Power grid load frequency control method, device, equipment, storage medium and program product

Abstract

This application relates to a method, apparatus, device, storage medium, and program product for controlling the frequency of power grid loads. The method includes: constructing an operating model of the power distribution network based on an event-triggered low-frequency control system model and a stability function corresponding to the distribution network; solving the operating model according to preset constraints to obtain an adjustable gain; the constraints are used to ensure the operating model operates in a stable environment; generating a control signal based on the adjustable gain; and controlling the load frequency of the distribution network based on the control signal. By constructing the operating model of the distribution network, the controller gain and communication gain at different triggering times can be calculated, and precise control of the low frequency of the distribution network can be achieved based on the controller gain and communication gain. This realizes targeted frequency control at different times, meeting the frequency requirements of different power consumption scenarios, effectively improving data transmission efficiency while ensuring the stability of the power grid load frequency, and avoiding excessive frequency overshoot.

Description

Technical Field

[0001] This application relates to the field of power system technology, and in particular to a method, apparatus, equipment, storage medium, and program product for controlling the frequency of power grid loads. Background Technology

[0002] With the gradual development of new energy technologies, the intermittency of wind and photovoltaic power generation output and the uncertainty of load demand have exacerbated the dynamic imbalance between active power supply and demand in the power grid, frequently causing frequency deviation problems. To address this, power dispatching centers generally adopt Load Frequency Control (LFC) strategies, using communication networks to monitor frequency deviation information and adjust the output power setpoint of synchronous generators (SGs) to maintain power supply and demand balance in the power grid. In particular, energy storage systems (ESSs), with their rapid response capabilities, participate in LFC as supplementary frequency regulation resources, providing additional frequency regulation capacity and becoming an effective means to enhance power grid frequency stability, attracting widespread attention. However, data interaction between energy storage systems and the power grid control center relies on communication networks, inevitably leading to problems such as data transmission congestion and reduced network bandwidth utilization, which cannot ensure effective data transmission and stable control of the power grid frequency.

[0003] Traditional frequency control methods employ an event-triggered strategy, which uses a fixed-gain trigger controller to regulate the load frequency in the power grid. However, this method suffers from problems such as excessive frequency overshoot and slow convergence speed. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, equipment, storage medium, and program product for controlling the grid load frequency to ensure grid frequency stability, in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a method for controlling the frequency of power grid loads, including:

[0006] The operation model of the power distribution network is constructed based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network.

[0007] The operating model is solved according to the preset constraints to obtain the adjustable gain; the constraints are used to constrain the operating model to work in a stable environment.

[0008] A control signal is generated based on the adjustable gain, and the load frequency of the power distribution network is controlled based on the control signal.

[0009] In one embodiment, the method further includes:

[0010] Obtain the variable gain controller, state function, and disturbance model corresponding to the power distribution network;

[0011] Based on the variable gain controller, state function, and disturbance model, a low-frequency control system model is constructed.

[0012] The low-frequency control system model and the event-triggered communication mechanism are integrated to obtain the event-triggered low-frequency control system model.

[0013] In one embodiment, constructing a low-frequency control system model based on the variable gain controller, state function, and disturbance model includes:

[0014] Based on the variable gain controller, the current state function, and the disturbance model, construct the system state model for the next time step;

[0015] The low-frequency control system model is constructed based on the state function and system matrix at the current moment.

[0016] In one embodiment, fusing the low-frequency control system model and the event-triggered communication mechanism to obtain the event-triggered low-frequency control system model includes:

[0017] By combining the different event triggering times in the event-triggered communication mechanism, the event triggering delay and control error are determined;

[0018] The variable gain controller is updated based on the event triggering delay and control error to obtain a new variable gain controller;

[0019] Based on the new variable gain controller, state function, and disturbance model, the event-triggered low-frequency control system model is constructed.

[0020] In one embodiment, the step of constructing the operating model of the power distribution network based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network includes:

[0021] The stability function is subjected to forward differencing to obtain a differencing-processed stability function, which is then used as the first model term.

[0022] The second model is determined based on the event-triggered low-frequency control system model and the transpose of the event-triggered low-frequency control system model.

[0023] Based on the stability function and the transpose of the stability function, determine the third model;

[0024] Based on the first model, the second model, and the third model, an operational model for the power distribution network is constructed.

[0025] In one embodiment, the constraints include: a first constraint and a second constraint; the first constraint includes a linear matrix less than zero; the second constraint includes an intermediate linear matrix greater than or equal to zero.

[0026] Secondly, this application also provides a power grid load frequency control device, comprising:

[0027] The module is used to construct the operation model of the power distribution network based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network.

