load i during time period t. Let i be the power of industrial load i during time period t;

[0034] (2) Transition number constraint: ,in t represents the number of transfers of industrial load i, i.e., the total number of times industrial load is turned on and off; t represents the number of time periods, based on the 96 points of the power grid, with a day divided into 96 time periods.

[0035] System constraints include:

[0036] (1) System power balance constraints:

[0037] in: Let i be the discharge power of electric vehicle i during time period t. Let i be the discharge power of the battery energy storage during time period t. The power of the industrial load during time period t;

[0038] During time period t, the sum of the power of all electric vehicles, battery storage, and industrial loads participating in primary frequency regulation, as well as the unfinished tasks of the virtual control unit, should be greater than or equal to the regulation task issued by the power grid.

[0039] Furthermore, based on the simulation analysis results, the output curves of each distributed resource and the revenue of the virtual control unit are obtained under normal and abnormal conditions, thereby achieving optimized allocation of distributed resources, including both normal and abnormal conditions:

[0040] Normally, this means that distributed resources have completed the control tasks assigned by the power grid.

[0041] Abnormal situations, including whether the power deficit has been fully compensated and whether there are any penalty fees, include:

[0042] Scenario 1: Power deficit is fully compensated with no penalty fees;

[0043] Scenario 2: The power deficit cannot be fully compensated and there are penalty fees;

[0044] Scenario 3: Power deficit will not be replenished and there will be penalty fees.

[0045] A virtual control unit frequency response real-time control device, used to implement the steps of any one of the virtual control unit frequency response real-time control methods, including:

[0046] The module for establishing a real-time control model for distributed resources is used to establish a real-time control model for distributed resources based on the reported information and real-time control mode of the distributed resources.

[0047] The control mode design module is used to design online budget and real-time control modes based on the real-time characteristics of the real-time control model and existing control modes.

[0048] The simulation analysis module is used to establish constraint models based on online budgets and real-time control modes, and to perform simulation analysis.

[0049] The optimization allocation module is used to obtain the output curves of each distributed resource and the revenue of the virtual control unit under normal and abnormal conditions based on the simulation analysis results, so as to achieve the optimized allocation of distributed resources.

[0050] Furthermore, the simulation analysis module is used to establish a constraint model based on the online budget and real-time control mode, and to perform simulation analysis. When a large disturbance occurs in the power grid, the main grid side issues control task requirements to the virtual control unit, including lag time, ramp-up time, sustainability time, and power regulation factors. The virtual control unit makes requirements on its subordinate distributed resources, including requirements for adjustability, price regulations for distributed resources participating in primary frequency regulation, and basic requirements for the power recovery capability of distributed resources.

[0051] A computer device includes a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor executes the computer program to implement the steps of any of the above-described virtual control unit frequency response real-time control methods.

[0052] A computer storage medium storing a computer program, wherein when the computer program is executed by a processor, it implements the steps of any one of the following virtual control unit frequency response real-time control methods.

[0053] The present invention has the following beneficial effects and advantages:

[0054] This invention rationally allocates control tasks issued by the power grid to the distributed resources under the virtual control unit, with the goal of maximizing the revenue of the virtual control unit. The revenue of the virtual control unit mainly includes the electricity sales fee for the power sold by the virtual control unit to the power grid, the intermediary fee paid by the distributed resources to the virtual control unit, the electricity purchase fee paid by the virtual control unit to the distributed resources for purchasing power, and the penalty fee that the virtual control unit needs to pay to the power grid if it fails to complete the control tasks issued by the power grid.

[0055] First, we summarize the operating characteristics of electric vehicles, energy storage, and industrial loads, analyze the influencing factors of their operating status, and select reporting information that can concisely and efficiently reflect their operating status, thereby determining the reporting information for distributed resources.

[0056] Based on real-time characteristics and the 96-point specification of the power grid, a suitable time scale is determined, and a "online budgeting, real-time control" control mode is designed in conjunction with the characteristics of existing control modes. The control period is set to 15 minutes, and it is assumed that the operating state of distributed resources remains unchanged during the control period. The control cycle is 30 minutes, and the reporting information of distributed resources is determined 5 minutes in advance. Simulation analysis is performed on all possible disturbances to form a control strategy table.

