Verification and optimization method, system and equipment for AGC (Automatic Gain Control) strategy and medium

Abstract

The invention discloses a verification and optimization method and system for an AGC strategy, and belongs to the technical field of power grids. The method comprises the following steps: acquiring whole-process simulation data of a target power grid, and building an offline simulation power grid based on the whole-process simulation data; based on a target AGC strategy, constructing an interaction interface with the off-line simulation power grid; and verifying the target AGC strategy in the offline simulation power grid through the interaction interface based on a pre-constructed typical fault set and a pre-constructed evaluation index, and optimizing the target AGC strategy based on a verification result. The method does not need to use an actual power grid for test verification, and reduces the operation risk of strategy verification in the actual power grid.

Description

Technical Field

[0001] The present invention relates to the field of power grid technology, and more specifically, to a verification and optimization method, system, device and medium for AGC strategy. Background Art

[0002] my country is accelerating the construction of a new power system, and new resources such as wind power, photovoltaics, and energy storage are increasing in the proportion of power grids. Limited by the low inertia of power electronic equipment and the randomness and volatility of new energy output, the real-time balance of power grid active power has become more difficult, and the quality of grid frequency operation has deteriorated.

[0003] Automatic generation control (AGC) is an important means of active power control in power grids, and plays a key role in improving the frequency quality of power grids and ensuring safe and economical operation of power grids. With the large-scale access of new resources such as wind power, photovoltaic power, and energy storage, a large number of AGC control strategies with new resources as the control object have been proposed to improve the level of power grid frequency control. However, unlike conventional regulation resources such as hydropower and thermal power, the control strategy of new frequency regulation resources is more complex, the power grid is more sensitive to control parameters, and the resource controllability is poor. The applicability of the strategy based on existing artificial experience or mechanism analysis and evaluation can no longer meet the needs of the power grid. The direct application of relevant control strategies to the power grid has poor safety and is prone to cause operation accidents. Summary of the invention

[0004] In view of the above problems, the present invention proposes a verification and optimization method for AGC strategy, including:

[0005] Acquire full-process simulation data of the target power grid, and build an offline simulation power grid based on the full-process simulation data;

[0006] Based on the target AGC strategy, construct an interactive interface with the offline simulated power grid;

[0007] Based on the pre-constructed typical fault set and the pre-constructed evaluation index, the target AGC strategy is verified in the offline simulated power grid through the interactive interface, and based on the verification result, the target AGC strategy is optimized.

[0008] Optional, offline simulation of the power grid, including: dynamic models of frequency-related components;

[0009] The frequency-related component dynamic models include, but are not limited to: DC FC model, synchronous machine model, speed regulator model, motor model, static load model, new energy model, virtual inertia model, primary frequency modulation model and AGC model.

[0010] Optional, pre-built sets of typical faults, including:

[0011] A typical set of faults that have an impact on the target AGC policy.

[0012] Optional, typical fault sets that affect the target AGC policy, including but not limited to:

[0013] Steady-state random fluctuation fault set, conventional fault disturbance fault set in different regions and large disturbance fault set.

[0014] Optional, pre-built evaluation metrics, including but not limited to:

[0015] Maximum deviation of disturbance frequency, time consumption of disturbance frequency recovery and frequency root mean square.

[0016] Optionally, the method further includes: deploying an actual power grid according to the optimized target AGC strategy. In another aspect, the present invention also proposes a verification and optimization system for an AGC strategy, comprising:

[0017] Building a power grid unit for acquiring full-process simulation data of a target power grid, and building an offline simulation power grid based on the full-process simulation data;

[0018] Building an interface unit, for building an interactive interface with the offline simulated power grid based on a target AGC strategy;

[0019] A verification and optimization unit is used to verify the target AGC strategy in the offline simulated power grid through the interactive interface based on a pre-constructed typical fault set and a pre-constructed evaluation index, and optimize the target AGC strategy based on the verification result.

[0020] Optional, offline simulation of the power grid, including: dynamic models of frequency-related components;

[0021] The frequency-related component dynamic models include, but are not limited to: DC FC model, synchronous machine model, speed regulator model, motor model, static load model, new energy model, virtual inertia model, primary frequency modulation model and AGC model.

[0022] Optional, pre-built sets of typical faults, including:

[0023] A typical set of faults that have an impact on the target AGC policy.

[0024] Optional, typical fault sets that affect the target AGC policy, including but not limited to:

[0025] Steady-state random fluctuation fault set, conventional fault disturbance fault set in different regions and large disturbance fault set.