[0028] The solution module is used to solve the operating model according to preset constraints to obtain adjustable gain; the constraints are used to constrain the operating model to work in a stable environment.

[0029] The control module is used to generate a control signal based on the adjustable gain and control the load frequency of the power distribution network based on the control signal.

[0030] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0031] The operation model of the power distribution network is constructed based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network.

[0032] The operating model is solved according to the preset constraints to obtain the adjustable gain; the constraints are used to constrain the operating model to work in a stable environment.

[0033] A control signal is generated based on the adjustable gain, and the load frequency of the power distribution network is controlled based on the control signal.

[0034] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0035] The operation model of the power distribution network is constructed based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network.

[0036] The operating model is solved according to the preset constraints to obtain the adjustable gain; the constraints are used to constrain the operating model to work in a stable environment.

[0037] A control signal is generated based on the adjustable gain, and the load frequency of the power distribution network is controlled based on the control signal.

[0038] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0039] The operation model of the power distribution network is constructed based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network.

[0040] The operating model is solved according to the preset constraints to obtain the adjustable gain; the constraints are used to constrain the operating model to work in a stable environment.

[0041] A control signal is generated based on the adjustable gain, and the load frequency of the power distribution network is controlled based on the control signal.

[0042] The aforementioned power grid load frequency control method, device, equipment, storage medium, and program product construct an operating model of the power distribution network based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network; solve the operating model according to preset constraints to obtain adjustable gain; the constraints are used to ensure that the operating model operates in a stable environment; generate control signals based on the adjustable gain, and control the load frequency of the power distribution network based on the control signals. By constructing the operating model of the power distribution network, the controller gain and communication gain at different triggering times can be calculated, and precise control of the low frequency of the power distribution network can be achieved based on the controller gain and communication gain, realizing targeted frequency control at different times, which can meet the frequency requirements of different power consumption scenarios. Compared with the traditional method of adjusting the load frequency in the power grid through fixed gain, which can lead to excessive frequency overshoot, controlling the load frequency through the joint control of controller gain and event-triggered gain can effectively improve data transmission efficiency while ensuring the stability of the power grid load frequency and avoiding excessive frequency overshoot. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a structural block diagram of a computer device in one embodiment;

[0045] Figure 2 This is a flowchart illustrating a method for controlling the frequency of power grid load in one embodiment;

[0046] Figure 3 This is a flowchart illustrating the construction of an event-triggered low-frequency control system model in one embodiment;

[0047] Figure 4 This is a flowchart illustrating the process of constructing a low-frequency control system model in one embodiment;

[0048] Figure 5 This is a flowchart illustrating the construction of an event-triggered low-frequency control system model in another embodiment;

[0049] Figure 6 This is a flowchart illustrating the operation model of a power distribution network in one embodiment;

[0050] Figure 7 This is a schematic diagram illustrating the application of controller gain in one embodiment;

[0051] Figure 8 This is a schematic diagram illustrating the application of controller gain in another embodiment;

[0052] Figure 9 This is a schematic diagram illustrating the application of controller gain in another embodiment;

[0053] Figure 10 This is a schematic diagram illustrating the application of controller gain in yet another embodiment;

[0054] Figure 11 This is a schematic diagram illustrating the application of controller gain in yet another embodiment;

[0055] Figure 12 This is a schematic diagram illustrating the application of the event triggering mechanism at the release time in one embodiment;

[0056] Figure 13 This is an application diagram illustrating the performance output of a power distribution network system in one embodiment;

[0057] Figure 14 This is a flowchart illustrating a method for controlling the power grid load frequency in another embodiment;

[0058] Figure 15 This is a structural block diagram of a power grid load frequency control device in one embodiment. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0060] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0061] With the gradual development of new energy technologies, the intermittency of wind and photovoltaic power generation output and the uncertainty of load demand have exacerbated the dynamic imbalance between active power supply and demand in the power grid, frequently causing frequency deviation problems. To address this, power dispatching centers generally adopt Load Frequency Control (LFC) strategies, using communication networks to monitor frequency deviation information and adjust the output power setpoint of synchronous generators (SGs) to maintain power supply and demand balance in the power grid. In particular, energy storage systems (ESSs), with their rapid response capabilities, participate in LFC as supplementary frequency regulation resources, providing additional frequency regulation capacity and becoming an effective means to enhance power grid frequency stability, attracting widespread attention. Data interaction between energy storage systems and the power grid control center relies on communication networks, inevitably leading to problems such as data transmission congestion and reduced network bandwidth utilization, which cannot ensure effective data transmission and stable control of the power grid frequency. Traditional frequency control methods employ event-triggered strategies, i.e., using fixed-gain trigger controllers to adjust the load frequency in the power grid. However, these methods suffer from excessive frequency overshoot and slow convergence speed.