[0057] The requirements of the main grid side for tasks assigned by the power grid and the requirements of the distribution network side for distributed resources are clearly defined. A model is established with the goal of maximizing the revenue of the virtual control unit, and constraints such as the capacity and power limitations of each distributed resource are used as constraints. Simulation examples are then analyzed.

[0058] When distributed resources are operating normally, they can complete the control tasks assigned by the power grid. Each distributed resource outputs power in sequence according to its cost coefficient, and the virtual control unit receives the highest revenue at this time.

[0059] When a distributed resource encounters an anomaly, the power deficit is supplemented by resources with spare capacity, ultimately enabling the completion of the control tasks assigned by the power grid. There are no penalty fees, but the cost coefficient of the supplementary resources is relatively large, resulting in a decrease in the total revenue of the virtual control unit.

[0060] When the distributed resources encounter an anomaly, the resource reserve is insufficient, and the resulting power deficit cannot be fully compensated. Ultimately, the control task issued by the power grid is not completed, resulting in penalty fees and a further decrease in the total revenue of the virtual control unit.

[0061] When the distributed resources encounter an anomaly (condition three), the cost coefficient of the resource with surplus is too high, and the virtual control unit will not select it for supplementation. Ultimately, the control task issued by the power grid is not completed, resulting in penalty fees and further reducing the total revenue of the virtual control unit.

[0062] In summary, based on the analysis of factors influencing the operational status of three distributed resources—electric vehicles, energy storage, and demand response—this invention determines reporting information that can concisely and efficiently reflect their operational status. Combining existing control processes with the response characteristics of distributed control resources, a suitable rolling control time interval is selected, and a "online budget, real-time control" control mode and its workflow are designed accordingly. Based on the reporting information and control mode, a real-time control model for distributed resources is established. Through optimized solution of the mathematical model, optimized allocation of distributed resources can be achieved, maximizing the benefits of virtual control units while fulfilling the assigned control responsibilities. This invention's method enables distributed resources to participate in main grid frequency control, providing assistance for the construction of new power systems. This invention can effectively aggregate distributed resources, achieve real-time optimized control of frequency response, improve system frequency regulation capability and economic efficiency, and is suitable for formulating real-time control strategies for virtual control units participating in main grid frequency response. Attached Figure Description

[0063] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0064] Figure 1 This is a schematic diagram of the real-time control mode framework of the present invention;

[0065] Figure 2 This is a schematic diagram illustrating the requirements of the main grid side for tasks issued by the power grid in this invention;

[0066] Figure 3 This is a schematic diagram illustrating the revenue structure of the virtual control unit of this invention;

[0067] Figure 4 This is a schematic diagram illustrating the distributed resource output under normal circumstances according to the present invention;

[0068] Figure 5 This is a schematic diagram of the distributed resource output situation under abnormal conditions of the present invention;

[0069] Figure 6 This is a schematic diagram of the distributed resource output situation under the second abnormal condition of the present invention.

[0070] Figure 1 In the diagram: 1 represents time period 1, 2 represents time period 2, and 3 represents time period 3. Detailed Implementation

[0071] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other.

[0072] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0073] The following reference Figures 1-6 The technical solutions of some embodiments of the present invention are described below.

[0074] Example 1

[0075] This invention provides an embodiment of a real-time frequency response control method for a virtual control unit, comprising the following steps:

[0076] Step 1. Establish a real-time control model for distributed resources based on the reported information and real-time control mode.

[0077] The method of this invention uses the reported information of distributed resources as the data basis. The reported information is obtained by summarizing the operating characteristics of distributed resources, reflecting the real-time operating status of distributed resources. This method can maximize the benefits of the virtual control unit and obtain the output status of each distributed resource and the benefits of the virtual control unit.

[0078] The distributed resource reporting information of the present invention includes: electric vehicle reporting information, energy storage reporting information, and industrial load reporting information.

[0079] The information reported by the electric vehicle includes: current state of charge, upper and lower limits of state of charge, rated charging and discharging power, rated capacity, expected state of charge, and off-grid time.