[0026] Optional, pre-built evaluation metrics, including but not limited to:

[0027] Maximum deviation of disturbance frequency, time consumption of disturbance frequency recovery and frequency root mean square.

[0028] Optionally, the verification and optimization unit is further used to: deploy an actual power grid according to the optimized target AGC strategy. In another aspect, the present invention also provides a computing device, including: one or more processors;

[0029] a processor for executing one or more programs;

[0030] When the one or more programs are executed by the one or more processors, the above-described method is implemented.

[0031] In yet another aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, the method described above is implemented.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] The present invention provides a verification and optimization method for an AGC strategy, including: obtaining full-process simulation data of a target power grid, and building an offline simulation power grid based on the full-process simulation data; building an interactive interface with the offline simulation power grid based on a target AGC strategy; verifying the target AGC strategy in the offline simulation power grid through the interactive interface based on a pre-built typical fault set and a pre-built evaluation index, and optimizing the target AGC strategy based on the verification result. The present invention can optimize the strategy by verifying the target AGC strategy by building an offline power grid, without the need to use an actual power grid for testing and verification, thereby reducing the operational risk of conducting strategy verification in an actual power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is a flow chart of the method of the present invention;

[0035] Figure 2 It is a schematic diagram of an embodiment of the method of the present invention;

[0036] Figure 3 A flowchart of an embodiment of the method of the present invention;

[0037] Figure 4 A schematic diagram of a monotonic increase and decrease load curve of an embodiment of the method of the present invention;

[0038] Figure 5 It is a minute-level random fluctuation curve fitting diagram of the method embodiment of the present invention;

[0039] Figure 6 A disturbance diagram of the southwest control area showing a comparison of fault disturbances in an embodiment of the method of the present invention;

[0040] Figure 7 A disturbance diagram of the Sichuan control area showing the comparison of the fault disturbance of the embodiment of the method of the present invention;

[0041] Figure 8 A disturbance diagram of the Chongqing control area showing the fault disturbance comparison of an embodiment of the method of the present invention;

[0042] Fig. 9 A DC disturbance diagram for comparing fault disturbances in an embodiment of the method of the present invention;

[0043] Fig.10 A global diagram of the steady-state random fluctuation comparison of the method embodiment of the present invention;

[0044] Fig.11 It is a partial enlarged diagram of the steady-state random fluctuation comparison of the method embodiment of the present invention;

[0045] Fig.12 It is a structural diagram of the system of the present invention. DETAILED DESCRIPTION

[0046] Now, exemplary embodiments of the present invention are described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms used in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention. In the accompanying drawings, the same units / elements are marked with the same reference numerals.

[0047] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0048] Embodiment 1:

[0049] The present invention proposes a verification and optimization method for AGC strategy, such as Figure 1 As shown, including:

[0050] Step 1: Acquire the whole process simulation data of the target power grid, and build an offline simulation power grid based on the whole process simulation data;

[0051] Step 2: Based on the target AGC strategy, construct an interactive interface with the offline simulated power grid;

[0052] Step 3: Based on the pre-constructed typical fault set and the pre-constructed evaluation index, the target AGC strategy is verified in the offline simulated power grid through the interactive interface, and based on the verification result, the target AGC strategy is optimized.

[0053] Among them, the offline simulation power grid includes: dynamic model of frequency-related components;

[0054] The frequency-related component dynamic models include, but are not limited to: DC FC model, synchronous machine model, speed regulator model, motor model, static load model, new energy model, virtual inertia model, primary frequency modulation model and AGC model.

[0055] The pre-built typical fault sets include:

[0056] A typical set of faults that have an impact on the target AGC policy.

[0057] Typical fault sets that affect the target AGC policy include but are not limited to:

[0058] Steady-state random fluctuation fault set, conventional fault disturbance fault set in different regions and large disturbance fault set.

[0059] Among them, the pre-built evaluation indicators include but are not limited to:

[0060] Maximum deviation of disturbance frequency, time consumption of disturbance frequency recovery and frequency root mean square.

[0061] The method further includes: deploying an actual power grid according to the optimized target AGC strategy.

[0062] The present invention is further described below with reference to specific cases:

[0063] The implementation principle of the specific case is as follows Figure 2 The specific implementation steps are as follows: Figure 3 As shown, including:

[0064] (1) Build an offline simulation power grid based on the whole process simulation data; include a complete dynamic model of frequency-related components, including but not limited to DC FC, synchronous machine, speed regulator, motor, static load, new energy, virtual inertia, (new energy) primary frequency regulation, AGC, etc.