[0062] In view of the above-mentioned technical problems, this application provides a method for controlling the grid load frequency that can ensure the stability of the grid frequency. The following embodiments will specifically illustrate the method for controlling the grid load frequency.

[0063] The power grid load frequency control method provided in this application embodiment can be applied to, for example, Figure 1 The computer device shown can be a server, and its internal structure diagram can be as follows. Figure 1As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores the frequency, power, and event triggering mechanisms of the power grid system. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for controlling the frequency of the power grid load.

[0064] Those skilled in the art will understand that Figure 1 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0065] In one exemplary embodiment, such as Figure 2 As shown, a method for controlling the frequency of power grid load is provided. This embodiment illustrates the application of this method to computer equipment. In this embodiment, the method includes:

[0066] S201, construct the operation model of the power distribution network based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network.

[0067] The distribution network can be any of the following: traditional distribution network, new energy distribution network, radial distribution network, ring distribution network, ring network type, or distribution cabinet type, or other types of distribution network, with no restrictions. The stability function can be a discontinuous Lyapunov function containing a time-varying matrix. The event-triggered low-frequency control system model includes frequency-controlled event-triggered control functions and variable-gain control functions.

[0068] In the embodiments of this application, the computer device determines the target power distribution network that requires low-frequency control based on scenario requirements, acquires the state information and performance output information of the target power distribution network at different times to construct a low-frequency control system model for the corresponding time, and constructs an event-triggered mechanism for frequency control. The event-triggered mechanism and the low-frequency control system model are then fused to obtain an event-triggered low-frequency control system model, enabling frequency adjustment of the power distribution network at the corresponding trigger time. Finally, the event-triggered low-frequency control system model and a stability function are used to construct an operational model of the power distribution network, which is then fused to obtain the operational model of the power distribution network, ensuring the stability of the power distribution network's performance during load frequency control.

[0069] S202, solve the running model according to the preset constraints to obtain the adjustable gain.

[0070] The constraints are used to ensure the operating model functions in a stable environment, guaranteeing that the output of the power distribution network's operating model is always less than 0. The constraints include a first constraint and a second constraint. The first constraint includes a linear matrix less than zero; the second constraint includes an intermediate linear matrix greater than or equal to zero. The intermediate linear matrix is ​​the exponential linear matrix involved in the linear matrix derivation. The constraints also include given parameters, preset variables, and a set of parameter values. The given parameters can be the event trigger weight matrix, the maximum time delay upper bound, given constant values, and bounded external disturbances. The preset variables can be matrices at different trigger times. The set of parameter values ​​can include the first set. Second set The given parameters and preset variables are the constituent elements of a linear matrix or an intermediate linear matrix. Adjustable gains include event triggering mechanism gains and controller gains at different trigger times.

[0071] In the embodiments of this application, after the operation model of the power distribution network is constructed, for each triggering moment of frequency control, target values ​​are extracted sequentially from the first set and the second set. A linear matrix and an intermediate linear matrix are constructed using given parameters and preset variables for the corresponding triggering moment. These linear matrices and the intermediate linear matrix are then substituted into the first and second constraints respectively for solving, yielding the event triggering mechanism gain and the controller gain for the corresponding triggering moment. After performing the above operations at all triggering moments, the event triggering mechanism gain and the controller gain for each triggering moment are obtained.

[0072] S203 generates a control signal based on the adjustable gain and controls the load frequency of the power distribution network based on the control signal.

[0073] In the embodiments of this application, for the calculated event triggering mechanism gain and controller gain at each triggering moment, the controller gains at all triggering moments are combined into a controller gain matrix, and the event triggering mechanism gain and controller gain matrix are used to generate a control signal, which is transmitted to the low-frequency control actuator of the power distribution network, so that the actuator can perform gain control of power distribution network communication and gain control of load frequency at the corresponding triggering moment.

[0074] The aforementioned method for controlling the power grid load frequency constructs an operational model of the distribution network based on the event-triggered low-frequency control system model and stability function corresponding to the distribution network. The operational model is then solved according to preset constraints to obtain an adjustable gain. These constraints ensure the operational model operates in a stable environment. A control signal is generated based on the adjustable gain, and the load frequency of the distribution network is controlled based on this signal. By constructing the operational model of the distribution network, the controller gain and communication gain at different triggering times can be calculated. Precise control of the low frequency of the distribution network based on these controller and communication gains achieves targeted frequency control at different times, meeting the frequency requirements of different power consumption scenarios. Compared to the traditional method of adjusting the load frequency in the power grid through a fixed gain, which can lead to excessive frequency overshoot, controlling the load frequency through the combined use of controller gain and event-triggered gain effectively improves data transmission efficiency while ensuring the stability of the power grid load frequency, avoiding excessive frequency overshoot.