[0080] The energy storage reporting information includes: current state of charge, upper and lower limits of state of charge, rated charge and discharge power, and rated capacity.

[0081] The reported information on the industrial load includes: initial state, transferable capacity, and transferable power.

[0082] Step 2. Based on the real-time characteristics of the real-time control model, determine an appropriate time scale to formulate a control strategy, and design an online budget and real-time control mode in combination with existing control modes.

[0083] The real-time control mode described in this invention is: online budgeting and real-time control. It can be regarded as a micro energy storage unit, but it can only participate in regulation when connected to the grid; the energy storage has bidirectional regulation capability, existing as a load during charging and as a power source during discharging; the industrial load has a large adjustable capacity, is easy to control, and has certain economic advantages.

[0084] According to the 96-point rule of the power grid, the 24 hours of a day are divided into 96 periods, each lasting 15 minutes, which serves as the basis for the division of control periods.

[0085] Based on 96 points of the power grid, a control period of 15 minutes is set, assuming that the operating status of distributed resources remains unchanged during the control period. The control cycle is 30 minutes. The reporting information of distributed resources is determined 5 minutes in advance, and the adjustability of each distributed resource is calculated. Simulation analysis is performed for all possible disturbances to form a control strategy table. In actual operation, if a large disturbance occurs, the control strategy for each distributed resource is obtained by matching the information in the strategy table; if no large disturbance occurs, the operation continues to the next time period.

[0086] It can be regarded as a micro energy storage unit, but it can only participate in regulation when connected to the grid; the energy storage has bidirectional regulation capability, existing as a load during charging and as a power source during discharging; the industrial load has a large adjustable capacity, is easy to control, and has certain economic advantages.

[0087] The workflow of the real-time control mode described in this invention is as follows:

[0088] In the last 5 minutes of time period 1, the power grid issues N commands to the virtual control unit based on the data from the anticipated fault set. The virtual control unit calculates the operating status and adjustability of the distributed resources based on the information reported by the distributed resources, and formulates a control strategy table for time period 2 based on the commands issued by the power grid. In actual operation, if a large disturbance occurs in the power grid during time period 2, the information in the strategy table is used to match and obtain a control scheme for each distributed resource; if no large disturbance occurs, the operation continues into the next time period. To ensure that the distributed resources still have a certain degree of adjustability in time period 3, the operating status of the distributed resources in both control periods within the control cycle needs to be comprehensively considered when formulating the control strategy table.

[0089] Step 3. Establish a constraint model based on the online budget and real-time control mode, and conduct simulation case analysis.

[0090] The real-time control mode of this invention is the core of the theory, clarifying the requirements of the main grid and distribution network sides for distributed resources, and providing a basis for the design of distributed resource constraints. A model is established with the maximization of virtual control unit revenue as the objective function, and the capacity and power limitations of each distributed resource as constraints. Simulation examples are then analyzed to obtain the output curves of each distributed resource and the revenue of the virtual control unit under normal and abnormal conditions.

[0091] When a large disturbance occurs in the power grid, the main grid sends control tasks to the virtual control unit, including elements such as lag time, ramp-up time, duration, and power regulation amount, denoted by T.

[0092] The distribution network side requires the virtual control unit to impose requirements on its subordinate distributed resources, including requirements for adjustability, pricing for distributed resources participating in primary frequency regulation, and basic requirements for the power recovery capabilities of distributed resources, to ensure that distributed resources are capable of completing regulation tasks. Specifically, for distributed resources to participate in the primary frequency regulation of the power grid, a contract must be signed with the virtual control unit, clearly defining all costs associated with their participation, including intermediary fees and electricity purchase costs.

[0093] like Figure 2 As shown, Figure 2 This is a schematic diagram illustrating the requirements of the main grid side for tasks issued by the power grid in this invention. In the requirements of the main grid side for tasks issued by the power grid, the lag time refers to the time from a large disturbance in the power grid to the time when the distributed resources receive the instruction from the virtual control unit and begin to respond; the ramp time refers to the time required for the distributed resources to begin responding and to fully respond; the power regulation amount refers to the actual power adjustment required by the distributed resources when responding to the control instruction; and the duration refers to the time that the distributed resources can maintain this state after reaching the specified power regulation amount. Based on the study of primary frequency regulation of the power grid, this invention sets the total duration of tasks issued by the power grid to 90 seconds.