[0065] (2) Construct a typical fault set that has an impact on the AGC strategy, including but not limited to steady-state random fluctuations, conventional fault disturbances in different regions (N-1 faults), and large disturbances (DC faults or other N-2 faults).

[0066] (3) Construct strategy applicability evaluation indicators, including but not limited to maximum deviation of disturbance frequency, time required for disturbance frequency recovery, and root mean square frequency.

[0067] (4) Based on the control strategy, an interactive interface with the offline simulated power grid is constructed.

[0068] (5) Based on the fault set constructed in (2) and the evaluation indicators constructed in (3), the strategy verification and optimization are iteratively carried out in the simulated power grid to evaluate the applicability of the strategy.

[0069] (6) Deploy the strategies that pass the applicability assessment to the actual power grid.

[0070] The present invention can reliably verify the applicability of the AGC control strategy without conducting experiments in the actual power grid, and provide a strategy optimization method to reduce the operational risk of strategy verification in the actual power grid and improve the control effect of the AGC.

[0071] In 2019, the Southwest Power Grid and the Central China Main Grid achieved asynchronous interconnection, and the problem of grid frequency stability became prominent. In 2023, the first phase of Kola Photovoltaic was put into operation, and the impact on the "minute-hour" level active power and frequency of the grid increased. How to adjust the existing B coefficient to improve the grid frequency control effect has become a problem.

[0072] Based on this, the present invention is applied to the Southwest Power Grid to verify the present invention. The verification steps include:

[0073] 1) Based on the electromechanical transient simulation data of the Southwest Power Grid, add simulation data such as new energy virtual inertia, new energy primary frequency regulation, DC FC, AGC, etc., establish the "millisecond-second-minute-hour" level full-process dynamic frequency simulation data, and build an offline simulation power grid.

[0074] 2) Construct the maximum capacity unit tripping disturbance and DC lockout fault disturbance in the southwest, Sichuan and Chongqing regions; construct the steady-state random fluctuation formed by minute-level random fluctuation and consistent load increase / decrease fluctuation.

[0075] Set the fault disturbance as follows:

[0076] (1) Xiluodu jump machine in the southwest control area 70W;

[0077] (2) Jintang in Sichuan control area tripped 60W;

[0078] (3) Chongqing control area Luotian jump machine 60W;

[0079] (4) Jinsu DC power rapid drop 200W;

[0080] Steady-state random fluctuations, such as Figure 4 As shown, including the following:

[0081] (1) 750 seconds of “monotonic slow load increase + minute-level random load fluctuation”;

[0082] (2) 750 seconds of “monotonous rapid load increase + minute-level random load fluctuation”;

[0083] (3) 750 seconds of “monotonous rapid load reduction + minute-level random load fluctuation”;

[0084] (4) 750 seconds of “monotonic slow load reduction + minute-level random load fluctuation”;

[0085] (5) 750 seconds of “minute-level random load fluctuation”.

[0086] Minute-level load fluctuation: This is based on the frequency fluctuation curve of the power grid in 2018 when the DC FC was out of operation, the AGC was out of operation, and the dispatcher did not intervene before the Pengshui unit tripped (specific method: reverse the load fluctuation of the power grid from the operating frequency curve, and then set the same load fluctuation in the simulation to obtain the same frequency fluctuation curve). The operating frequency curve and the simulation fitting curve are shown in Figure 2. Figure 5 As shown:

[0087] 3) For fault disturbances, the maximum deviation of disturbance frequency and the time required to recover disturbance frequency are constructed as evaluation indicators; for steady-state random fluctuations, the maximum deviation and root mean square frequency are constructed as evaluation indicators.

[0088] 4) Build the interface between offline simulation data and control strategy module.

[0089] 5) Based on the constructed fault set and evaluation indicators, the strategy verification and optimization are iteratively carried out in the offline simulated power grid until a control strategy that meets the requirements is formed (the specific value of the B coefficient is determined).

[0090] 6) The determined B coefficient is deployed in the Southwest Power Grid, and the original parameters and the new parameters are compared. Figure 6-Figure 11 shown.

[0091] Embodiment 2:

[0092] The present invention also proposes a verification and optimization system 200 for AGC strategy, such as Fig.12 As shown, including:

[0093] Building a power grid unit 201, used to obtain full-process simulation data of a target power grid, and building an offline simulation power grid based on the full-process simulation data;

[0094] A construction interface unit 202 is used to construct an interactive interface with the offline simulated power grid based on a target AGC strategy;

[0095] The verification and optimization unit 203 is used to verify the target AGC strategy in the offline simulated power grid through the interactive interface based on the pre-constructed typical fault set and the pre-constructed evaluation index, and optimize the target AGC strategy based on the verification result.