[0075] In one exemplary embodiment, such as Figure 3 As shown, the method also includes:

[0076] S301, obtain the variable gain controller, state function and disturbance model corresponding to the power distribution network.

[0077] The state function can be either the first difference function between the actual frequency and the rated power of the distribution network, or the second difference function between the actual power and the rated power. The disturbance model can be an energy-bounded external disturbance function; the variable gain controller includes gain control expressions at multiple times. Optionally, the variable gain controller can be represented by the following relationship (1):

[0078] (1);

[0079] In the formula, , , For controller gain, , , These represent different event trigger time intervals; and They represent the times at time 1 and 2 respectively. and The state function.

[0080] In the embodiments of this application, when it is necessary to control the frequency of the target power distribution network structure, the variable gain controller, state function, and disturbance model corresponding to the power distribution network are first obtained. Optionally, the state information of the target power distribution network at different times is collected by sensors, such as actual frequency, rated frequency, actual power, and rated frequency. The difference between the actual frequency and rated frequency at each time moment is calculated, and the difference between the actual power and rated frequency is calculated to obtain the state function at the corresponding time moment. Furthermore, the pre-stored disturbance model and variable gain controller are retrieved from the database so that the low-frequency control system model can be constructed in subsequent events.

[0081] S302, a low-frequency control system model is constructed based on the variable gain controller, state function, and disturbance model.

[0082] In the embodiments of this application, the construction of the low-frequency control system model at the next time step requires the use of the state function, gain control function, and disturbance model from the previous time step. Optionally, after obtaining the variable gain controller, state function, and disturbance model, taking the current time step as an example, the system state model for the next time step is constructed based on the gain control function, state function, and disturbance model of the variable gain controller at the current time step; and the low-frequency control system model is constructed based on the state function and system matrix at the current time step. That is, the gain control function, state function, and disturbance model from any previous time step can be used to construct the system state model for the next time step, and the state function and system matrix from any time step can be used to construct the low-frequency control system model for the corresponding time step.

[0083] S303 integrates the low-frequency control system model and the event-triggered communication mechanism to obtain the event-triggered low-frequency control system model.

[0084] In the embodiments of this application, after obtaining the low-frequency control system model at each moment, the delay and control error at different event triggering moments are determined by combining the different event triggering moments in the event triggering communication mechanism; for each triggering moment, the gain function at the corresponding moment is updated according to the event triggering delay and control error to obtain a new gain control function at the corresponding moment; the new gain control function, state function and disturbance model are fused to construct the event triggering low-frequency control system model.

[0085] The above method can accurately define event triggering and frequency control by constructing an event-triggered low-frequency control system model, so as to obtain the controller gain and communication gain at different triggering times in subsequent calculations, and achieve targeted control of the frequency at different times by accurately controlling the low frequency of the distribution network based on the controller gain and communication gain.

[0086] In one exemplary embodiment, such as Figure 4 As shown, a low-frequency control system model is constructed based on the variable gain controller, state function, and disturbance model, including:

[0087] S401, based on the variable gain controller, the current state function, and the disturbance model, construct the system state model for the next time step.

[0088] In the embodiments of this application, taking the current moment as an example, the gain control function of the current moment is extracted from the variable gain controller, and combined with the state function and disturbance model of the current moment, the system state model of the next moment is constructed.

[0089] S402, construct a low-frequency control system model based on the current state function and system matrix.

[0090] In the embodiments of this application, the current moment is used as an example to obtain the state function and system matrix at the current moment to construct a low-frequency control system model. Optionally, the low-frequency control system model is represented by the following relationship (2):

[0091] (2);

[0092] in, Indicates the step size. and Let these represent the state function and the low-frequency control system model at the current moment, respectively. This represents the perturbation model, specifically the energy-bounded external perturbation function. yes The system state model at the next moment. This is the gain control function at the current moment. , , and It is a system matrix. Controllable.

[0093] The above method can accurately define frequency control by constructing a low-frequency control system model, so as to obtain the controller gain at different triggering times in subsequent calculations, and achieve targeted control of the frequency at different times by accurately controlling the low frequency of the distribution network based on the controller gain.