[0094] The constraint model established based on the online budget and real-time control mode includes:

[0095] Maximizing the revenue of the virtual control unit is the objective function of the model:

[0096] Right now:

[0097] in: The revenue generated from the sale of power from the grid by the virtual control unit. The cost factor representing the power purchased by the power grid from the virtual control unit is then... ; The intermediary fee paid to the virtual control unit for distributed resources. , and Let T represent the power of electric vehicles, energy storage, and industrial load participating in primary frequency regulation during time period t, respectively, where T represents the duration. For intermediary fees, All are binary variables, where N, M, and H represent the number of the three types of distributed resources participating in a single frequency modulation. Then:

[0098]

[0099] in: The electricity purchase fee paid to the virtual control unit for purchasing distributed resource power. Electricity purchase cost coefficients for electric vehicles, energy storage, and industrial loads. and These are the battery compensation fees paid by the virtual control unit to electric vehicles and battery storage, respectively, where: Let i be the discharge power of electric vehicle i during time period t. Let i be the discharge power of the battery energy storage during time period t, then:

[0100]

[0101] in: The penalty fee payable to the power grid by the virtual control unit for failing to complete the control tasks issued by the power grid. As a penalty cost coefficient, For the control and regulation tasks issued by the power grid, Let be the power of the virtual control unit participating in primary frequency regulation during time period t. Then:

[0102] .

[0103] Electric vehicle constraints include: charging and discharging power constraints, state of charge constraints, and time coupling constraints.

[0104] Electric vehicles are a typical type of flexible load, possessing "dual characteristics of load and power source," and their constraints are as follows:

[0105] (1) The charging and discharging power constraint is: , ,in Let i represent the discharge power and charging power of electric vehicle i during time period t, respectively.

[0106] (2) The state of charge constraint is: ,in This represents the battery capacity of electric vehicle i during time period t. The minimum state of charge for electric vehicles is defined as follows. The maximum state of charge for a specified electric vehicle;

[0107] (3) The time coupling constraint is: ,in and These represent the charging efficiency and discharging efficiency of an electric vehicle, respectively. Let i be the battery capacity of electric vehicle i during time period t. The time from the end of the electric vehicle's response to the end of the current time period. The duration for an electric vehicle to participate in a frequency regulation;

[0108] Battery energy storage constraints include: charge and discharge power constraints, state of charge constraints, and time coupling constraints.

[0109] Energy storage has bidirectional regulation capabilities, existing as a load during charging and as a power source during discharging. Its constraints are as follows:

[0110] (1) The charging and discharging power constraint is: , ,in: Let i represent the discharge power and charging power of the battery energy storage i during time period t, respectively. This refers to the maximum discharge power of the battery energy storage device. This refers to the maximum charging power of the battery energy storage device. It is a binary variable;

[0111] (2) The state of charge constraint is: ,in This represents the battery capacity of battery storage i during time period t. and These represent the minimum and maximum states of charge for the specified battery energy storage. Let i be the battery capacity of the battery energy storage device during time period t.

[0112] (3) The time coupling constraint is: ,in and These represent the charging efficiency and discharging efficiency of battery energy storage, respectively. Charging efficiency for battery energy storage Charging efficiency for battery energy storage Let i be the battery capacity of the battery during time period t;

[0113] Industrial load constraints include response capacity constraints and transfer frequency constraints.

[0114] The industrial load has a large adjustable capacity and is easy to control, but its constraints are as follows:

[0115] (1) The response capacity constraint is: ,in and This represents the minimum and maximum output of industrial load i during time period t. Let i be the power of industrial load i during time period t;

[0116] (2) The number of transitions is constrained as follows: ,in This represents the number of times industrial load i is transferred, i.e., the total number of times industrial load is turned on and off; t is the number of time periods, based on the 96 points of the power grid, with a day divided into 96 time periods;

[0117] System constraints include: power balance constraints.