[0096] Among them, the offline simulation power grid includes: dynamic model of frequency-related components;

[0097] The frequency-related component dynamic models include, but are not limited to: DC FC model, synchronous machine model, speed regulator model, motor model, static load model, new energy model, virtual inertia model, primary frequency modulation model and AGC model.

[0098] The pre-built typical fault sets include:

[0099] A typical set of faults that have an impact on the target AGC policy.

[0100] Typical fault sets that affect the target AGC policy include but are not limited to:

[0101] Steady-state random fluctuation fault set, conventional fault disturbance fault set in different regions and large disturbance fault set.

[0102] Among them, the pre-built evaluation indicators include but are not limited to:

[0103] Maximum deviation of disturbance frequency, time consumption of disturbance frequency recovery and frequency root mean square.

[0104] The verification and optimization unit 203 is further used to deploy an actual power grid according to the optimized target AGC strategy.

[0105] The present invention does not need to use an actual power grid for testing and verification, thereby reducing the operational risk of conducting strategy verification in an actual power grid.

[0106] Embodiment 3:

[0107] Based on the same inventive concept, the present invention also provides a computer device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding functions, so as to implement the steps of the method in the above embodiment.

[0108] Embodiment 4:

[0109] Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It is understandable that the computer-readable storage medium here can include both a built-in storage medium in a computer device and an extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the method in the above embodiment.

[0110] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0111] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0112] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0113] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0114] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0115] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for verifying and optimizing an AGC strategy, characterized in that: include: Acquire full-process simulation data of the target power grid, and build an offline simulation power grid based on the full-process simulation data; Based on the target AGC strategy, construct an interactive interface with the offline simulated power grid; Based on the pre-constructed typical fault set and the pre-constructed evaluation index, the target AGC strategy is verified in the offline simulated power grid through the interactive interface, and based on the verification result, the target AGC strategy is optimized.

2. The method according to claim 1, characterized in that The offline simulation power grid includes: a dynamic model of frequency-related components; The frequency-related component dynamic models include, but are not limited to: DC FC model, synchronous machine model, speed regulator model, motor model, static load model, new energy model, virtual inertia model, primary frequency modulation model and AGC model.

3. The method according to claim 1, characterized in that The pre-built typical fault sets include: A typical set of faults that have an impact on the target AGC policy.

4. The method according to claim 3, characterized in that The typical fault sets that affect the target AGC policy include, but are not limited to: Steady-state random fluctuation fault set, conventional fault disturbance fault set in different regions and large disturbance fault set.

5. The method according to claim 1, characterized in that: The pre-built evaluation indicators include, but are not limited to: Maximum deviation of disturbance frequency, time consumption of disturbance frequency recovery and frequency root mean square.

6. The method according to claim 1, characterized in that The method further includes: deploying an actual power grid according to the optimized target AGC strategy.

7. A verification and optimization system for AGC strategy, characterized in that: include: Building a power grid unit for acquiring full-process simulation data of a target power grid, and building an offline simulation power grid based on the full-process simulation data; Building an interface unit, for building an interactive interface with the offline simulated power grid based on a target AGC strategy; A verification and optimization unit is used to verify the target AGC strategy in the offline simulated power grid through the interactive interface based on a pre-constructed typical fault set and a pre-constructed evaluation index, and optimize the target AGC strategy based on the verification result.

8. The system according to claim 7, characterized in that The offline simulation power grid includes: a dynamic model of frequency-related components; The frequency-related component dynamic models include, but are not limited to: DC FC model, synchronous machine model, speed regulator model, motor model, static load model, new energy model, virtual inertia model, primary frequency modulation model and AGC model.

9. The system according to claim 7, characterized in that The pre-built typical fault sets include: A typical set of faults that have an impact on the target AGC policy.

10. The system according to claim 9, characterized in that The typical fault sets that affect the target AGC policy include, but are not limited to: Steady-state random fluctuation fault set, conventional fault disturbance fault set in different regions and large disturbance fault set.

11. The system according to claim 7, characterized in that The pre-built evaluation indicators include, but are not limited to: Maximum deviation of disturbance frequency, time consumption of disturbance frequency recovery and frequency root mean square.

12. The system according to claim 7, characterized in that The verification and optimization unit is also used to: deploy an actual power grid according to the optimized target AGC strategy.

13. A computer device, characterized in that: include: one or more processors; a processor for executing one or more programs; When the one or more programs are executed by the one or more processors, the method according to any one of claims 1 to 6 is implemented.

14. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed, the method according to any one of claims 1 to 6 is implemented.

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