[0094] In one exemplary embodiment, such as Figure 5 As shown, the low-frequency control system model and the event-triggered communication mechanism are integrated to obtain the event-triggered low-frequency control system model, including:

[0095] S501, combined with the different event triggering times in the event-triggered communication mechanism, determines the event triggering delay and control error.

[0096] In the event-triggered communication mechanism, the different event triggering times are represented by the following relationship (3):

[0097] (3);

[0098] In the formula, To control error, , Indicates the first interval. Indicates the second interval. Indicates the current data transmission time. Indicates the next trigger time. Represents the transmitted state. express transpose, Indicates at time state, and Represents positive integers. Represents the set of positive integers. Indicates the supremacy. and These are the weight matrix and threshold of the event triggering mechanism, respectively.

[0099] Optionally, the delay of event triggering is represented by the following relation (4):

[0100] (4);

[0101] In the formula, Indicates the current data trigger time. Indicates the next trigger time.

[0102] S502 updates the variable gain controller based on the event trigger delay and control error to obtain a new variable gain controller.

[0103] In the embodiments of this application, for each trigger moment, the trigger moment is matched with the time interval of the variable gain controller. If the trigger moment falls within a certain time interval, the gain control function corresponding to that time interval is extracted. The gain control function is then updated using the event trigger delay and control error at that trigger moment to obtain a new gain control function. After the above operation is performed on the gain control functions of all trigger moments, a new variable gain controller is obtained. Optionally, taking the current moment as the trigger moment as an example, the gain control function at the current moment is... The gain control function is updated by taking into account the event trigger delay and control error at the current moment, resulting in a new gain control function. .

[0104] S503, based on the new variable gain controller, state function and disturbance model, constructs an event-triggered low-frequency control system model.

[0105] In the embodiments of this application, after obtaining the new variable gain controller, the state functions at different trigger times, and the disturbance model, for each trigger time, the gain function corresponding to the trigger time is extracted from the new variable gain controller, and the event-triggered low-frequency control system model is constructed by combining the state function and disturbance model at that trigger time. Optionally, taking the current time as the trigger time as an example, the event-triggered low-frequency control system model is represented by the following relationship (5):

[0106] (5);

[0107] In the formula, Indicates the step size. and Let these represent the state function and the low-frequency control system model at the current moment, respectively. This represents the perturbation model, specifically the energy-bounded external perturbation function. yes The system state model at the next moment The delay for the event to be triggered at the current moment. The control error at the current moment, The controller gain at the current moment. , , and It is a system matrix. Controllable.

[0108] In one exemplary embodiment, such as Figure 6 As shown, the operation model of the distribution network is constructed based on the event-triggered low-frequency control system model and stability function corresponding to the distribution network, including:

[0109] S601, perform forward differencing on the stability function to obtain the differencing stability function, and use the differencing stability function as the first model term.

[0110] The stability function can be expressed by the following relation (6):

[0111] (6);

[0112] In the formula, and It is an index in the summation process. This indicates the summation sign. (Selection) and As an adjustable parameter This indicates the time interval between the current trigger time and the next trigger time. It is a given constant value. and They are at time and The constant Lyapunov matrix, and These represent positive definite matrices. In the interval The interior is continuous, within the interval. The interior is discontinuous. Furthermore, for , and It always holds true, thus we can obtain and .

[0113] In the embodiments of this application, after obtaining the stability function, forward differencing is performed on the stability function to obtain the differencing-processed stability function, i.e., the first model. To express.

[0114] S602, Based on the event-triggered low-frequency control system model and the transpose of the event-triggered low-frequency control system model, determine the second model.

[0115] The second model is passed through To express.

[0116] S603, based on the stability function and the transpose model of the stability function, determine the third model.

[0117] The third model, through To express.

[0118] S604, based on the first, second and third models, construct the operation model of the power distribution network.

[0119] In the embodiments of this application, after obtaining the first model, the second model, and the third model, the first model, the second model, and the third model are fused to obtain the operation model of the power distribution network. Optionally, the operation model of the power distribution network is represented by the following relation (7):

[0120] (7);

[0121] In the formula, For the first model, For the second model, For the third model, for Performance boundary.

[0122] The above method ensures that the designed controller enables the low-frequency control system of the power grid to function while conserving network resources. Stablize.

[0123] Optionally, in order to ensure The gain is always less than 0. Constraints are set, and the operating model of the distribution network is solved using these constraints to obtain the adjustable gain. The constraints can be: given parameters... , , and In the case of variables , , , , , , and matrix Then, a variable gain event-triggered controller is constructed for the low-frequency control system of the power grid within different event intervals, such that the following inequality (8) applies to all values. and Both are true:

[0124] (8);

[0125] in, It is a linear matrix. It is the intermediate linear matrix; , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , . Represents the symmetric terms of a matrix. Represents the new matrix, , , , , ,and .