[0118] (1) The system power balance constraint is:

[0119] in: Let i be the discharge power of electric vehicle i during time period t. Let i be the discharge power of the battery energy storage during time period t. The power of the industrial load during time period t;

[0120] During time period t, the sum of the power of all electric vehicles, battery storage, and industrial loads participating in primary frequency regulation, as well as the unfinished tasks of the virtual control unit, should be greater than or equal to the regulation task issued by the power grid.

[0121] Step 4. Based on the simulation results from Step 3, obtain the output curves of each distributed resource and the revenue of the virtual control unit under normal and abnormal conditions, thereby achieving optimized allocation of distributed resources.

[0122] The possible outcomes are divided into two main categories: normal and abnormal situations. The normal situation refers to the distributed resources completing the control tasks assigned by the power grid.

[0123] like Figure 4 As shown, Figure 4This is a schematic diagram illustrating the output of distributed resources under normal circumstances according to the present invention. The distributed resources are capable of completing the control tasks issued by the power grid, and each distributed resource outputs power in sequence according to its cost coefficient. At this time, the virtual control unit has the highest revenue.

[0124] The abnormal situations refer to whether the power deficit has been fully compensated and whether there are penalty fees, including the following three situations:

[0125] Scenario 1: Power deficit is fully compensated with no penalty fees;

[0126] Scenario 2: The power deficit cannot be fully compensated and there are penalty fees;

[0127] Scenario 3: Power deficit will not be replenished and there will be penalty fees.

[0128] like Figure 5 As shown, Figure 5 This is a schematic diagram of the distributed resource output under an abnormal situation according to the present invention. Taking energy storage as an example, the power deficit is supplemented by resources with surplus capacity, and the control tasks issued by the power grid can be completed in the end. There is no penalty fee, but the cost coefficient of the supplementary resources is relatively large, and the total revenue of the virtual control unit is reduced.

[0129] like Figure 6 As shown, Figure 6 This is a schematic diagram illustrating the distributed resource output situation under the second abnormal condition of this invention. Taking energy storage as an example, the generated power deficit cannot be fully compensated, ultimately failing to complete the control tasks assigned by the power grid, incurring penalty fees, and further reducing the total revenue of the virtual control unit.

[0130] This invention addresses the third abnormal situation: distributed resource output. Taking energy storage as an example, if the cost coefficient of resources with surplus capacity is too high, the virtual control unit will not select them for supplementation, ultimately failing to complete the control tasks assigned by the power grid, incurring penalty fees, and further reducing the total revenue of the virtual control unit.

[0131] Example 2

[0132] The present invention provides another embodiment of a virtual control unit frequency response real-time control device, comprising:

[0133] The module for establishing a real-time control model for distributed resources is used to establish a real-time control model for distributed resources based on the reported information and real-time control mode of the distributed resources.

[0134] The control mode design module is used to design online budget and real-time control modes based on the real-time characteristics of the real-time control model and existing control modes.

[0135] The simulation analysis module is used to establish constraint models based on online budgets and real-time control modes, and to perform simulation analysis.

[0136] The optimization allocation module is used to obtain the output curves of each distributed resource and the revenue of the virtual control unit under normal and abnormal conditions based on the simulation analysis results, so as to achieve the optimized allocation of distributed resources.

[0137] The simulation analysis module described in this embodiment is used to establish a constraint model based on the online budget and real-time control mode, and to perform simulation analysis. When a large disturbance occurs in the power grid, the main grid side issues control task requirements to the virtual control unit, including lag time, ramp-up time, sustainability time, and power regulation factors. The virtual control unit makes requirements on its subordinate distributed resources, including requirements for adjustability, price regulations for distributed resources participating in primary frequency regulation, and basic requirements for the power recovery capability of distributed resources.

[0138] The virtual control unit frequency response real-time control device described in this embodiment is used to implement the steps of the virtual control unit frequency response real-time control method as described in Embodiment 1.

[0139] Example 3

[0140] Based on the same inventive concept, embodiments of the present invention also provide a computer device, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor. When the processor executes the computer program, it implements the steps of any of the virtual control unit frequency response real-time control methods described in Embodiment 1.