[0126] The values ​​of the set of values ​​are substituted into the above constraints in sequence to solve the problem, and the event triggering mechanism gain and controller gain at all triggering times are obtained, that is, the event triggering mechanism gain and controller gain matrix. The event triggering mechanism gain and controller gain matrix are used to generate control commands and send them to the actuator of the low-frequency control of the power distribution network, thereby realizing the low-frequency precise control of the power distribution network.

[0127] To verify the effectiveness of the above method, assume the disturbance signal... It enters the distribution network system from time zero. Initial parameters are set, and by executing the steps of constructing a low-frequency control system model, an event-triggered low-frequency control system model, and an operational model of the distribution network, the operational model of the constructed distribution network is solved using constraints to obtain adjustable gains, such as... Figure 7-11 As shown. Among them. Figure 7 This represents the gain value in the first column of the controller gain matrix. Figure 8 This represents the gain value in the second column of the controller gain matrix, and so on. Figure 11 This represents the gain value in the fifth column of the controller gain matrix. The release time and time interval of the event-triggered mechanism are as follows: Figure 12 As shown, from Figure 7-12 As can be seen, the controller gain will be updated at different trigger times and maintained until the next trigger time. Furthermore, the system's performance output is the output result of the low-frequency control system model. exist Figure 13 Shown in Figure 13 This indicates that external disturbances have been effectively suppressed. Therefore, the simulation results show that the design method disclosed in this invention is effective.

[0128] In addition to the methods of all the above embodiments, a method for controlling the frequency of power grid load is also provided, such as... Figure 14As shown, the method includes:

[0129] S701, obtain the variable gain controller, state function and disturbance model corresponding to the power distribution network;

[0130] S702, construct the system state model for the next moment based on the variable gain controller, the current state function, and the disturbance model;

[0131] S703, construct a low-frequency control system model based on the current state function and system matrix;

[0132] S704, combining the different event triggering times in the event-triggered communication mechanism, determines the event triggering delay and control error;

[0133] S705 updates the variable gain controller based on the event trigger delay and control error to obtain a new variable gain controller;

[0134] S706, based on the new variable gain controller, state function and disturbance model, an event-triggered low-frequency control system model is constructed;

[0135] S707, perform forward differencing on the stability function to obtain the differencing stability function, and use the differencing stability function as the first model term;

[0136] S708, Determine the second model based on the event-triggered low-frequency control system model and the transpose of the event-triggered low-frequency control system model;

[0137] S709, Based on the stability function and the transpose model of the stability function, determine the third model;

[0138] S710, based on the first, second and third models, construct the operation model of the power distribution network;

[0139] S711 solves the operating model according to preset constraints to obtain adjustable gain; the constraints are used to ensure that the operating model works in a stable environment.

[0140] S712 generates a control signal based on the adjustable gain and controls the load frequency of the power distribution network based on the control signal.

[0141] Each of the above steps has been described in the foregoing embodiments. For details, please refer to the foregoing content. They will not be repeated here.

[0142] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0143] Based on the same inventive concept, this application also provides a power grid load frequency control device for implementing the power grid load frequency control method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more power grid load frequency control device embodiments provided below can be found in the limitations of the power grid load frequency control method described above, and will not be repeated here.

[0144] In one exemplary embodiment, such as Figure 15 As shown, a power grid load frequency control device is provided, comprising: a construction module 151, a solution module 152, and a control module 153, wherein:

[0145] Module 151 is used to construct the operation model of the power distribution network based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network.

[0146] The solver module 152 is used to solve the running model according to preset constraints to obtain adjustable gain; the constraints are used to constrain the running model to work in a stable environment.

[0147] The control module 153 is used to generate a control signal based on the adjustable gain and to control the load frequency of the power distribution network based on the control signal.

[0148] In one exemplary embodiment, the above-described apparatus further includes:

[0149] The acquisition module is used to acquire the variable gain controller, state function, and disturbance model corresponding to the power distribution network.

[0150] The first building module is used to construct a low-frequency control system model based on the variable gain controller, state function, and disturbance model;

[0151] The fusion module is used to merge the low-frequency control system model and the event-triggered communication mechanism to obtain the event-triggered low-frequency control system model.

[0152] In one exemplary embodiment, the first building module described above includes:

[0153] The first building unit is used to build the system state model for the next time step based on the variable gain controller, the current state function, and the disturbance model.

[0154] The second building unit is used to construct a low-frequency control system model based on the current state function and system matrix.

[0155] In one exemplary embodiment, the fusion module includes:

[0156] The determining unit is used to determine the event triggering delay and control error by combining the different event triggering times in the event-triggered communication mechanism;

[0157] The update unit is used to update the variable gain controller based on the event triggering delay and control error to obtain a new variable gain controller;

[0158] The third building unit is used to construct an event-triggered low-frequency control system model based on the new variable gain controller, state function, and disturbance model.

[0159] In an exemplary embodiment, the above-described building module 151 includes:

[0160] The processing unit is used to perform forward differencing on the stability function to obtain the differencing stability function, and uses the differencing stability function as the first model term.

[0161] The first determining unit is used to determine the second model based on the event-triggered low-frequency control system model and the transpose model of the event-triggered low-frequency control system model;

[0162] The second determining unit is used to determine the third model based on the stability function and the transpose model of the stability function;

[0163] The fourth building unit is used to construct the operation model of the power distribution network based on the first, second, and third models.

[0164] In an exemplary embodiment, the solution module 152 includes: a first constraint and a second constraint; the first constraint includes a linear matrix being less than zero; the second constraint includes an intermediate linear matrix being greater than or equal to zero.

[0165] Each module in the aforementioned power grid load frequency control device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0166] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, performs the following steps:

[0167] The operation model of the power distribution network is constructed based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network.

[0168] The operating model is solved according to the preset constraints to obtain the adjustable gain; the constraints are used to ensure that the operating model works in a stable environment.

[0169] A control signal is generated based on the adjustable gain, and the load frequency of the power distribution network is controlled based on the control signal.

[0170] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0171] Obtain the variable gain controller, state function, and disturbance model corresponding to the power distribution network;

[0172] A low-frequency control system model is constructed based on the variable gain controller, state function, and disturbance model.

[0173] By integrating the low-frequency control system model and the event-triggered communication mechanism, an event-triggered low-frequency control system model is obtained.

[0174] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0175] Based on the variable gain controller, the current state function, and the disturbance model, construct the system state model for the next time step;

[0176] Construct a low-frequency control system model based on the current state function and system matrix.

[0177] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0178] By combining the different event triggering times in the event-triggered communication mechanism, the event triggering delay and control error are determined;

[0179] The variable gain controller is updated based on the event triggering delay and control error to obtain a new variable gain controller;

[0180] Based on the new variable gain controller, state function, and disturbance model, an event-triggered low-frequency control system model is constructed.

[0181] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0182] The stability function is subjected to forward differencing to obtain the differencing stability function, which is then used as the first model term.

[0183] The second model is determined based on the event-triggered low-frequency control system model and its transpose.

[0184] Based on the stability function and the transpose model of the stability function, determine the third model;

[0185] Based on the first, second, and third models, construct the operation model of the power distribution network.

[0186] In one embodiment, when the processor executes the computer program, it further implements the following steps: the constraints include: a first constraint and a second constraint; the first constraint includes a linear matrix being less than zero; the second constraint includes an intermediate linear matrix being greater than or equal to zero.

[0187] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0188] The operation model of the power distribution network is constructed based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network.

[0189] The operating model is solved according to the preset constraints to obtain the adjustable gain; the constraints are used to ensure that the operating model works in a stable environment.

[0190] A control signal is generated based on the adjustable gain, and the load frequency of the power distribution network is controlled based on the control signal.

[0191] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0192] Obtain the variable gain controller, state function, and disturbance model corresponding to the power distribution network;

[0193] A low-frequency control system model is constructed based on the variable gain controller, state function, and disturbance model.

[0194] By integrating the low-frequency control system model and the event-triggered communication mechanism, an event-triggered low-frequency control system model is obtained.

[0195] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0196] Based on the variable gain controller, the current state function, and the disturbance model, construct the system state model for the next time step;

[0197] Construct a low-frequency control system model based on the current state function and system matrix.

[0198] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0199] By combining the different event triggering times in the event-triggered communication mechanism, the event triggering delay and control error are determined;

[0200] The variable gain controller is updated based on the event triggering delay and control error to obtain a new variable gain controller;

[0201] Based on the new variable gain controller, state function, and disturbance model, an event-triggered low-frequency control system model is constructed.

[0202] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0203] The stability function is subjected to forward differencing to obtain the differencing stability function, which is then used as the first model term.

[0204] The second model is determined based on the event-triggered low-frequency control system model and its transpose.

[0205] Based on the stability function and the transpose model of the stability function, determine the third model;

[0206] Based on the first, second, and third models, construct the operation model of the power distribution network.