[0141] Example 4

[0142] Based on the same inventive concept, this embodiment of the invention also provides a computer storage medium storing a computer program, which, when executed by a processor, implements the steps of any one of the virtual control unit frequency response real-time control methods described in Embodiment 1.

[0143] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0144] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0145] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0146] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0147] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A real-time frequency response control method for a virtual control unit, characterized by: include: Based on the reported information and real-time control mode of distributed resources, a real-time control model for distributed resources is established. Design an online budget and real-time control mode based on the real-time characteristics of the real-time control model and existing control modes; A constraint model is established based on the control mode of online budgeting and real-time control, and simulation analysis is performed. Based on the simulation analysis results, the output curves of each distributed resource and the revenue of the virtual control unit under normal and abnormal conditions are obtained, thereby realizing the optimal allocation of distributed resources.

2. The real-time frequency response control method for a virtual control unit according to claim 1, characterized in that: The reported information for distributed resources includes: reported information for electric vehicles, reported information for energy storage, and reported information for industrial loads; the reported information for electric vehicles includes: current state of charge, upper and lower limits of state of charge, rated charge / discharge power, rated capacity, expected state of charge, and off-grid time; the reported information for energy storage includes: current state of charge, upper and lower limits of state of charge, rated charge / discharge power, and rated capacity; the reported information for industrial loads includes: initial state, transferable capacity, and transferable power.

3. The real-time frequency response control method for a virtual control unit according to claim 1, characterized in that: The design of an online budget and real-time control mode based on the real-time characteristics of the real-time control model and the existing control mode is as follows: the 24 hours of a day are divided into 96 time periods, the control period is set to 15 minutes, and it is assumed that the operating state of the distributed resources remains unchanged during the control period. The control cycle is 30 minutes. The reporting information of the distributed resources is determined 5 minutes in advance and the adjustability of each distributed resource is calculated. Simultaneously, simulation analysis is performed on all possible disturbances to form a control strategy table. If a large disturbance occurs, the control policy for each distributed resource is obtained by matching the information in the policy table. If no major disturbances occur, the work will continue for the next period.

4. The real-time frequency response control method for a virtual control unit according to claim 1, characterized in that: The constraint model is established based on the online budget and real-time control mode, and simulation analysis is performed. When a large disturbance occurs in the power grid, the main grid sends control tasks to the virtual control unit, including lag time, ramp-up time, sustainability time, and power regulation factors. The virtual control unit makes requirements on its subordinate distributed resources, including requirements for adjustability, price regulations for distributed resources to participate in primary frequency regulation, and basic requirements for the power recovery capability of distributed resources.

5. The real-time frequency response control method for a virtual control unit according to claim 1, characterized in that: The establishment of the constraint model based on the online budget and real-time control mode includes: Maximizing the revenue of the virtual control unit is the objective function of the model: Right now: ; in: The revenue generated from the sale of power from the grid by the virtual control unit. The cost factor for purchasing virtual control unit power for the power grid is then... ; The intermediary fee paid to the virtual control unit for distributed resources. , and Let T represent the power of electric vehicles, energy storage, and industrial load participating in primary frequency regulation during time period t, respectively, where T is the duration. For intermediary fees, All variables are binary, and N, M, and H represent the number of the three types of distributed resources participating in a single frequency modulation. Then: ； in: The electricity purchase fee paid to the virtual control unit for purchasing distributed resource power. Electricity purchase cost coefficients for electric vehicles, energy storage, and industrial loads. and These are the battery compensation fees paid by the virtual control unit to electric vehicles and battery storage, respectively, where: Let i be the discharge power of electric vehicle i during time period t. Let i be the discharge power of the battery energy storage in time period t, then: ； in: The penalty fee payable to the power grid by the virtual control unit for failing to complete the control tasks issued by the power grid. As a penalty cost coefficient, For the control and regulation tasks issued by the power grid, Let be the power of the virtual control unit participating in primary frequency regulation during time period t. Then: ； Electric vehicle constraints include: (1) Charge and discharge power constraints: , ,in These represent the discharge power and charging power of electric vehicle i during time period t, respectively. (2) Charge state constraints: ,in Let i be the battery capacity of electric vehicle i during time period t. and These are the minimum and maximum states of charge for electric vehicles, respectively. (3) Time coupling constraint: ,in and These refer to the charging efficiency and discharging efficiency of electric vehicles, respectively. Let i be the battery capacity of electric vehicle i during time period t. The time from the end of the electric vehicle's response to the end of the current time period. The duration for electric vehicles to participate in one frequency regulation; Battery energy storage constraints include: (1) Charge and discharge power constraints: , ,in: These represent the discharge power and charging power of battery energy storage i during time period t, respectively. This refers to the maximum discharge power of the battery energy storage device. This refers to the maximum charging power of the battery energy storage device. It is a binary variable; (2) Charge state constraints: ,in Let i be the battery capacity of the battery energy storage device during time period t. and These represent the minimum and maximum states of charge for the specified battery energy storage. Let i be the battery capacity of the battery during time period t; (3) Time coupling constraint: ,in and These are the charging efficiency and discharging efficiency of battery energy storage, respectively. Charging efficiency for battery energy storage Charging efficiency for battery energy storage Let i be the battery capacity of the battery during time period t; Industrial load constraints include: (1) Response capacity constraint: ,in and Let i be the minimum and maximum output of the industrial load i during time period t. Let i be the power of industrial load i during time period t; (2) Transition number constraint: ,in t represents the number of transfers of industrial load i, i.e., the total number of times industrial load is turned on and off; t represents the number of time periods, based on the 96 points of the power grid, with a day divided into 96 time periods. System constraints include: (1) System power balance constraints: ; in: Let i be the discharge power of electric vehicle i during time period t. Let i be the discharge power of the battery energy storage during time period t. The power of the industrial load during time period t; During time period t, the sum of the power of all electric vehicles, battery storage, and industrial loads participating in primary frequency regulation, as well as the unfinished tasks of the virtual control unit, should be greater than or equal to the regulation task issued by the power grid.

6. The real-time frequency response control method for a virtual control unit according to claim 1, characterized in that: Based on the simulation analysis results, the output curves of each distributed resource and the revenue of the virtual control unit are obtained under normal and abnormal conditions, thereby achieving optimized allocation of distributed resources, including both normal and abnormal conditions: Normally, this means that distributed resources have completed the control tasks assigned by the power grid. Abnormal situations, including whether the power deficit has been fully compensated and whether there are any penalty fees, include: Scenario 1: Power deficit is fully compensated with no penalty fees; Scenario 2: The power deficit cannot be fully compensated and there are penalty fees; Scenario 3: Power deficit will not be replenished and there will be penalty fees.

7. A real-time frequency response control device for a virtual control unit, characterized in that: include: The module for establishing a real-time control model for distributed resources is used to establish a real-time control model for distributed resources based on the reported information and real-time control mode of the distributed resources. The control mode design module is used to design online budget and real-time control modes based on the real-time characteristics of the real-time control model and existing control modes. The simulation analysis module is used to establish constraint models based on online budgets and real-time control modes, and to perform simulation analysis. The optimization allocation module is used to obtain the output curves of each distributed resource and the revenue of the virtual control unit under normal and abnormal conditions based on the simulation analysis results, so as to achieve the optimized allocation of distributed resources.

8. The virtual control unit frequency response real-time control device according to claim 7, characterized in that: The simulation analysis module is used to establish a constraint model based on the online budget and real-time control mode, and to perform simulation analysis. When a large disturbance occurs in the power grid, the main grid side issues control task requirements to the virtual control unit, including lag time, ramp-up time, sustainability time, and power regulation factors. The virtual control unit makes requirements on its subordinate distributed resources, including requirements for adjustability, price regulations for distributed resources to participate in primary frequency regulation, and basic requirements for the power recovery capability of distributed resources.

9. A computer device, comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the real-time frequency response control method for a virtual control unit as described in any one of claims 1-6.

10. A computer storage medium, characterized in that: The computer storage medium contains a computer program, which, when executed by a processor, implements the steps of a real-time frequency response control method for a virtual control unit as described in any one of claims 1-6.

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