[0207] In one embodiment, when the computer program is executed by the processor, it further implements the following steps: the constraints include: a first constraint and a second constraint; the first constraint includes a linear matrix being less than zero; the second constraint includes an intermediate linear matrix being greater than or equal to zero.

[0208] In one embodiment, a computer program product is provided, comprising a computer program that, when executed by a processor, performs the steps described above:

[0209] The operation model of the power distribution network is constructed based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network.

[0210] The operating model is solved according to the preset constraints to obtain the adjustable gain; the constraints are used to ensure that the operating model works in a stable environment.

[0211] A control signal is generated based on the adjustable gain, and the load frequency of the power distribution network is controlled based on the control signal.

[0212] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0213] Obtain the variable gain controller, state function, and disturbance model corresponding to the power distribution network;

[0214] A low-frequency control system model is constructed based on the variable gain controller, state function, and disturbance model.

[0215] By integrating the low-frequency control system model and the event-triggered communication mechanism, an event-triggered low-frequency control system model is obtained.

[0216] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0217] Based on the variable gain controller, the current state function, and the disturbance model, construct the system state model for the next time step;

[0218] Construct a low-frequency control system model based on the current state function and system matrix.

[0219] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0220] By combining the different event triggering times in the event-triggered communication mechanism, the event triggering delay and control error are determined;

[0221] The variable gain controller is updated based on the event triggering delay and control error to obtain a new variable gain controller;

[0222] Based on the new variable gain controller, state function, and disturbance model, an event-triggered low-frequency control system model is constructed.

[0223] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0224] The stability function is subjected to forward differencing to obtain the differencing stability function, which is then used as the first model term.

[0225] The second model is determined based on the event-triggered low-frequency control system model and its transpose.

[0226] Based on the stability function and the transpose model of the stability function, determine the third model;

[0227] Based on the first, second, and third models, construct the operation model of the power distribution network.

[0228] In one embodiment, when the computer program is executed by the processor, it further implements the following steps: the constraints include: a first constraint and a second constraint; the first constraint includes a linear matrix being less than zero; the second constraint includes an intermediate linear matrix being greater than or equal to zero.

[0229] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0230] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0231] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for controlling the frequency of power grid load, characterized in that, The method includes: The operation model of the power distribution network is constructed based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network. The operating model is solved according to the preset constraints to obtain the adjustable gain; the constraints are used to constrain the operating model to work in a stable environment. A control signal is generated based on the adjustable gain, and the load frequency of the power distribution network is controlled based on the control signal.

2. The method according to claim 1, characterized in that, The method further includes: Obtain the variable gain controller, state function, and disturbance model corresponding to the power distribution network; Based on the variable gain controller, state function, and disturbance model, a low-frequency control system model is constructed. The low-frequency control system model and the event-triggered communication mechanism are integrated to obtain the event-triggered low-frequency control system model.

3. The method according to claim 2, characterized in that, The step of constructing a low-frequency control system model based on the variable gain controller, state function, and disturbance model includes: Based on the variable gain controller, the current state function, and the disturbance model, construct the system state model for the next time step; The low-frequency control system model is constructed based on the state function and system matrix at the current moment.

4. The method according to claim 2, characterized in that, The process of fusing the low-frequency control system model and the event-triggered communication mechanism to obtain the event-triggered low-frequency control system model includes: By combining the different event triggering times in the event-triggered communication mechanism, the event triggering delay and control error are determined; The variable gain controller is updated based on the event triggering delay and control error to obtain a new variable gain controller; Based on the new variable gain controller, state function, and disturbance model, the event-triggered low-frequency control system model is constructed.

5. The method according to any one of claims 1-4, characterized in that, The construction of the power distribution network's operational model based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network includes: The stability function is subjected to forward differencing to obtain a differencing-processed stability function, which is then used as the first model term. The second model is determined based on the event-triggered low-frequency control system model and the transpose of the event-triggered low-frequency control system model. Based on the stability function and the transpose of the stability function, determine the third model; Based on the first model, the second model, and the third model, an operational model for the power distribution network is constructed.

6. The method according to any one of claims 1-4, characterized in that, The constraints include: a first constraint and a second constraint; the first constraint includes a linear matrix being less than zero; the second constraint includes an intermediate linear matrix being greater than or equal to zero.

7. A control device for power grid load frequency, characterized in that, The device includes: The module is used to construct the operation model of the power distribution network based on the event-triggered low-frequency control system model and stability function corresponding to the power distribution network. The solution module is used to solve the operating model according to preset constraints to obtain adjustable gain; the constraints are used to constrain the operating model to work in a stable environment. The control module is used to generate a control signal based on the adjustable gain and control the load frequency of the power distribution network based on the control signal.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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